Emergent Interaction
a Pre-study
Niklas Andersson
Anders Broberg
Agneta Bränberg
Lars-Erik Janlert
Erik Jonsson
Kenneth Holmlund & Jonny Pettersson
UMINF 01.16
DEPARTMENT OF COMPUTING SCIENCE
SE-901 87
SWEDEN
ISSN-0348-0542
i
Emergent Interaction
a Pre-study
Niklas Andersson 1
Anders Broberg 2
Agneta Bränberg 3
Lars-Erik Janlert 4
Erik Jonsson 5
Kenneth Holmlund 6 & Jonny Pettersson 7
UMINF 01.16
DEPARTMENT OF COMPUTING SCIENCE
SE-901 87
SWEDEN
ISSN-0348-0542
1
[email protected]
2
[email protected]
3
[email protected]
4
[email protected]
5
[email protected]
6
[email protected]
7
[email protected]
ii
EMERGENT INTERACTION
- A PRE-STUDY
© 2002, UCIT, Department of
Computing Science, Umeå
University, SE-901 87 Umeå,
Sweden.
Contact: Anders Broberg,
[email protected]
Graphic design: Niklas Andersson.
Illustrations: Niklas Andersson
and Diana Africano.
Typefaces: Adobe Garamond
10/12pt (expert font with ligatures) and Adobe Myriad (with
+50/1000 em tracking).
Printed and bound in Sweden by
UmU Tryckeri, Umeå University.
UMINF 01.16
ISSN-0348-0542
iii
Abstract
This is the final report from a pre-study on Emergent Interaction. The purpose of the pre-study was
to get a clearer idea of what emergent interaction is, what it can be used for, and what the problems
are, as a preparation for a larger study. The project is an Umeå Center for Interaction Technology
(UCIT) and Ericsson Erisoft collaboration, with participants from four UCIT labs (CCL, IDL, DML
and VR-lab) and Ericsson Erisoft Research. It represents the first step of a UCIT research program on
emergent interaction.
An Emergent Interaction Systems consists of an environment in which a number of individual
actors share some experience/phenomenon. Data originating from the actors and their behaviour is collected, transformed and fed back into the environment. The defining requirement of emergent interaction is that this feedback has some noticeable and interesting effect on the behaviour of the individuals
and the collective - that something ‘emerges’ in the interactions between the individuals, the collective,
and the shared phenomenon as a result of introducing the feedback mechanism.
The immediate effect may be enhancement of the individual experience - with resulting effects on
the individual’s behaviour, choice of action, and so on. The immediate effect can also be some kind of
change in the observed, shared phenomenon. In particular the feedback might effect or establish some
kind of collective control. The effect could also involve some kind of organizing and controlling of the
collective. ‘Organization’, in this case, need not imply uniformity and regularity, it could just as well
be to diversify or even randomise behaviours.
Systems in which people interact in a shared feedback loop already exist. What is new with the
emergent interaction research program is a unified approach to such systems, and an agenda that seriously addresses the task of designing EIS. This is made possible and necessary by the new information
technology. Computer, communication, and interface technologies crucially change the conditions and
possibilities. First, the amount and variety of data that is possible to collect, and the speed of collection increase radically. Second, the new information technology offers completely new possibilities to
design and control the feedback function and thus ultimately the behaviour of such systems. Third,
the feedback loops can be speeded up many orders of magnitude to match the ‘natural’ time scales of
individual and collective behaviour, thus also making the existence and importance of such systems
more easily recognisable. Fourth, in this new time scale, with these new capabilities, there are great
opportunities as well as possible hazards that we so far only can guess about.
A number of pre-study activities are summarised in the report. Some of the concrete results are: a
list of focus areas for emergent interaction; a categorisation of emergent interaction applications into
nine categories; a classification of four different aspects of emergent interaction applications; a list of
prototype requirements.
This report will serve as a basic framework for the continued study of emergent interaction within
the UCIT emergent interaction research program. A number of suggestions for the next actions within
this program are also given. First, three possible first prototype implementations (spinning, collaborative art, campus communities) are suggested. They cover a number of aspects that have high priority
for closer investigation. Second, the EI concept should be established in the scientific world as well as
in the commercial world. Third, we have identified a number of research issues to study and ideas to
develop (Emergent Architecture, Emergent Architecture Protocol, Emergent Design are some) within
the emergent interaction field. Other important activities, closely related to but outside of the proper
research program, are market studies and work to get external financing for the program.
iv
v
Acknowledgement
The authors wish to thank the organisations and persons who contributed to the completion of this
report. In particular, we wish to thank our UCIT and Ericsson Erisoft colleagues for providing vital
comments, information, and suggestions during meetings, workshops or over a cup of coffee. Without
this large group of people the content of this report would not have emerged to what it now became.
We would like to give special thanks to the following people; Thomas Pederson for his contribution
to the physical-virtual discussion; the invited speakers at our seminars Ulf Holmgren, Ulf Jonsson,
Magnus Nilsson, Per-Axel Persson, and Erik Stolterman; and Diana Africano for her help with the
illustrations.
vi
Content
1. Introduction
1
2. Background
4
3. Methods and Activities
8
Expected Outcome from the Pre-study
The Outline of this Paper
Human-idea-thing Interaction
Emergence
Enhancement
Workshops and Brainstorming
Focus Areas
2
2
4
5
7
8
9
4. Emergent Interaction Systems
14
5. Application Areas
20
6. Technical System Aspects
34
7. Interaction
48
8. Sociological Aspects
54
9. Data, Information, and Knowledge
57
10. Pre-study Outcome
59
A Functional Model of Emergent Interaction
Control System Perspective on EI Systems
System Architectural Issues
Design Space of EI Systems
Existing Examples
Go with the Flow
The Democratic Process
Web-based Recommendation Systems
Sports arena
Other examples
New Implementations
Ideas for Ei Prototypes
General Aspects of Emergent Interaction Applications
Handling the Negative Aspects
System Architecture
System Architecture for Emergent Interaction Systems
Example of Emergent Interaction System Architectures
Open Issues
Data Communication
Wireless Data Communication
Data Communication in Emergent Interaction Systems
Protocols and Services
Security
Open Issues
Traffic Patterns
Traffic Patterns in Eis
Input Collection from the Actors and their Surroundings
Feeding back Processed Information
Visualising the Information
Building the Actors’ Experience
Open Issues
Open Issues
Open Issues
Designing for Emergence
Emergent Interaction in a Context
Applications
Technical Frameworks
Research and Development Projects
Journals and Conferences
Possible Application Areas
Positive and Negative Aspects
Prototype Requirements
Cost Requirements
Technical Requirements
14
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16
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20
20
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22
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23
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vii
Effect Requirements
Security Requirements
Summary of the Requirements
Open Issues
Suggestions
Implementations
Research and Development
Establishing the Emergent Interaction Concept
Market studies
External financing
Summary
66
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71
Appendix A - Ideas on EI- Application
72
Appendix B - Focus Area Map
78
Appendix C - Collaborative Art
79
References
80
viii
Introduction
1
1. Introduction
This report is the final report from a pre-study on Emergent Interaction (EI) started
in spring 2001. The pre-study project is an Umeå Center for Interaction Technology (UCIT) and Ericsson Erisoft collaboration, with participants from four
UCIT labs (CCL*, IDL#, DML£ and VR-lab¤) and Ericsson Erisoft Research$.
It represents the first step of a UCIT research program on emergent interaction.
Niklas Andersson (IDL), Anders Broberg (CCL) who has also been project
leader for the pre-study, Agneta Bränberg (DML), and Erik Jonsson (Ericsson
Erisoft, AWARE) have been main participants in the projects. Kenneth Holmlund
(VR-lab), Lars-Erik Janlert (CCL), and Jonny Pettersson, have all added valuable
competences to the project. The size of the project has been approximately 1100
hours.
Our project has been inspired by the emergence of applications of a new kind,
such as: Amazon.com (Amazon.com, 2002); GPS art, orienteering, and discovery
(Pryor & Wood, 2001); E-street (MRC, 2001b); IT-hockey (MRC, 2001c); the
SMS/WAP based FriendFinder (Telia, 2001); etc. The interaction between the
individual and the collective is a common theme for these applications, i.e. the
social aspects of the application are in focus. Also significant is the fact that some
of these applications have emerged (all three GPS applications) from individual
use of the technique, in the same sense that the web publishing of personal information emerged from Tim Berner-Lee’s ideas of making the research databases at
CERN available for researchers everywhere in the world. (Berners-Lee, 1990).
An Emergent Interaction System (EIS) is defined to consist of an environment in
which a number of actors share some experience/phenomenon, and in which part
of the interaction among actors in the system emerges via a shared feedback loop.
Data originating from the actors and their behaviour is collected and used to compute a feedback, which is delivered into the environment. The defining requirement of emergent interaction to occur is that this feedback has some noticeable
and significant effect on the behaviour of the individuals and the collective. Something emerges in the interactions between the individuals, the collective, and the
shared phenomenon as a result of introducing the feedback mechanism. The
immediate effect of emergent interaction may be enhancement (see section Background where the term of enhancement is discussed) of the individual experience
– with resulting effects on the individual’s behaviour, choice of action, and so on.
The immediate effect can also be some kind of change in the observed, shared
phenomenon. In particular the feedback might in effect establish some kind of
collective control of it. The ultimate effect could also involve some kind of organising and controlling of the collective. ‘Organization’, need not imply uniformity
and regularity, it could just as well be to diversify or even randomise behaviours.
Systems in which people interact in a shared feedback loop already exist. What
is new with the emergent interaction research program is a unified approach to
such systems, and an agenda that seriously addresses the task of designing EISs.
This is made possible and necessary by the new information technology. Computer, communication, and interface technologies crucially change the conditions
and possibilities. First, the amount and variety of data that is possible to collect,
and the speed of collection increase radically. Second, the new information technology offers completely new possibilities to design and control the feedback
function and thus ultimately the behaviour of such systems. Third, the feedback
loops can be speeded up many orders of magnitude to match the ‘natural’ time
scales of individual and collective behaviour, thus also making the existence and
* http://www.cs.umu.se/research/cogcomp/
# http://www.dh.umu.se/
£ http://www.medialab.tfe.umu.se/
¤ http://www.vrlab.umu.se/
$ http://www.ericsson.com/erisoft/
2
Introduction
importance of such systems more easily recognisable. Fourth, in this new time
scale, with these new capabilities, there are great opportunities as well as possible
hazards that we so far only can guess about.
Expected outcome from the pre-study
To get a clearer idea of emergent interaction, in order to prepare for a larger study
of emergent interaction was the overall purpose for the project. The suggested
purposes for the subsequent main study can be summarised in five sub goals:
•
Create new application/products based on the results
•
Create an understanding of the new possibilities (including dangers) and
techniques for collective control, and control of collectives
•
Create an understanding of the new possibilities (including dangers) and
techniques for social behaviour and applications
•
Create a testing ground for various key technologies and infrastructures
•
Provide new tools for analysing, simulating and understanding social
behaviour
Our work in the pre-study has been guided by three general questions:
•
What can emergent interaction be used for?
•
What are the problems with it?
•
What is the potential of the concept?
To establish an articulated and well-grounded consensus on the concept of emergent interaction is another way to formulate the main purpose of the pre-study.
This report is the concrete result from that process of knowledge and consensus
building. More specifically, this preliminary report on emergent interaction and
emergent interaction systems addresses:
•
Feasibility
•
Usefulness
•
Usability issues
•
Theoretical background and requirements
•
Key research issues
•
Technological requirements
•
Possible application areas
•
Some application scenarios and design sketches
•
Suggestions for whether and how to proceed with a larger project
The Outline of this Paper
There are ten sections in this report, of which the first is the present introduction. The purpose of the second section, Background, is to present three concepts:
enhancement, Human Idea Thing Interaction (HITI), and emergence; all three are
important for the understanding of the background of the pre-study. The purpose
of the third section, Methods and Activities, is to discuss the methods used and the
activities in the pre-study. The purpose of the fourth section, Emergent Interaction
Systems, is to introduce a high-level model of EISs aimed to more strictly discuss,
compare, evaluate, etc EISs; some open research issues are also introduces in this
section. The purpose of the fifth section, Application Areas, is to discuss ideas for
Introduction
3
EI systems and how to assess the value of implementing them. The purpose of
next section, Technical System Aspects, is mainly to discuss emergent interaction
from a technical perspective, where data communication with traffic patterns, and
system architecture are in focus. The seventh section, Interaction, takes an interaction perspective on EIS, by discussion data collection, feedback, timing, etc.
The purpose with section eight, Sociological Aspects, is to take the sociological
and psychological aspects of emergent interaction into account. The purpose with
the ninth section, Data, Information, and Knowledge, is to discuss emergent interaction from a perspective of Computer and Information Science, by discussing
computability, information flows, and system architectural aspects of EISs. The
last section, Pre-study Outcome, discusses how to continue in a more extensive
project with implementation of some prototype, user studies, etc.
In addition, three appendices are included in the report. Appendix A is a summary of all proposals for applications that have been discussed in different forums
during the project. Appendix B is a summary of the intent of each section in the
report and how different focus areas (see page 13 for a discussion on focus areas)
are considered in the report. Appendix C describes an example of emergent interaction application.
4
Background
2. Background
Where do we look for existing concepts, methods, theories and facts that can
help in defining, understanding and developing emergent interaction? Some disciplines and research areas that are obvious candidates for an information search are
sociology, social psychology, ethnology, cognitive science, artificial life, in particular swarm intelligence, control theory, human-computer interaction, computermediated communication. Less obvious fields of research and less widely known
specialties might also have something important to offer. It is impossible in a prestudy to cover emergent interaction from the viewpoint of all possible disciplines
and research areas, but the Focus Areas section is aimed to give as broad view of
emergent interaction as possible. The purpose of this section is to introduce three
important aspects of emergent interaction: human-idea-thing interaction, emergence, and enhancement.
Human-Idea-Thing Interaction
Umeå Center for Interaction Technology (UCIT) was established in September
2000 as a centre for multidisciplinary research grounded on interaction, communication and simulation technology and centred on its use from a human perspective (Janlert, 2002). The purpose is to bring together different branches of
technological science, cognitive science and human-related research, in developing the concepts, theories, methods, technologies and tools that will facilitate the
passage from industrial society to information society. On the central concept of
interaction we take an integrated perspective, taking into account all the different
interconnections and interaction possibilities between the three basic categories
of Humans, Things (material objects) and Ideas (information captured in various
media) - Human-Idea-Thing Interaction (HITI).
Human
Figure 1. Basic typology of
interaction: idea-idea; human-idea;
human-human; human-thing;
thing-thing and idea-thing.
Idea
Thing
Human-Idea-Thing Interaction (HITI) is a concept that extends more traditional
areas of research such as HCI (Human-Computer Interaction) and HMI (HumanMachine Interaction) in important ways, involving several other fields and research
topics. Some examples are Computer-Mediated Communication, Data Communication, Media Research, wireless communication between artefacts, Signal
Processing, Interaction Design, Cognitive Science, High-Performance Computing, Scientific Visualisation, Virtual Reality, Tele-immersion, and more. Whereas
some of these areas include different aspects of human behaviour and human
Background
5
values, the HITI concept makes the human point of view an integral part of the
research endeavour.
Thing stands for all kinds of stationary and mobile physical artefacts – equipped
or integrated with information technology. Idea represents all kinds of information and other meaningful expressions in various forms such as numbers, texts,
pictures, sounds, animations, simulations – that is captured, stored, processed,
presented and transmitted with support of modern information technology. This
categorisation corresponds closely to the social world of people and human behaviour, the information world of databases, documents, media, computation and
communication, and the physical world of everyday artefacts, environments, spaces
and places – all viewed and defined from a human point of view.
The concept of HITI points out the importance of the interconnections and
interdependencies between the three categories of humans, things and ideas, and
the need to consider them in their entirety. For instance, addressing Human-Idea
interaction in separation from Human-Thing and Human-Human interaction we
are prone to neglect the increasingly burdensome role of humans as mediators
between the world of information and the physical world. The HITI concept helps
in identifying and analysing the critical problems and provides a framework supporting creative and innovative development. It suggests, for instance, that information
registered in the handling and operation of some object may be used for further
purposes; that external, remotely accessed information may be utilised to improve
an artefact’s performance, etc. By its comprehensiveness and integrative attitude
the HITI concept invites participation and close cooperation with the humanities
and the social sciences, involving subjects such as philosophy, sociology, ethnology, linguistics, art, and more.
By considering the interactions between humans, things and ideas as a whole,
the HITI approach opens for discovery of new combinations, new patterns of
relationships and new user behaviour. The privileged perspective is that of the
user. How do we allocate and distribute knowledge and information between our
mind, our body, our tools and informational, social and physical environments?
How do we shape things and environments to fit them to our bodily, sensory and
cognitive capabilities, to please and engage our hands, eyes and minds, and to
facilitate everyday life? A close collaboration between researchers from the humanistic and social sciences and researchers from the natural and technological sciences will be a condition for a successful result.
Emergence
The global behaviour of a simple system that consists of a few simple subparts can
often be predicted. But when a system gets sufficiently complex, i.e. with spatial
and/or temporal consequences due to local interactions between many subparts
and/or more complex subparts, it usually becomes difficult to predict the global
behaviour of the system. This means that it becomes an often exceedingly difficult
task to divide the system into its subparts, analyse each subpart and then draw
conclusions about how these subparts will produce a collective global behaviour.
In other words, it is the interaction between the subparts that is the interesting
phenomena and that is also hard to predict.
Emergence concerns such behaviours that arise when subparts interact in a sufficiently complex system.
Emergent behaviour can be observed in any sufficiently complex system, natural or artificial. An example from nature is ants. Each ant is believed to use a few
simple rules that guide their local behaviours. They are not believed to have any
global view of the ant society that they are part of, or obeying any direct global
control. One example is how they find the shortest way to food. When an ant
walks it deposits a pheromone trail on the ground, and when an ant chooses direction it will choose with higher probability those directions marked by a stronger
6
Background
pheromone concentration. The overall effect is that the ants together find the
shortest way. The reason is that a shorter way will receive a higher concentration
of pheromones than a longer way, since it takes less time to walk a short way than
a long way.
Another example is human beings. A human being consists of a large amount
of cells. These cells are organized into different organelles. An organelle displays
an emergent behaviour that cannot be anticipated from just inspecting the cooperating cells. These organelles cooperate to form a human being, which is also
hard to explain behaviourally by just looking at the different organelles. And if
we look at how different human beings interact in a population, it is also hard to
predict the emergent behaviours of that population.
As can be seen by these examples, emergent behaviours are characterised by two
main properties. First, it is difficult to predict the global emerging behaviour by
just inspecting the subparts. Second, it is hard decide which subparts to use to get
a particular desired global emergent behaviour. Emergent behaviours are further
characterised by:
•
The emergent behaviour is determined in a bottom-up way.
•
The subparts that are involved in determining the global behaviour are
distributed.
•
The global behaviour arises from local determination of behaviour in each
participating subpart.
•
As can be seen by the human beings example, emergent behaviours can
arise on all levels.
All this implies that emergent interaction systems are hard to design and that it is
hard to foresee all resulting emerging behaviours that emerge from the system.
Although the term emergence has become very popular for describing everyday phenomena there is still no consensus how emergence should be formally
described in scientific terms. There are no formal definitions and we cannot
through analysis of a real system or a model system tell whether the system shows
true emergent behaviour or if the behaviour just resembles an emergent one.
There is therefore a risk that the term is used as a substitute and an excuse for
lack of knowledge (i.e. a theory or model) about the system of interest.
Many scientists have devoted their work much of their time to search for
the universal properties and a formal definition of emergence. Several of these
attempts are done within a fairly new research field called Computational Mechanics (Crutchfield & Young, 1989). Computational mechanics is a method for
inferring causal architecture – represented by a mathematical object called the
e-machine – from observed behaviour. The e-machine captures all patterns in
the process that have any predictive power, so computational mechanics is also a
method for pattern discovery.
Within this framework Shalizi has recently suggested a more rigorous definition of emergence:
“One set of variables, A, emerges from another, B if (1) A is a function of B,
i.e., at a higher level of abstraction, and (2) the higher-level variables can
be predicted more efficiently than the lower-level ones, where “efficiency of
prediction’’ is defined using information theory.”
(Shalizi, 2001)
We will not go further into how to actually measure the “efficiency of prediction”
as it is beyond the scope of this report, but merely conclude that a formal theory of
emergence would be an invaluable tool when attempting to approach emergence
from a design and implementation perspective.
Background
7
Enhancement
Enhanced experience has been used earlier as a keyword in the Arena project
(MRC, 2001a). Enhancement may apply either to emotion or to understanding,
or to both. Note, that it is difficult and not always such a good idea to completely
separate emotion and cognition.
Emotional enhancement, some different types of:
•
empathy or emotional identification with agents in shared experience – an
agent may be a person, it might also be a group or team of persons – it
could be an animal or a herd of animals, and it could also be some kind of
artefact, a robot, a car, a machine, or even a group of such more or less animated objects (such as the cars flowing around you in the Monday morning
traffic) – opening interesting perspectives of perceiving and understanding
our technological environment in emotional terms
•
sensual amplification and/or transformation of the shared experience –
basically making events appear louder, brighter, more colourful, earth-shaking, etc. – can also involve transformations making signals not normally
picked up by our senses experienceable, may also involve synaesthetic
crossovers to different modalities and senses – the same techniques may of
course just as well be used for the purpose of enhancing understanding
•
expression of own emotions – magnifying (compare above) natural expression of emotions so as to make a stronger impression, or supporting better
articulated, more nuanced expressions, or even providing new means, new
outlets of expressing emotions difficult or impossible to express otherwise
– similar techniques may again be used to enhance cognitive expression
•
collective sense of togetherness, of being part of the collective is another
plausible target for emotional enhancement, particularly in emergent interaction
Cognitive enhancement, some different types of:
•
commenting information – annotating the experience (phenomenon) with
history, statistics, prognosis, etc.
•
hyper reality – enabling experiencing what normally is unperceivable
(hidden, beyond the visual spectrum, etc.), compare note above on sensual
amplification
•
overview – adding multiple, alternative perspectives to the normal single
point of view of an individual, getting an ‘objective,’ generalised viewpoint
•
attention – helping to focus on the relevant information in the middle of
information and sensation chaos
•
evaluation – providing various value assessment of the experience, opinions, grading, comparisons, etc.
•
analysis – support for deeper understanding of the processes involved in
the experienced phenomenon.
8
Methods and activities
3. Methods and Activities
The activities in the project have mainly been of analytic character: weekly project
meetings, literature studies, seminars, workshops and brainstorming. We have had
both internal and external activities. The purpose with the internal activities has
mainly been to push the knowledge of the concept further on. The purposes with
the external activities have been to spread our ideas and to get new influences into
the project. All activities during the project can more or less be traced back to two
activities: a workshop on a high level model for EISs, and brainstorming sessions
on research issues (Focus Areas).
The overall purpose with this section is to give an insight in the project and the
methods and activities used to fulfil the project goal. More than twenty recorded
project meetings have been completed within the frame of the pre-study. These
meetings has functioned as the base for the project and kept the project running.
The atmosphere at these meetings has been open-minded and constructive.
To establish a common, well-informed and articulated view on how emergent
interaction should be understood, we have also arranged a number of seminars.
The following topics were selected: wireless networks, sensor technologies, system
architecture, communities, and social psychology. Seminars for all topics except
social psychology have been given. The following seminars were given as public
seminars:
•
Seminar on Wireless network by Ulf Holmgren and Ulf Jonsson, Department
of Applied Physics and Electronics, Umeå University
•
Seminar on Sensor technologies by Per-Axel Person, Department of Applied
Physics and Electronics, Umeå University
•
Seminar on System Architecture by Magnus Nilsson, Ericsson Erisoft.
•
Seminar on Communities by Erik Stolterman, Department of Informatics
Umeå University.
Two other seminars was arranged in association with the project:
•
External seminar on emergent interaction by Anders Broberg at Department of Computing Science, Umeå University
•
Internal seminar about the Ericsson Erisoft’s project ARENA/ICE by Erik Jonsson Ericsson Erisoft.
In summary, the project has been filled with a broad spectrum of activities. The
weekly meetings have stood for the continuity in the project, where the progress
of the project has been discussed (well documented in the minutes from the
meetings). The seminars have stood for the widening of the knowledge and for
the establishment of the EI concept. The workshop activities have stood for the
creativity in the project where many new interesting ideas and views have been
proposed and reviewed. The literature studies have stood for the analysis and contextualisation of the concept. The writing activities have stood for the synthesis of
forming a whole of the parts. The rest of this section discusses the workshop and
brainstorming activities.
Workshops and Brainstorming
We have had six workshops or brainstorming sessions, three of them have been
internal to the project or extended to include other UCIT-staff. The first workshop was aimed to identify and discuss areas of interest from an emergent interaction perspective. This activity is discussed below in this section. The result
Methods and activities
9
from this workshop has ruled much of the activity later in the project, and the
process of developing and discussing these focus areas has continued throughout
the whole project. The second workshop was aimed to discuss the structure of this
report and there is not so much to present from that workshop beside the fact that
this report is a result. The third workshop was aimed to discuss a high-level model
for EISs.
The other three activities have been external. The first two directed to Ericsson staff to discuss applications of emergent interaction and propose prototype
applications, and to discuss positive and negative aspects of these proposals. The
result is discussed in section Application Areas. In all these application workshops
the same method was used – The six thinking hats (Adams, 2002; APTT, 2001).
The method of The Six Thinking Hats is aimed to structure and focusing the
meeting activities, i.e. divide the informative, creative, positive review, negative
review, feeling, and conclusion activities into isolated sessions.
Focus Areas
Twentyone focus areas were identified to be of interest for the study of EIS. Each
of these areas are described below with a short definition: what is the intention
with this area; what interesting issues are there to resolve; what possibilities and
opportunities can be identified?
Application areas
There could be a large number of different application areas for emergent interaction systems, considering that emergent interaction phenomena can be found in
a wide range of cases: from swarms of termites (Resnick, 1994) to economical
systems, in biological systems (Green, 1993), in the emerging of new life forms in
the biological evolution, and definitely in large groups of people. The main interest of this focus area is to identify possible application areas for emergent interaction systems. Section Application Areas elaborates and exemplifies the variety of
applications for EI.
Categories and characteristics
There are groups of actors in almost all forms of communities, actors with a similar way to act, behave, think, etc. These groups or categories of actors can be characterised by several parameters such as: how well known the group is, what makes
it a group (the way they act, think, etc.), how active the group is, how easy it
is to identify a group or members of a group, the awareness of being a member,
the dynamics of the group, etc. The main issues in this focus area have to do
with mechanisms to identify groups and group members and mechanisms to control the behaviour of different kinds of groups in EI systems. There is a need to
develop relevant ways to characterise groups (interesting parameters). Some areas
with high relevance for this focus area are:
•
Collaborative filtering
•
Social navigation
•
Clustering algorithms, LSA, SOM, K-nearest neighbours, and SVM.
Communication
How will the communication between the different parts of an EI system take
place? Different techniques, protocols and equipment should be evaluated. Wireless communications, packet data, TCP/IP, Bluetooth, synchronous/asynchronous,
delays, throughput, packet loss, bit errors, user roaming and mobility, security,
multicast, unicast, broadcast, etc., are examples of questions and sub-areas to look
into.
10
Methods and activities
Communities
A community is a group of people with something in common, and that something is in focus for their communication. There are two main reasons why communities are of interest for EI. First, EISs can be used to support the emergence,
maintenance, and the phase-out of communities. Second, a lot of research concerning different aspects of communities has been done, from studies covering
quite technical aspects to studies covering more sociological and psychological
aspects of communities, and studies in between (Stolterman, 2001). A community can be characterised by a number of characteristics. An open question is
which of the characteristics of a community that are relevant for EI systems.
Computability Aspects
Theoretical and practical limits of time and memory resources constrain what can
be computed. We need to analyse the most important computation tasks in terms
of time and memory requirements, and find out what it is that characterises these
computations. It would also be of interest to study different computing paradigms
and how well they suit EISs, for example centralised versus distributed computing.
Control Systems
An emergent interaction system has some resemblance to an ordinary control
system (Doeblin, 1985). Control system theory talks about input, output, feedback and timing, for instance. What is the purpose of the system? Do we have
a servo problem or a regulator problem? In the servo problem the goal is for the
output to follow a given reference input. In the regulator problem on the other
hand the goal is to keep the output at a constant level. The system could be adaptive or fixed. The complexity of the system is of course essential. If the system is
too simple and predictable it is of less interest to us. Generally, we may expect
emergent interaction systems to be much more complex than the typical control
system dealt with in control systems theory.
Data Collection
Data collection is a central part of an EI system. Which information is collected
and how it is collected are important issues. What kind of data is can be made
available and what can we do with that data? Which data would seem to be
needed in order to do what we want? The data can be of different kinds, e.g. user
input and data from sensors. Other issues are how complex or basic the collected
information is. Is the same kind of data collected from all users all the time?
Democratic and Undemocratic systems
An EIS collects data from actors in the system; if the system treats data from
all actors equally the system is a democratic system. If the system treats the actors
unequally it is an undemocratic system. It is also possible to imagine systems that
dynamically change their democratic/undemocratic behaviour. For example, in
the normal case the system is a democratic system, but under some circumstances
the system turns into an undemocratic system, giving one or several actors a more
prominent role in the feedback loop. Some of the interesting issues are social: how
and when is it considered appropriate to use a democratic or an undemocratic
system? There are also computational aspects of implementation, such as how to
implement the control mechanisms.
Feedback
Feedback is essential; without it there is no dynamics in the system. The content
of the feedback is closely connected to what the goal of the EIS is. This focus area
is concerned with the form of the feedback: what forms of feedback are possible
and what forms of feedback will be able to effectively reach the actors, eventually
affecting their behaviour. Big displays for everyone, or small displays, one for each
user? Should everybody have the same feedback? What kind of feedback should it
Methods and activities
11
be? Visible, audio, smell, changing the temperature, air/gas, are some of the alternatives. Should all actors be aware that there is a feedback? What the form of the
feedback is? What the content of the feedback is? Should the feedback (normally)
be conscious or unconscious? Close to the actors or in the background? Should
the feedback be direct or indirect?
Model
The main issue in this focus area is to create a high-level functional model for
emergent interaction systems. This model can be used in several ways, for example, to:
•
explain the concept of emergent interaction
•
identify and classify existing phenomenon in terms of emergent interaction
•
support the design phase of new emergent interaction systems
In section four, Emergent Interaction Systems, such a high-level model is presented
and discussed.
Physical-Virtual Systems
An emergent interaction process can take place largely (but not completely, as
long as the human beings in it make use of their bodies) in the virtual world,
like the “rating systems” that some web-based bookshops have. An example of a
system with a more even mix of physical and virtual components is MRC’s IThockey project (MRC, 2001c), where the main shared phenomena is a physical
activity, and a virtual media is used for the presentation. It is also possible to have
situations where emergent interaction takes place entirely in the real world, for
instance a theatre where the audience takes an active part in the production. We
need a model for emergent interaction that covers the whole range of the physicalvirtual scale.
Ongoing research in physical-virtual systems tries to explore the interaction
possibilities that emerge from integrating the physical world with the virtual
world. Depending on research interest, the virtual world can range from being the
content in the environment provided by one single cellular phone, to the entire
Internet based on and accessed through networked computers. The explored
physical-virtual environments are often tuned towards specific application areas
such as: digital augmentation of existing physical environments, information visualisation, CSCW, tele-presence, education, simulation, and art. Physical-virtual
research finds inspiration in related areas such as Ubiquitous Computing (Weiser,
1991), Tangible (Ishii & Ullmer, 1997) and Graspable (Fitzmaurice, Ishii, &
Bricks, 1995), User Interfaces, Mixed Reality (Ohta & HideyukiTamura, 1999),
and Augmented Reality (Mackay, Velay, Carter, Ma & Pagani, 1993).
Fundamental research issues include how to create interactive systems that
allow users to make optimal use of the two worlds’ unique features, decrease the
costs of shifting between physical and virtual environments in the middle of tasks,
sense users’ physical activities, how to make high-level interpretations of physical
and virtual activities, make cause-effect relationships in physical-virtual environments appear as natural as in physical environments.
* Mostly interaction on a user
interface level
Presentation and Interaction
The area of “Presentation and Interaction” concerns the part of the system that is
the most “visible” for the users. How will the users experience this new kind of
system and how will they interact with it*? This area will be most active in the
latter phases of the EI project. The work will build on the findings and results
from the focus areas of Psychology, Feedback and User Awareness, among others.
12
Methods and activities
Psychology and Sociology
EISs are systems engaging a number of people forming a collective – in some sense
an emergent unit created and maintained by the shared phenomenon and the
feedback. How does such a collective “think” and “act”? What do we mean with
thinking in this case? How do mass phenomena like collective panic or hysteria
happen? What kind of feedback will different kinds of people react to? What kind
of feedback will different persons react differently to, and what kind of feedback
will different persons react in the same way to? How do behaviour patterns spread,
what makes them grow and what make them die? These are some examples of
questions focusing on the sociological and psychological aspects of EI. It is obvious that this is a very important focus area, the human actors being by far the most
complex components of an EI system.
Scenarios
Scenarios are fictional stories, with characters, events, products and environments.
They allow us to explore product ideas and key themes in the context of a realistic future. The stories always have a visual element – because they are the vehicle for expressing visual design ideas and interactions between people and things.
Sketches, photographs and video or computer simulations might provide the
visual element. The choice of medium depends on whether we want to depict
behaviours, which benefit from dynamic rendering like animation. We might also
want to use sound. Scenarios range from single page renderings and sketchy references of product concepts to detailed multiple frames of interaction sequences.
The choice depends upon the resolution level of the design at that point.
Security
EISs is a kind of applications where security, integrity, and privacy issues call for
attention – people want to be left alone, they are afraid of being logged, and
they worry about data being transmitted in a secure way. There may be risks of
losing the control over the system with an escalation of unwanted effects. There
is the risk that an unauthorised person takes control, which definitely could cause
unwanted effects. It is important that secure transmission of data and authorisation issues are solved for EIS architectures.
Simulation
Simulation can be used as a tool to test and examine the concept of EI systems
and explain how they work. Different emergent interaction systems can be tested
through simulations. Different techniques, architectures and application areas can
be illustrated and evaluated. What to simulate and how to do it needs to be investigated. Another issue to resolve is how to handle the results from the simulations.
Identifying new research areas could also be an output from this work.
System Architecture
System architecture is about identifying which components, logical and physical,
an EI system can be compiled of. The roles of each component need to be specified. Issues such as scalability, centralised or distributed architecture, dedicated
or public systems, etc need to be investigated. Different architectures can be proposed for different purposes, situations, and variants of EI systems.
System Awareness
The system perspective of awareness deals with questions related to user modelling, i.e. to make the system aware of the ongoing processes in the “shared
phenomenon” and its surrounding, but also questions such as direct or indirect
feedback and foreground/background aspects of feedback. The important issue is
to identify properties of EIS to make it easier to choose techniques for user modelling and design the feedback.
Methods and activities
13
Timing
If the feedback is too slow in an EIS, the persons involved might lose interest.
On the other hand, if the response is too fast and the pace becomes too high, the
result might be that the system runs away, producing unwanted effects. Clearly,
the timing aspects of EISs are important. If the timing should be considered fast
(or slow) depends on what the users know about the system. Other factors important in considering timing, is if the system is synchronous or asynchronous. Real
time is also an important issue. What is to be considered real time and what is
not?
Traffic patterns
The traffic in an EI system will create patterns. Different systems and applications
can create different traffic patterns. The composition of the traffic, the amount
of data, variation and symmetry are examples of properties that can identify patterns. Which categories of patterns can be identified and how can they be handled? Can the traffic be altered to create, remove and/or change the traffic patterns
in a system? The ability of different technical solutions to handle different traffic
patterns is another issue.
User Awareness
The user perspective of awareness deals with psychological and cognitive aspects
of users’ awareness, for example the level of awareness of users participating in
an EIS, and the level of awareness of their possibility to affect, etc. Important
issues are to identify and characterise levels of user awareness, maybe create taxonomies.
14
Emergent Interaction Systems
4. Emergent Interaction Systems
An EIS is an environment with a number of actors who share some experience/
phenomenon, and whose behaviour is significantly influenced by a shared feedback loop picking up data from the individuals and their actions. From that perspective, emergent interaction is not new as a phenomenon. The next section,
Application Areas, gives some examples of existing EISs with no or little involvement of data communication and computer controlled feedback. It also shows
the great potential that sensor technologies, data communication, and computercontrolled feedback add to this kind of complex systems.
The purpose with this section is to discuss a high-level model of emergent
interaction that covers the important aspects of emergent interaction and points
to some open research issues related to the concept. The section is divided into
three parts. The first part, A Functional Model of Emergent Interaction, analyses
EISs in terms of a number of different logical units. The second part, Control
System Perspective on EI Systems, makes some reflections on the similarities between
control system and EISs. The third part, System Architectural Issues, demonstrates
the openness of the model by giving two examples of system architectures.
Emergent interaction is a concept that appears to be related to ideas in many
different areas, such as social navigation, communities and collaborative filtering;
and many sciences, e.g. social psychology, ethnology, control theory, and computing science study related questions. In this situation a slightly more formal model
will be helpful for several reasons. First, it serves as a consistent conceptual framework for discussing emergent interaction, also across different disciplines. Second,
it can be used to identify and discuss existing phenomena as cases of emergent
interaction. Third, the design and implementation of EISs needs a basic model as
a guide. Note that the functional model proposed here is not a system architecture
design nor a model of the traffic pattern generated in EISs — the model leaves
many of the aspects related to these issues open, serving rather as a framework for
discussing those aspects.
A Functional Model of Emergent Interaction
In a typical EIS, the actors and other functional units in the system are logically
divided into a few distinct categories, e.g. the players, the referees and the audience, etc., in an ice hockey arena. Another characteristic of EISs is that they are
situated in a context. That makes it relevant to talk about EISs that interact. One
consequence is that the boundary of a particular EIS, physically and logically,
is rather pragmatically determined. A third characteristic of EI systems is their
dynamic character: an EIS can be a part of some larger EIS, that also can be a part
of something larger, and EISs are momentarily defined by which units and sub
EISs that are up and running.
Our functional model of an EIS is displayed in Figure 2, and the logical units
are explained below:
Shared Phenomenon, a (partially) shared and synchronous experience or
phenomenon that has an existence independent of what the PID and the
feedback system might deliver (but whose particular content and development in time may be affected by the emergent interaction). There is always,
on some sufficiently general level some kind of shared ‘reality’, like the
current traffic situation, a sports arena, a theatre, the weather or the stock
market, etc. If the shared experience gets too thin, abstract, and/or incoherent, however, the whole set-up will become rather uninteresting.
The Actors are participants in a shared phenomenon from which data can
be collected. The actors play different roles, some of them are more in focus
and other act more in the background, e.g. the players and the audience.
Their roles and participation may shift over the time.
Emergent Interaction Systems
15
Feedback
Shared
phenomenon
Actor
f (...)
PID
f (...)
Data
Weight
functions
Administration
f (...)
Compile
and
Compute
Figure 2. A functional model of an
emergent interaction system.
Application
External
input/output
Weight Functions make it is possible to control the “importance” or the
impact that an actor or group of actors has on the behaviour of an EIS. It
is possible to apply weight functions f(…) to each actor’s data stream, and
also make changes to them.
Personal Interaction Devices hereafter ‘PID,’ could be cellular phone, PDA,
wearable computing technology, some remote sensing tracking technology, etc., in collective use. It is a fundamental part of the assumptions that
several people use these devices.
Compile and Compute Unit hereafter ‘CCU’, is obviously a key parameter
of the whole process. By choosing different functions to compute the feedback, we would expect quite different effects (including failure to produce
any significant effect). The informed choice of what information to feed
back should be a basic step towards predicting and controlling emergent
interaction towards desired overall effects.
The data can be data from the use of the PID (for some other and primary
purpose), it can be more elementary personal data such as position data
and biosensor data, and it can be data explicitly and deliberately input or
captured by the actor for the very purpose of the EIS. Environmental data
not stemming from the individual actors can also be used. The figure above
shows these two possible sources, data going from the PIDs and from the
shared phenomenon itself to the Compile and Compute Unit.
The feedback can be a shared presentation (in any kind of medium). It can
also be some other kind of result or change in the shared phenomenon
that is collectively valid. That means that the result is objectively the same
for any individual and not tailored to specific individuals as such. The ultimate effect (importance, meaning, consequences, etc.) of the result on the
individual may however vary and be context dependent. As a simple example, you might be able to directly experience (parts of ) the result only at
certain locations and orientations, so you will miss out on (or be spared)
that (partial) result unless you happen to be there or you move to that area
and face that direction. That kind of circumstantially selective effect may
clearly be an important part of the process.
Administration facility gives the potential to start up, maintain, and close
down the system, but also gives the potential to control the behaviour in
an EIS. The control can be in form of restraining or emphasizing the input
from individuals or groups. A particularly simple way of manipulating the
feedback function is to adjust individual inputs with different weights.
External output is the output of an EIS to some other EIS; this kind of data
feed to the outside world can be broadcasted or directed.
External input comes from other EISs in the surroundings, directed or
broadcasted, requested or not.
16
Emergent Interaction Systems
Application is a system set-up dedicated to some high-level purpose or
event, e.g. theatre, interactive art, etc. Section Application Areas, discusses
different applications and identifies nine groups of emergent interaction
applications. There are several parameters that can be used to characterise
an application, such as openness, software, kind of sensors, distribution (in
time, space, and among individuals), timing, security, integrity, etc.
Control System Perspective on EI Systems
From a technical point of view an EIS has much in common with a control system
for the process industry. Of course the behaviour of systems where humans and
interaction between humans are in focus are far more complex, with a larger dose
of indeterminism. The intention with running an EIS where the emergence of the
unexpected is in focus is very different from the intention with running control
systems for a process industry where the controlled process is in focus. Still, in
discussing EISs and building a functional model EISs, there is much in the notion
of a control system that is useful.
“…understanding emergence has always been about giving up control, letting
the system govern itself as much as possible, letting it learn from the footprints”
(Johnson, 2001)
It is a well-known behaviour for most systems that the value of the output, at
a given time, not only depends of the value of the input at that time, but also
depends on earlier values of the input. Systems that “remember” old inputs are
called dynamic systems. A static system on the other hand means that the output
only depends on the current input.
A common definition of the regulation problem is “to decide, with knowledge
of the output, an input, such that the system’s purpose is fulfilled”. But what is
the purpose of the system? Well, the “system’s purpose” can be very hard to define.
Take a minute and think about the economical system of a country. What is the
purpose of that system?
The two most common ways to define the purpose of a system is, the servo
problem and the regulation problem. In the servo problem the goal is for the
output to follow a given reference input. In the regulator problem the goal is to
keep the output at a constant level.
In any case there should be some kind of feedback to form a closed loop
system. The feedback could be either positive or negative. Positive feedback means
that a piece of the output it brought back to the input, adding to the original
input, resulting in a drift of the output towards a maximum level or even starting an oscillation. Negative feedback on the other hand can be used to stabilise a
system. The system can be a first-order or a second-order system. It can be overdamped or underdamped. Both transient responses and steady-state responses can
be relevant parameters to think about and measure. Timing is important in a control system as well as in an emergent interaction system. For more information
about control systems, see (Doeblin, 1985).
System Architectural Issues
The functional model leaves many options open for the system architecture
design. The same model can be implemented using several different architectures.
That leaves many other issues are open as well, since the architecture affects traffic patterns, system awareness issues, etc. In order to highlight the openness of
the model and to emphasize some critical issues, two architectures are shortly
described below: the ad-hoc architecture (decentralised) and the client server
architecture (centralised).
Emergent Interaction Systems
17
Basically, an Emergent Architecture (EA) is compiled of autonomous units (more
or less centralised); each unit is dedicated to some high-level function. The basic
functionality that every unit has is the potential to interact with other units in
their surroundings. The ad-hoc architecture has one-to-many communication as
the main principle for the interaction. A client server architecture has one-to-one
communication as the main principle for the data collection and one-to-many
communication in the feedback (see the discussion in section Technical System
Aspects concerning the communication aspects). In addition to the interaction
potential, the units have a high-level functionality that is a combination of basic
functionalities, such as:
•
Sensor/measure
•
Presentation
•
Compile and compute
•
Administration
The emergent interaction concept has a potential to open up a new market, a
market for emergent interaction units, such as personal devices/tools, presentation
units. Below is a list of examples of such units. PIDs – are basically units with
a combination of sensor and presentation functionality, aimed for the personal
interaction. The PIDs, especially in ad-hoc solutions have some level of a compile
and compute functionality that makes them more autonomous. Public Displays
– are units with presentation functionality, aimed to present public information.
It is possible to imagine intelligent displays with a compile and compute functionality added, especially in an ad-hoc architecture. Status units – are basically
units with sensor functionality, they measure and report some aspect of the system
status. Application Server Units – are basically administration units for EI applications. An application server serves actors with information about kinds of applications possible to join and application software general and dedicated. One such
unit can administrate several applications. Bridge Units – are used to bridge spatial
distances in EIS, and to connect one EIS with other EISs. They have very simple
compile and compute functionality. System Awareness Units – are basically units
Figure 3. Examples of EIS architectures. Left: An ad-hoc decentralised architecture, with a very loose
infrastructure for the communication.
Right: An Emergent System based
on a centralised architecture,
where all the communication goes
via a central CCU.
with a compile and compute functionality, they are aimed to keep track of the
behaviour in the system, or part of the system. History is also a function of the
system awareness units.
The simplest way to explain ad-hoc architectures is to say that they copy the
LEGO™ concept. They are architectures with a very loose infrastructure, but a
well-defined interface or protocol that gives a high level of flexibility. There are
many interesting research issues for this kind of architecture, e.g. to study traffic
18
Emergent Interaction Systems
patterns in order to make the communication more efficient, security issues, etc.,
but the most outstanding issue is the design of the protocol.
Client Server architectures (CSA) are more traditional architectures for distributed system. The main idea in this kind of architecture is to centralise the intelligent functionality in the system to one unit, and to have dummy clients that
interact via this unit. That means that all sensors, PIDs, and feedback units, in an
EIS talk with each other via a central unit, and the compile and compute functionality is also in this hub (see Figure 3).
Design Space of EI Systems
The emergent interaction concept and the functional model of emergent interaction systems imply a systematic approach to a broad range of applications in
which interaction between the collective and the individuals is a common theme.
New computer, communication, and interface technologies give us entirely new
possibilities to design EI systems. In fact, a vast design space opens before us:
•
First, the amount and variety of data that is possible to collect and the
speed of collection are radically increased. There are now sensors for
almost any basic physical variable, and we can make massive, real-time
and continuous data collections to maintain very complex models of the
environment.
•
Second, the feedback loops can be speeded up many orders of magnitude,
and can be made to match the ‘natural’ time scales of individual and collective behaviour. The computerised CCU makes it possible to control and
dynamically vary response times.
•
Third, manipulation of the weight functions gives a relatively simple way
to control the behaviour of the system. For example, amplify the feedback
from quiet individuals in order to calm the collective.
•
Fourth, the computerised CCU offers completely new possibilities to design
and control the feedback function, without any real limit to the complexity.
•
Fifth, continuously updated environment models can be used to study and
simulate collective behaviour. In some situations one may choose to run
the system in simulation mode, switching off (parts of ) the data collection,
e.g. to avoid a system break down because of traffic overload.
Size
Earth's
population
Time
City, region
Single
individuals
Centuries
Day
Centralised
Instant
Decentralised
Level of
centralisation
Figure 4. The time, size, and decentralisation design space.
Emergent Interaction Systems
19
This makes for a highly complex design space. We may try to bring some order
into this space by distinguishing different dimensions, different design parameters, such as time, size, democracy, technical solutions, etc. Even though the scope
of this report is very broad – twenty-one focus areas described in the previous section! – many dimensions of the design space are just mentioned in passing, and
surely some are not even mentioned.
Figure 4 highlights three (rather coarse) design dimensions of EI systems,
which are important from a model and system architecture perspective:
•
Time — the response time of the feedback, the speed of emergence, the
speed of pattern propagation (if there are such phenomena), the time-span
of an event are some of the factors having to do with time. Although
perhaps not necessarily correlated with each other, we have simplified and
collapsed them into one dimension; intuitively, an EIS can be fast or slow.
•
Size — the number of actors, units, the area spanned by the shared phenomenon, the actors, etc. Again, several measures are collapsed into one.
•
Centralisation level — the compile and compute function can be completely centralised; the other extreme is to let it be distributed over all the
actors and units in the event.
We note that the conditions for a market for EI units discussed above are totally
different for the ad-hoc architecture approach and the client-server architecture
approach. The ad-hoc situation implies a market built up around standard protocols for the interaction between the units, i.e. a LEGO approach. The client-server
situation implies a market built up around a fixed infrastructure, i.e. a system
design approach. Where the ad-hoc situation implies an open and flexible market,
like the market for web-application based on the http protocol, the client-server
situation has more in common with traditional design of information system.
Irrespective of the system architecture, however, the design of a protocol for the
interaction between EI units is a central research issue.
20
Application Areas
5. Application Areas
One purpose with this pre-study has been to discuss and suggest applications of
EISs. Several activities have been aimed to that purpose: a brainstorming session
on existing examples; a workshop focused on possible applications/prototypes to
implement; and a brainstorming session on requirements for implementation of
hypothetical prototypes. This section summarizes these activities. First, we discuss
some existing examples of EISs. Then, some ideas for new implementations of
EISs are introduced, and the question of how to evaluate these proposals is discussed.
Existing Examples
It is possible to identify a number of examples of emergent interactions in our
daily lives. In many of these examples the compile and compute part plays an
inconspicuous role and the data is not collected under controlled forms. The following list is far from a complete list of existing EIS; it serves more to give an
idea of the breadth of the concept. In order to study the impact and the consequences of the introduction of computerised emergent interaction artefacts, these
examples can serve as starting points for construction of scenarios. Each example
is illustrated with an instance of the high-level model from previous section. An
attempt to visualise the placement of the example into the time, size, and level of
centralisation dimensions of EISs complements the model instance.
Go with the Flow
In today’s industrialized world where almost every teenager has a mobile phone,
which they use to interact and communicate with their friends, information travels fast among groups of youths. It is now possible for them to have an idea of
what it is going on in a much larger area than before. One effect is that youths
at youth centres tend to go with the flow as movements become more “visible” to
them, and it has consequently become harder for the adult community to have
control over the situation. This system is distributed with a very decentralised
compile and compute, and with no external control (see Figure 5). We note that
this kind of phenomena has some characteristics in common with ant algorithms
and similar computational mechanisms (Bonabeau, Dorigo & Theraulaz, 1999).
Time
Instant
Day
Centuries
Size
Single individuals
City, region
Earth's population
Level of centralisation
Centralised
Decentralised
Figure 5. Having the control of the
overall situation.
Application Areas
21
The Democratic Process
The political system in a democratic society is a good example of emergent interaction, with many kinds of actors participating (politicians, different pressure/
interest groups, ordinary citizens, etc). Politicians and the rest of the society interact via a shared feedback loop, e.g. politics - public opinion survey - politics- public
opinion survey - politics - elections - politics - public opinion survey - … Public opinion surveys and elections have the compile and compute functionality. They may
also produce feedback direct in form of statistics etc, but also more indirect in
form of new political constellations and activities. The shared phenomenon in a
democratic process is the democratic society. Concrete results such as new buildings, roads, laws, etc are a part of it. The laws rule a democratic process, and the
laws and the control mechanisms for the laws serve as the external control of this
kind of system (see Figure 6). Moreover, democratic processes are not isolated
entities. They are situated in a larger context in which they interact with other
processes. Political trends and how they spread in the world community exemplify
this.
Time
Instant
Day
Centuries
Size
Single individuals
City, region
Earth's population
Level of centralisation
Figure 6. The democratic process in
a community.
Centralised
Decentralised
Web-based Recommendation Systems
Collaborative filtering or recommendation systems like those on web shops, e.g.
amazon.com, MovieLens, alexa.com, etc, serve as examples of another kind of EIS
where the physical and time distances can be extremely large. The system tracks
the articles that different customers buy, in order to present this information for
other customers buying the same article. E.g. some people that buy Astrid Lindgren’s “The Tomten” also buy Elsa Beskow’s “Peter in Blueberry Land”. Another
form of data collection is the possibility for the customers to rate the articles,
which is used to compute an average rating for the articles in the shop based on
the customers’ judgement. Characteristic for such applications beside the large
distances between the different actors in the system is that very much of the
system is in a virtual/digital world, which implies that it is relatively easy and
cheap to collect data, compile and compute, and produce feedback in a centralised
way (see Figure 7).
Time
Instant
Day
Centuries
Size
Single individuals
City, region
Earth's population
Level of centralisation
Figure 7. Virtual application.
Centralised
Decentralised
22
Application Areas
Sports arena
A sports arena with a sport event in focus and several kinds of actors (players,
referees, spectators, coaches, etc) all with their specific roles in the arena is also a
good example of an EIS. More or less every actor in a sport arena adds something
to a shared phenomenon via a shared feedback loop.
•
The audience reacts to the actions of the players, coaches, other spectators,
and referees.
•
The players react to the actions of coaches, referees, audience, other players, etc.
Basically, every actor in a sport arena has some level of the compile and compute
function. Further more, the CCU is traditionally focused on the interaction
between the referees to the audience via the speaker, e.g., which of the players
that scores, the reason to cancel a goal, etc. The speaker takes part of the referees’
interpretation of the game and from that produces a visual and/or audio feedback
to the other actors in the shared phenomenon. It is also possible to identify actors
taking a more salient role of the compile and compute task, e.g. cheer leaders,
media actors, etc. (see Figure 8)
Time
Instant
Day
Centuries
Size
Single individuals
City, region
Earth's population
Level of centralisation
Centralised
Decentralised
Figure 8. Sport events.
Other examples
The examples above give an impression of the wide scope of emergent interaction, with one example from the digital world (Web-based recommendation systems), one from a mix of digital and physical world (the democratic process), one
from the world of sports, and one example of a social phenomenon (the youths
example). The four examples share many characteristics; they also differ in many
characteristics. A democratic process is quite slow compared to a hockey game. A
web-based recommendation system has a quite explicit purpose of compiling and
computing information from the participating actors in the system, in contrast to
the other three. It is an important research issue to identify useful characteristics
of EISs. Such list will be a valuable tool in the design of EISs as well as for the
evaluation of EISs.
Time
Instant
Day
Centuries
Size
Single individuals
City, region
Earth's population
Level of centralisation
Centralised
Decentralised
Figure 9. Knowledge creation
Application Areas
23
It is possible to imagine other examples that illustrate the extremes of EISs. E.g.
the view of knowledge as a social construction (the view of a common phenomenon, such as the conception of the world) is an example of an extremely slow
EIS. It also exemplifies an EIS where the feedback is just distributed to the actors
and does not affect the shared phenomenon directly, which is quite opposite to
the democratic system example (see Figure 6 vs. Figure 9). Dance floors, traffic
systems, theatre events, exhibitions, music festivals, and aqua parks are all example
of systems for which the emergent interaction model is relevant.
New Implementations
In some sense, the media interest for MRC’s IT-hockey project and similar
projects (articles in newspapers and more technical journals) may be taken as a
sign that the time is ripe for EI systems. One goal of this pre-study was to suggest
EI applications suitable to implement as prototype systems. A number of brainstorming sessions has been the main activity in this invent phase. The result is
about seventy ideas (see Appendix A, for the results from these sessions), which
have been reviewed and compiled into nine categories:
•
Knowledge Society Events
•
Exercising Events
•
Home Activity Events
•
Public Space Events
•
Professional Events
•
Political Events
•
Communication Events
•
Arena Events
•
Community Events
The key ideas in each category are discussed below. Identifying pros and cons
with each application idea was part of the brainstorming sessions. The discussion
can be summarised in terms of a number of key ideas and four different types
of aspects: effects, implementation, values, and security. The results from these
activities serve also as input to a discussion about the feasibility and usefulness
aspects of EIS reported in section Pre-study Outcome.
The effects aspect concerns how the EIS affects the actors, environment, society, etc. These effects tend to be rather specific for a particular application. The
implementation aspect concerns the possibility to implement EI applications:
technical demands, how difficult it is to find a test group, how difficult to collect
and interpret data, etc. Also these issues tend to be rather specific for the application, but not as specific as the effects. The values aspect is a bit more general: is it
good or bad? fun or boring? easy or hard to get financial support? etc. The security
aspect is about taking care of privacy, security, and integrity. These issues are quite
general, especially in their negative aspects.
The rest of this subsection is dived into three parts. The first part makes a
walkthrough of the application ideas from the brainstorming sessions. The second
part discusses various aspects of emergent interaction applications. The third part
discusses in quite general terms how to handle the negative aspects of EI applications.
Ideas for EI Prototypes
We have identified nine clusters in the seventy proposals for EI applications. The
resulting categorisation should be viewed as a provisional mind tool for thinking
24
Application Areas
about EIS and not as a definite way to categorise emergent interaction events;
some of the proposals may fit multiple categories. The aim with this section is to
describe the categories, give some examples from each category, and present some
possible positive and negative aspects for each category of events. The tables in
each of the clusters summarise the results from the brainstorming activities. They
should obviously not be taken as complete and reliable lists of relevant aspects of
EI, but are still useful as a first indication of plausible beliefs about emergent interaction applications. There is much work to be done to make these tables more
complete and to verify what peoples in general really believe about these things.
Obviously, still more important than what people may think about these hypothetical systems in advance is what the objective effects and the objective requirements and consequences with regard to implementation, values and security are
in the fully implemented and working system.
Security
Implementation
Effects
Knowledge Society Events
We view much of our known knowledge as quite stable entities, and we call them
facts. One important aspect of these facts is that they to great extent have emerged
in the society as a social phenomenon. It is easier to see that knowledge is an emergent social phenomenon if weaker knowledge constructs such as notions, understandings, views, etc. are taken into consideration. E.g. our conception of the
world has developed from the belief that the earth is the centre of the universe to
the view most of us have today that earth plays a very minor role in the universe.
Our knowledge about the universe has not been fixated, however, cosmological
research is a very active field and our conception continues to change. On a more
individual base, a view of knowledge as something that emerges over time in an
individual’s interaction with a community is fruitful (Broberg, 2000). In short,
knowledge can be considered to be a social entity (Vygotsky, 1978). The systems
in this category are aimed to support the emergence of knowledge on the individual level or on the society/community level, or both. Some examples of prototypes from the workshop activities are classroom situation, knowing what one knows
and doesn’t know, what is hot or not in a research field, and Self-knowledge.
Positive aspects
Negative aspects
+ Can make the classroom more appealing
+ Experience/ event
+ Quality
+ Wake up the students
+ Involvement
+ Effectiveness of resources
+ Possibilities to stop harassment, bullying
_ Brainwashing
_ Stress
+ Knowledge is an emerging and social phenomena
+ New phenomenon/behaviour
_ Dangerous to lose the control of the system
_ Integrity
_ Privacy issues
Exercising Events
Physical exercise in a group (spinning, aerobics, dance, etc.) is a quite common
activity in today’s modern society. The idea is to make exercise less boring and
more enjoyable; to enhance the experience by doing it together. It has been shown
in social psychology research that the individual’s performance of quite individualised activities like biking, solving crossword puzzles, etc., typically increases
when done collectively, even without any direct help from each other (Asplund,
1987). The interaction in the collective is through a shared feedback loop, in
Table 1. Aspects of Knowledge
Society Applications.
Application Areas
25
Negative aspects
Effects
+
+
+
+
+
More effective
Easy to enhance the experience
Pepping
Feedback to the leader
Good for your health
_ Risk for self oscillation
_ Unpredictable
Implementation
Table 2. Aspects of Exercising
Applications.
Positive aspects
+
+
+
+
+
+
+
+
+
+
+
+
Categories
Profiles
Clear border
Closed community
Distributed
Dynamic
Nearness
Easy to measure
Often regular activity
Receptive persons
High acceptance for data collection
Social activity
_
_
_
_
_
_
_
Values
some kind of social interaction. In the case of physical exercise there is often a
dedicated person (leader) having control over the feedback loop. What we have
here is essentially an EIS, but without the involvement of computerised compile
and compute, data collection, and feedback. The question is if computerisation
would make it possible to enhance the experience even more. The proposals in
this category are aimed to enhance the experience, and to widen the concept of
collaborative exercising. Some examples are spinning, aerobics, dancing, and swimming.
+ Atmosphere
+ Cool
Hard to start
One-track
Short-term
Too narrowed activity
Not everyone is doing it
What to measure
How to give feedback
_ Hard to replace the human leader
_ Removes tradition
Home Activity Events
A large part of life is spent at home. A rough estimation is that we spend at least
50% of our time in our homes eating, sleeping, cleaning, watching TV, etc. Most
of these home activities are quite closed; i.e. we do them alone or in small groups
in privacy. The key idea for the applications in this category is to support the
emergence of communities focused on home activities: i.e. to create applications
aimed to make them easier, more fun, feel affinity, etc. Some examples are eating
dinner, 9 o’clock in front of the television set, sleeping and home economy administration.
Effects
Implementation
+
+
+
+
+ Not yet IT-polluted
Security
Table 3. Aspects of Home Activity
Applications.
+ Positive influence on what people are eating
Values
Positive aspects
Common experience
Everyday activity for everyone
Many social navigation possibilities
Social activity
Negative aspects
_ Somewhat hard to measure (taste)
_ Privacy issues
26
Application Areas
Professional Events
We have entered the knowledge or information society, a society where more
and more labour has to do with knowledge, e.g. communication and refinement
of data and information. Journalists, stockbrokers, designers, architects, and
researchers exemplify the growing category of knowledge workers. Knowledge
work tasks also become more and more involved in all kinds of work (Fällman,
2001). Knowledge work typically has the very useful and appreciated property
that it can be distributed in a way physical work often can not. We may safely
assume that IT will continue to be used to cut the costs for travel, to cover larger
areas, to bring together widely dispersed competencies and resources, etc. As a
result the physical distance between workers may increase, with fewer face-to-face
contacts. Therefore, there is a need for applications supporting people’s sense of
presence over a distance. The applications in this category are aimed to support
activities associated with professional activities. Some examples are meeting, factory floor, problem solving and design and empathy training/development.
Effects
+
+
+
+
+
Implementation
+ Easy to collect data
+ Easy to measure data
+ Easy to create adrenaline shocks
Values
Negative aspects
_ Stress
+ Focused on human needs
+ Humanity
Security
Positive aspects
+ Safety
Effective use of resources
Possible to speed up time
Solves the lack of empathy in society
Creates knowledge about forests
Experience/event
_ Hard to interpret data
_ Not any obviously emergent
interaction in the application
_ Integrity
_ Privacy issues
Public Space Events
Even if we spend most of our time in quite closed communities like families and
work teams, there is still time left for other activities. Some of them are things
we need to do, such as shopping, waiting for a bus, etc. Other activities are for
pleasure, such as visiting pubs, restaurants, exhibitions, etc. There are questions
of rationality and effectiveness in both types of public events such as to find out
where to go to find the cheapest, most attractive products or services as effectively
as possible. On the other hand there are also questions concerning communication, meetings, and beliefs: e.g. what is hot in an area? are there any people with
similar interest as me here? etc. Applications in this category are aimed to support this kind of public space activities. Some examples are exhibitions, atmosphere
detection, pubs, restaurants etc, silent areas and parties.
Table 4. Aspects of Professional
Applications.
Application Areas
Effects
Implementation
_ Drunk people might ruin the equipment
(puke warning)
_ PDA is needed
_ Willingness to carry the sensors
_ Too fast
+ Effective use of resources
+ Spread load
+ Better price
+ Faster
+ Winning time
+ Quality effects
+ Environmental
+ Experience/Event
+ Opportunity to make new acquaintances
+
+
+
+
+
Values
Negative aspects
_
_
_
_
_
_
_
+ Humanity
Security
Table 5. Aspects of Public Space
Applications.
Positive aspects
+ Safety
Great diversity of people
Individualised
Common intentional
Not common intention
Neutral (nobody owns the territory)
_
_
_
_
_
_
27
Dangerous to lose the control of the system
Unwanted effects
Less development and considerations
No spontaneity
Segregation
Standardisation
Stress
Boring application
Destroys the event
Competition problems
Whom does it benefit?
Wrong target group
Small target group
_ Integrity
_ Privacy
_ Unclear who should have the control
Negative aspects
Effects
+
+
+
+
Democracy
Organisation
Less violence
Control the situation
_
_
_
_
_
_
Implementation
+
+
+
+
Easy to measure
Everybody
Right equipment
Surveillance
+ Economy
Security
Table 6. Aspects of Political Applications.
Positive aspects
Values
Political Events
Politics or the political process in a democracy is given as one example of an existing EIS. Politicians, political parties, media, public opinion survey makers, and
citizens are all actors in the system. A fundamental requirement is that all individuals have equal rights to communicate their opinion, within a given framework
of rules. Another requirement is that there is an apparatus to control that every
one is following the rules. The applications in this category are aimed to support
the democratic process, both communication activities and the control apparatus.
Some examples are demonstrations, IT-democracy, avoid/track crime activities, and
war.
Does it work, is the result a better democracy ?
Crowds
More violence
Escalation
Injustice
Mobbing
_ No surprises
_ Security problems
28
Application Areas
Communication Events
It seems that we human beings have a basic instinct to communicate with each
other, in a broad sense (Aronson, 1995; Asplund, 1987). There are many techniques that serve to extend our possibility to communicate. Most of these technical artefacts are designed to shorten or bridge different types of communication
distances, and some may be intended to completely eliminate distance. Communication distance is more than kilometres (Broberg, 2001). distinguishes four
kinds of distances in learning situations: time, space, way of learning, and distance
to relevant material. This can be extended and generalised to communication in
general, taking also cultural, sociological, and linguistic distances into account.
The applications in this category are aimed to support shortening and bridging of
distances. Some examples are car-pooling, tourism/guiding, implicit traffic control,
and extended video/phone-conferencing.
_
_
_
_
Effects
Huge population
No one can escape
Nothing else happening
Repeatable
Implementation
Effective use of resources
…of advantage to society
Democracy
Distance spanning
Economy
Environmental
Possible to compare groups in similar situation
Commitment
+
+
+
+
+
+
+
+
+
+
+
+
Values
Negative aspects
_ Interference
_ Stress
+ Easy to find money for
+ Humanity
_ Not something that is new
_ Boring, grey
Security
Positive aspects
+ Safety
_ People want to be alone
_ Security
Demands on capacity
Not in Umeå
Computational problems
Too big
Arena Events
Humans are social animals (Aronson, 1995). Our basic instinct to do things
together is manifested in small, intimate groups such as a family, as well as in large
gatherings in venues such as theatres and sport arenas. Many activities in large
arenas have to do with entertainment in some form, but there are exceptions from
that, e.g. political rallies. The applications in this category are meant to extend
and enhance arena events as we now know them, for example making the audience more active or participating, or widening the arena into the virtual world.
Some examples of applications are theatre, track and field, docu-soap like Survivor,
and collaborative art.
Table 7. Aspects of Communication
Applications.
Negative aspects
Effects
+ Can create more interaction
+ The public (as paying) is allowed to decide
more
+ Easy to please
+ Enhances experience
+ Experience/event
+ It would help the drivers, the teams at the pit
stops
+ Fewer extra tracks
+ Less tomatoes thrown
_
_
_
_
_
_
Demands that you engage in the play
Dependent of the audience
Huge demands on the actors
Does it have any positive effect?
No new songs
We don't want to choose
Implementation
+
+
+
+
+
+
_
_
_
_
_
Few events
Once a year event
Very few events
How to charge?
Loads of technique
+ Collaboration with (Strix)
+ Commercial interests
+ Enormous market
+ Maybe a growing area
+ Money
+ Fun
+ Hot
+ Humanity
+ Tokyo as a lab (NTT DoCoMo)
+ Playfulness
_
_
_
_
_
_
_
_
Difficult to understand the market
Who profits?
What is new?
Does it already exist?
Just a game
Expensive prototype
Expensive system
Difficult industry ( TV )
Already based on interaction
Many existing concepts to expand
Closed area/local
Easy to find test pilots
Everyone is a participant, 24-7
Brainstorm with children/youths
29
_ Security
Security
Table 8. Aspects of Arena Applications.
Positive aspects
Values
Application Areas
Negative aspects
Effects
+ The group could later on be used to:
send out information
requests
reminders
+ Groups could be created (?) recreated or
consolidated afterwards from logged data
(who was there and personal profiles) when a
need is identified
_ Uniform
Implementation
Table 9. Aspects of Community
Applications.
Positive aspects
+ Individualised
+ Scalable
_
_
_
_
Values
Community Events
The society consists of communities (subgroups or subcultures), that is, people
with something in common that brings them together. That something (hockey
team, a hobby, political ideas, the work, etc) is in focus for their various activities, such as meetings, exchange of advice, communication, giving support to a
team, etc. Such lists of community activities can be very long. The applications in
this category are aimed to support activities intended to increase the engagement,
attendance, kinship and similar qualities. Some examples are hunting, instant communities, gardening and pets, and social life, create new contacts.
+ New
+ Cool
+ Business and pleasure
+ Young market
Where to find the people
Critical mass
Hard to get started
What terminals to use?
_ What do they have in common?
30
Application Areas
General aspects of Emergent Interaction Applications
Why should we develop EI applications? There is an unspoken need for something to show to the world*. On the other hand there is a need for a good platform
for testing important concepts. At first glance, this may seem to imply a balance
act between the “just a game” application and the “boring” application. There is
also a balance act between innovative thinking to enhance existing events or create
a new type of event, and the risk of destroying (the existing values of ) an existing
event or previously existing related events.
The above walkthrough lists positive and negative aspects for each of the nine
categories of EI applications. More general aspects have also been discussed during
the project. The purpose with this part is to compile all discussions on aspects
into a more general tentative assessment of EISs. One result from this work is a
list of prototype requirements, designed to guide the choice of prototype in the
next phase. These prototype requirements are presented and discussed in the last
section in this report, Pre-study Outcome.
The general discussion has identified one important purpose with the concept: to increase or enhance social life with participation and engagement in some
sense, and to provide new ways of forming acquaintances. To build prototype systems of this kind based on emergent interaction creates an attraction and makes
the concept more concrete and visible; of course, there is also a general feeling that
EI applications are cool and trendy.
The realisation that there may be some sinister similarities between EI applications and the scenario of George Orwell’s 1984 puts the finger on the main weaknesses of the EI concept - the secrecy issues, the integrity issues, and the risk for
breeding and amplifying negative tendencies in society. The general discussion has
also identified a number of other worries. First, there is a fear that EI will contribute to a more uniform society, i.e. a situation characterised by flock behaviours,
lack of individuality and personal initiative. Second, it seems to be complicated
to implement EIS technically; e.g. many of the ideas seem to assume wireless communication techniques, there are many completely new and untried ideas for the
compile and compute stage, as well as a heavy reliance on new technology in general. Third, the complexity of the systems is quite high, escalating the risk of operational disturbances. Fourth, there are worries about the level of radiation with
radio-based wireless communication techniques and sensors everywhere. Fifth,
and finally, we do not want boring applications for nerds only; on the other hand,
we do not want to launch a prototype implementation project that does not give
a serious impression in the eyes of the public. The rest of this subsection is an
attempt to compile the directed discussion to a general level. The aspects related
to each of the categories confirm the general feelings about EI. In addition these
category-directed aspects extend the positive feelings of the concept.
Discussions About the Effect Issues
The effect point of view raises concerns about the effect that emergent interaction application can have on individuals but also on the collective. First, many of
the proposed applications are aimed to utilise resources in a more effective way,
e.g. saving time, better prices, spread the load, etc. Second, another category of
applications is aimed to more qualitative effects both on the personal level and on
society level. For example, put a stop to harassment, preserve and improve health,
create a better understanding for a phenomenon, positive effects on the environment, etc. Third, emergent interaction has the potential to enhance an event or
experience of a phenomenon. For example making the class room more appealing, distance spanning, increase the social interaction, etc. Fourth, there is a group
of ideas serving to strengthen the democracy process. For example, the citizens
may have new ways of affecting the democratic process by just acting; have or take
control over violent situations implying less violence; etc. All these things must be
classified as positive effects.
* This is true for all research and
development projects, this is true
also for a R&D project on emergent interaction. Basically, this may
be important for future funding of
the research and development, but
also in order to commercialise the
concept.
Application Areas
31
On the other hand, for many applications, some unwanted effects can be identified as critical; losing the control over the situation (resulting in an escalation
of negative effects such as violence, mobbing, stress, chaos), system breakdown,
spreading effects beyond the scope of the system, etc. Another cluster of negative
issues can be summarised as a general scepticism about workability: whether it
really will work, whether it will have any positive effects at all, whether it will be
worth the trouble. Finally, many of the proposed applications put new demands
on the actors in the system such as more engagement, having to handle new situations, coping with more interference from the environment.
Discussions About the Implementation Issue
The implementation point of view raises concerns about how easy it is to get
started and what kind of activity should be in focus for the application. In that
sense the implementation aspects are typically directed towards the adequacy of
the particular idea as a prototype. Hence, these aspects are useful for setting up
requirements for prototype implementations, (see the discussion in last section
about prototype requirements, page 65). In the longer perspective these implementations issues are a good tools for judging the adequacy of implementing ideas
to full-scale applications.
The kind of event plays an important role for the difficulty, effort and adequacy of implementing an application. Applications focusing on emergence and
social phenomena like knowledge and democracy, i.e. applications with a focus
on human needs or the good for the society may be more relevant to implement
than a “just for fun” application. There is a hard balance act between these two
aspects, especially when concerning the positive aspects of the market values, such
as the potential to find a financial partner to collaborate with. For example, an
enormous market or a young market with a potential to grow will increase the
financial potential. Hence, applications associated with that kind of values are
rewarding to develop. On the other hand, there are other values not immediately
related to the economy that are important to have in mind in the balance act
between utility and attraction value. For example, is the event already “IT-polluted” or not? Does the application combine business and pleasure? Would an
implementation bring something special?
For a good implementation project, the application must not be too narrow,
and it must not be too wide. A too narrow activity means that it will be hard to
reach the critical mass for the application: the necessary facilities may not exist in
the near surroundings; it can be hard to find enough people willing to carry sensors and other necessary equipment. The continuity or frequency of the event is
also important for the possibility to run an implementation project.
The character of the room (room in a quite broad sense, including both spatial
and social aspects) of the event also plays an important role for the implementation. It is easier to implement a system if the activity takes place in a closed room
than in an open public space. On the other hand the ownership of the room also
affects of the possibilities to implement a system. A closed room often has a clear
ownership that can make it easier to get money for the project but may constrain
the application. A public space with a weaker ownership can give more freedom in
the choice of application, but can make financing a more intricate task. A closed
room makes it possible to involve all actors in the room, and is hard to escape
from (in a positive sense). Of course there are lots of activities not related to a
particular closed room, in which “everybody” or very many are involved, e.g. every
day chores in the home, shopping, etc. The closeness also implies that nothing else
important is happening in the room.
A proper feedback mechanism is crucial for every EIS. The relative difficulty
and effort of implementing the feedback loop (including the data collection, compiling and computing, and presenting the data), technically as well as socially,
must be considered during the early phases of the design of applications. There
are more concerns about the feedback mechanism. First, a high acceptance for
32
Application Areas
data collection among the participants is an important factor. Second, the measure
issue: it could be hard to identify what to measure, and it may be hard to do the
actual measuring of important parameters of the activity. Third, even if we can get
data from the activity it can be hard to give it a relevant interpretation. Fourth,
to design the feedback is not a trivial issue - exactly what the feedback should be
is in many applications an open question. It seems that many of these feedback
loop requirements are more easily satisfied for a closed room activity than for a
public space activity. Fifth, in many systems, there is one person or a small group
of individuals having the compute and compile function, and it may be undesirable to replace humans with a computerised functionality.
Most of the proposed applications are quite complex systems with heavy
demands on technique, and many of the proposals are in public spaces or quite
open spaces - thus raising questions of how to protect the equipment from being
stolen, destroyed, etc. Considering the complexity of EISs we may have worries
about the implementation costs. In the long run it is necessary to take market
aspects into consideration: whom does it benefit, who profits, how to charge,
competition problems, etc. Another question related to the cost aspects that needs
to be considered is what terminals or technologies to use.
There are many interesting concepts and research issues related to emergent
interaction, e.g. social navigation issues, scalability issues, new technical solutions,
etc. The adequacy of the application increases with its potential to expand and
study EI-related concepts. This is also true in particular for ideas that are associated with a purpose to cause new behaviours or phenomena.
Handling the negative aspects
EI systems are very complex systems. The idea of designing computerised EI systems where the interaction between the individual and the collective is in focus
is quite new. Together, these two facts imply a high risk of running into problems with a prototype implementation, especially without a proper understanding
of the potentially negative aspects of the application. The hazards, dangers and
potentially negative effects are important to keep in view, to investigate and negotiate - not only for any particular implementation - but also and more importantly
for long-term basic research on the operation conditions and behaviour of EI systems, giving the basis for more predictable and safer applications. The purpose
with this part is to summarise our discussion about how to address these misgivings and negative expectations about emergent interaction.
The potentially high cost for implementing and introducing an EI system is a
negative factor. We have considered what might be done to keep down costs. One
way is to start with a small-scale or stripped-down implementation using already
proven techniques. This would also give a smooth start on the project. E.g. it
might be possible to skip the mobility issues in the early stages of an implementation project. Another way to cut costs is to engage master thesis students in the
project. This will have a dual effect: it is also important to introduce the EI ideas
to the system developers of tomorrow.
Except for the worries about the costs and technical problems to set up EISs,
the worries about security, integrity, and privacy issues draw much attention people want to maintain some level of privacy, they are afraid of being logged,
and they worry about the data being transmitted in a secure way. There are general concerns about losing the control over the system. There are concerns specifically related to authorisation. Per definition we would not want an unauthorised
person to take control over the system, but we can imagine situations where it
would be unclear who would or should have control authority.
The “Big Brother scenario” for emergent interaction represents the most negative beliefs about the concept and the project that we have been able to imagine.
We have worked a lot to find ways of alleviating our own concerns and misgivings (and thus preparing ourselves for the job of convincing others that there is
Application Areas
* As so many other problems with
EI systems.
33
no real problem). The difficulties of solving problems with unauthorised control
of the system can be illustrated with the fact that some of the methods we have
discussed to solve the authorisation problem definitely contributes to the “1984
feeling”, e.g. censoring, filtering of data, tracing authorisation procedures, etc. It is
important emphasise that there is nothing of the original intention with emergent
interaction systems in this “Big Brother scenario”, which is a scenario that implies
a centralised control apparatus for regimentation of the masses. Emergent interaction stands for the opposite of this scenario, i.e. individual thinking and initiatives
taken from the considerations of the shared feedback.
On the other hand, these worries for a “Big Brother scenario” indicate a real
risk for EI systems, i.e. the misuse of the basic technique, which is important to
have in mind for the further development of the concept. Therefore, the need
for good examples to show is very important, especially to clarify the intentions
and to remove the cause for these worries. Engagement, together with ethics and
moral must also be seen as key issues for preventing unauthorised control and
misuse of the basic techniques for EI systems. Moreover, to inform all the participants of the value of being in the system, and to be absolutely frank and forthcoming as to how it works is part of this work to establish trust for the application and
the concept.
In summary, the main problem, we now believe, has much the character of
an information problem*. It is always important to analyse and identify what the
wanted effects are, and what unwanted effects could arise. This is important for
all kinds of actors in the system. Therefore, it is necessary to develop methods
for risk and consequence analysis for implementation of EIS and applications.
Such method, must take care of what happens if the system goes down, is it a risk
that an application can cause panic in some situations, is it risk for misuse of the
system, etc. We believe that simulations can be or must be a part of this method.
To verify, test, and develop the model are other open issues related to the model.
34
Technical System Aspects
6. Technical System Aspects
In this section system architecture, data communication, and traffic
patterns are discussed from an EI perspective. Each system will have
its own communication solution and one way to understand this is
to analyse the EIS from a System Architecture view. System Architecture describes how a system is designed and constructed. The Data
Communication in the EIS is another important area for discussion.
We can identify several places in the EIS where there is a need to
exchange data between nodes in the system.
If we analyse the logical EI model we find that all arrows in the
model represent data exchange, i.e. Data Communication. Nevertheless, not all EISs have the same needs and demands for Data Communications
and therefore a wide range of communication technologies and solutions will be
discussed in this chapter. Last, but not least, the data traffic generated by an EIS
can be analysed to identify patterns, i.e. Traffic Patterns. A study of such patterns
can give information about how a system works and how users interact with the
system.
System Architecture
The purpose with this section is to give an introduction to the concept of system
architecture and then discuss architectural aspects for EISs. System architecture is
about identifying which components, logical and physical, a system can be constructed of. The roles of each component need to be specified, such as the interfaces, links and protocols used to communicate with other components. Issues
such as scalability, centralised or distributed architecture, dedicated or public systems, etc., needs to be investigated. Different architectures can be designed for
different purposes, situations, and variants of EI systems.
There is no common definition of system architecture but in (Luckham, Vera
& Meldal, 1995) the following simple definition can be found: “An architecture
is a specification of the components of a system and the communication between
them.” This definition is used in this section with the following additions:
•
System Architecture is a high-level structure of a system.
•
It is a level of abstraction from which the system can be viewed as a whole.
•
All implementation details are hidden.
•
The structure must support both functional and non-functional requirements of the system.
There are a number of factors one should have in mind when discussing the
architecture for a system. Functionality, the architecture must support the required
functionality, i.e. what is the purpose of the designed system? Performance, it must
give the system ability to meet the performance needs. Environmental, in which
environment will the systems operate? Does the architecture support the implementation of the system for different environments and contexts? Some environments are more hostile or demanding than others. Different parts of the system
are operating under different conditions. The same system may need to be able
to operate under different temperature, moist, load, and current conditions, etc.,
depending on where they are deployed. Usability, how will the users interact with
the system? Do we have the support we need to implement a system with appropriate usability? Reliability, the system must be stable enough and able to operate
under high workload for a sufficiently long time. Future Proof, the architecture
could be prepared for future upgrades of the system. Production, if the system is
Technical System Aspects
35
to be a product it must be possible to produce and install it at reasonable costs.
Budget, the system must be possible to implement within the available budget,
time and economical resources. Who will implement the system? Maintainability, the system should be possible to maintain and administrate. This should be
reflected in the System Architecture. Scalability, if the system is to be scalable this
must be an issue to have in mind when designing the architecture. Understandability, it must be possible to understand how the system operates by viewing the
System Architecture. The Architecture can be used when demonstrating scenarios
for how the system will perform. It can also be a tool when analysing malfunction
in the system. Available Technology, should the system be implemented using only
available technology or can we wait for future solutions or do we need to develop
something new? What technology is available today? (Nilsson, 2001).
Note that the System Architecture should be specified early. This will help to
divide the system into logical and physical parts and make it possible to analyse
how to implement each sub-system. It should also make it easier to decide if it is
possible to implement the system or not and if the system can fulfil the requirements.
We can have different levels of architectures depending on what we want to
specify or analyse. An important requirement of System Architecture is that it
takes an overall view of the system. Different levels of abstraction give different
types of architecture. We can also analyse software architecture, network architecture, computer architecture etc. Some part of the system could be more advanced
and complex than others and should therefore be analysed further by creating
some kind of sub-system Architecture. This is the reason why very large systems
have many levels of architectural descriptions.
There exist tools and concepts for the design of System Architectures. In
(Luckham et al., 1995) three different concepts of System Architecture are presented: First, object connection architecture, second, interface connection architecture, and third, plug and socket architecture. Of these three the plug and socket
architecture is the most interesting for EI systems. Useful tools when designing a
system are Design Patterns (Gamma, Helm, Johnson, & Vlissides, 1995) and Anti
Patterns (Brown, Malveau, McCormick, Mowbray, & W.Thomas, 1999). Design
Patterns are known, proven solutions for common design problems, which can be
used as templates when designing systems. Anti Patterns is the opposite: examples
of common, bad solutions which one should avoid to use and also examples of
how to avoid them. Both Design Patterns and Anti Patterns supply a common
vocabulary and terminology, which makes it easier to describe and discuss the
architecture of the system.
System Architecture for Emergent Interaction Systems
What architectures would be suitable for EI systems? According to the EI model
an EIS seems to have a distributed System Architecture. Different types of units
and interfaces can easily be identified in the model. Units: PID, CCU, Control
unit, etc. Interfaces: PID – CCU, CCU – PID, Control – CCU, shared-phenomenon – CCU, CCU – shared-phenomenon, EIS – EIS, etc. Note that most of the
terminology used in this section was defined in the section Emergent Interaction
Systems, sub-section System Architecture Issues.
These components and interfaces are all on the same level of abstraction in the
EI model. If the resolution is increased we can se more components and more
interfaces, e.g. in the PID the Sensors-PID interfaces and different units, which
handles different interfaces. It’s all about resolution and level of abstraction. What
level of abstraction is the right one? It depends on the purpose of the architecture.
If the purpose is to show an overview of an EIS, a level that doesn’t show too many
details in each unit is needed. If the purpose instead is to guide the design of the
PID or the CCU the architecture must show these units in more detail.
36
Technical System Aspects
In this pre-study we don’t need to go into details but if a system is to be implemented the Architecture should be carefully designed and analysed as early as possible to ensure that the system is possible to implement. It is also important to
verify that the architecture fulfils the requirements, and enables estimation of the
work needed for the implementation.
There are many ways to describe the difference between two system architectures. For an EIS it is possible to identify many architectural characteristics that
are important for the system’s possibilities and limitations. These are some examples of such characteristics:
•
Homogenous systems, all PIDs are of the same type or they have the same
capacity and functionality. Only one communication interface is used by
the PIDs in the system.
•
Heterogeneous systems, the system supports different types of PIDs with different capacity and functionality. More than one communication interface
can be used by PIDs in the system.
•
Centralised systems, the system is (functionally) centralised around a central
CCU, which controls the activities in the system.
•
Decentralised systems (partially or totally), the CCU is distributed in the
system. More than one node has the CCU functionality. Those distributed
CCUs can be standalone units or be included in some other system unit,
such as a PID.
What are the maximum numbers of actors for different architectures? The number
of actors a system is required to support is an important factor in the design of
the system architecture. Different requirements on the available capacity per actor
lead to different solutions. If the system is supposed to support a small number
of actors the communication to and from each actor can be allowed to use a large
part of the available network capacity. On the other hand, if the system must be
able to support a large number of actors each actor can only use a small fraction
of the available network capacity.
Example of Emergent Interaction System Architectures
In this section some examples of different architectures of interest for EIS design
are shown. The architectures shown are extreme solutions selected to illustrate the
possible variation of EIS architectures. In the design of a real EIS more effort must
be laid upon defining a suitable architecture that fulfils the requirements for the
actual application. The range of architectural variation is illustrated in Figure 10,
where the examples span the axes in a two-dimensional space where EIS architectures can be defined. Size
Time
Large
Small
Figure 10. Illustration of the variety
of possible EIS architectures.
Centralised
Decentralised
Level of
centralisation
Technical System Aspects
37
Centralised Architecture
In this architecture all PIDs send their data to a central CCU. The CCU distributes the feedback as a broadcast or multicast message to all PIDs and displays.
This is a much more effective way of communication than if the CCU would
have to communicate with all the PIDs one-to-one (unicast). The communication needed for the feedback using unicast would be proportional to the number
of units, whereas it only depends on the data quantity if multicast/broadcast is
used.
The data collection from the PIDs to the CCU is one-to-one (unicast) and
will therefore be proportional to the number of units in the system. An interesting issue is whether the amount of communication needed for the data collection
could be reduced. Assuming that the data sent from the units to the CCU is of
a kind where the CCU is not interested in duplicated data. In such a system the
PIDs could send their data to the CCU on a broadcast or multicast channel so
that all other PIDs can receive the data. Each PID that receives data identical with
its own now doesn’t need to send it to the PID. An EIS build upon a centralised
architecture is shown in Figure 11.
Examples of positive and negative aspects of the architecture from an EI perspective
+ The architecture corresponds well with the EI model.
+ Easy to understand.
-
Well known architecture, and therefor not a very interesting architecture
to study.
-
The data collection needs a lot of network capacity per PID, which leads to
scalability problems.
Presentation
unit
Compile
and
Compute
Fugure 11. EIS with centralised
architechture.
Application
Ad-Hoc (Decentralised) Architecture
This is a decentralised architecture for an EIS where all data sources (such as PIDs,
sensors, etc.) broadcast their data and each PID receives data from all sources
(within range). Each PID includes a CCU to process all data, received and the
PID’s own. Other units than PIDs, such as the displays could also have their own
CCU to process data received from the PID. Such units could also be connected
38
Technical System Aspects
to other systems to exchange data and/or compiled results. If so, also data and
results from other EISs or subsystems could be sent out to the PIDs so that their
CCUs can use that information in their data processing.
This architecture reduces the communication interfaces in the EIS so that the
only wireless communication needed is a broadcast interface. Then it is up to all
units with a CCU to receive all data and compile a result. If all units receive the
same data and use the same algorithm they will produce the same result. Because
of the limited range of the wireless broadcast, however, it is possible that not all
units receive the same data and they will therefore compile different results. It is
also possible to allow that the CCUs use different algorithms to compile different
result even with the same data. An EIS build upon a centralised architecture is
shown in Figure 12..
Examples of positive and negative aspects of the architecture from an EI perspective
+ Generally easy to implement. In the simplest case only one node has to be
specified, the PID.
+ The communication is also simple, only one broadcast interface needs to
be implemented.
+ Ad-Hoc, no infrastructure needed.
+ Easy to expand with infrastructure support for communication.
+ A new market is created for EI units.
-
Hard to control and administrate the system
-
Capacity for a CCU needed in the PID. To solve this problem a number of
powerful PIDs could have CCUs and broadcast their result to PIDs lacking
a CCU.
-
Scalability: How should the communication be implemented to avoid
capacity problems in large systems? Another problem is whether the PIDs
have capacity enough to handle all data received in a large system.
Intelligent
display
Compile
and
Compute
Actor outside
the application
range
Shared
phenomenon
Actor inside
the application
range
Figure 12. EIS with ad-hoc architecture.
Application
Application
server
Technical System Aspects
39
Minimal System Architecture
The CCU and the wireless communication infrastructure needed (if any) are all
implemented in a laptop PC. This gives a portable or even mobile system which
can be used everywhere and is easily installed in new locations. The communication could for example be some kind of WLAN. A system like this can be seen
as minimal in terms of complexity, capacity, costs, needed resources for CCU and
communication, space needed for the installed system, etc. The number of units
the system can support could still be large.
Examples of positive and negative aspects of the architecture from an EI perspective
+ Inexpensive system.
+ Portable and mobile systems.
-
Scalability, hard for a laptop to handle massive computing tasks and for the
WLAN to handle large number of PIDs.
-
Only a limited amount of data can be collected.
Very Large System Architecture
This is an architecture where the CCU functionality is duplicated in a cluster
of servers, which can perform massive computation tasks in (almost) real-time.
The wireless network (one or many access networks) are used to handle large
numbers of PID’s. The CCUs communicate with each other over a high capacity
wired network. Large amounts of data from the PIDs and sensors can be collected.
Complex and bandwidth demanding feedback can be given to the PIDs and the
displays. A system like this can be seen as large in terms of complexity, capacity,
costs, needed resources for CCU and communication, etc. The physical size of the
system (also known as “foot print”) on the other hand could still be small.
Examples of positive and negative aspects of the architecture from an EI perspective
+ High capacity system.
+ Scalability, possible to construct systems with different sizes including very
large systems.
-
Not portable.
-
Expensive to build.
-
Complex to design, implementation, and administrate.
Open Issues
Many issues remain to be resolved for how to design EI system architectures.
What is the maximum performance and capacity for different architectures? What
are the bottlenecks of the systems? What network capacity and response times are
essential for different applications? What amount of data is relevant and realistic
for the feedback and/or the data collection? How and why should ad-hoc EISs be
designed? Should the system be stationary, portable or even mobile? Can we have
virtual systems? These are some examples of interesting issues for further studies
of system architecture for EIS’s.
To summarise, both the ad-hoc architecture and the centralised architecture are
potential architectures for EISs. The major advantages with a centralised architecture are the stability in the basic architectural concepts, and that there is lot of
practical experience reported from building applications with this kind of architecture. The latter advantage points out the major weakness of the ad-hoc solutions: it is a relative new idea of building applications, and not so much practical
40
Technical System Aspects
experience has been reported. On the other hand, many of the basic system architectural concepts and their consequences have to be studied, implying that the
news value in building EI applications on that kind of architecture is much higher.
Clearly, emergent interaction has the potential to open up a new market for EI
Units, such as personal devices/tools, presentation units, etc. An ad-hoc architecture gives better conditions for such a market than CSA architectures do.
Data Communication
How will the different parts in an EI system communicate? Which different technologies, protocols and equipment can be used? Today there are many solutions
for wireless communication available that make it possible to build advanced
and flexible EIS. First, the needs must be analysed and then matched against
the available solutions. This section analyses the possible and probable needs for
data communication in an EIS. First, a short introduction to some relevant communication technologies and systems will be given. Hopefully this can provide
a meaning for concepts such as packet data, TCP/IP, Bluetooth, synchronous/
asynchronous communication, delays, throughput, packet loss, bit errors, roaming and mobility, security, multicast, unicast, broadcast, etc., in the EIS context.
What is data communication? For our purposes we can use the following definition: Data communication is when computers exchange data with other computers. The computers can talk directly with each other or communicate via some
communication infrastructure, i.e. a network.
By using this definition it is possible to identify the need for data communication in the EI model. All nodes in the EI model can be seen as computers and all
these computers need to exchange data with other computers in the EIS. Therefore, data communication is an important part of every EIS. Data communication
is needed both for the data collection and the shared feedback. Another observation is that some kind of wireless (i.e. radio) communication could be used to
make it easy for the PIDs to communicate with the rest of the system. Other parts
of the system could either use wireless communication or wired network solutions.
The protocols and interfaces used should be standardised in order to make
it easier to replace one node with another, i.e. one sensor should be possible to
replace with another without redesigning the system. What protocols do we need?
Is TCP/IP the best choice or do we need something, which better handles realtime traffic and Quality of Service* (QoS) in wireless networks. An overview of
QoS in an Internet perspective can be found in (Xiao & Ni, 1999). These questions are candidates for further study in following EI projects.
The wireless communication in the EIS is an important issue to discuss because
many different technologies exist today and it is not obvious which solution to
use. Most likely, different solutions will be interesting for different kind of systems
in different contexts and in systems designed for special purposes. The wired communications solutions will probably be easier to find and the technologies used
should not vary much between different EISs. That is the reason this section is
focusing on wireless data communication.
Wireless Data Communication
There are many different types of wireless data communication and there are different ways to categorise wireless communications. One way to categorise wireless systems is by the purpose of the system. There are broadcast systems such as
those for television and radio broadcast. Other systems are specialised for mobile
telephony, cellular telephony systems such as GSM, TDMA, PDC, CDMA, etc.
There are also wireless data systems, which are specially designed for TCP/IP data
communications networks.
* Quality of Service is a networking term that is used when a network connection can guarantee a
certain bandwidth.
Technical System Aspects
41
Another way to categorise wireless systems is to analyse their range. If we only
discuss the range and coverage of different wireless network technologies we can
organise existing technologies into several categories: Global or national coverage, regional coverage, cellular (medium range) coverage, local area coverage, and
personal area coverage. For each of these categories there are technologies that are
interesting from an EI perspective. Here is a list of some of these technologies
organised into range and coverage categories:
•
Global or national coverage, Digital Video Broadcasting for Satellite broadcast (DVB-S)
•
Regional coverage, digital terrestrial broadcast of television and radio
(DVB-T, DAB, RDS, Paging, etc)
•
Cellular coverage, mobile or cellular telephony with data services (GSM,
GPRS, EDGE, UMTS, CDMA, MobiText, etc)
•
Local area coverage, Wireless Local Area Networks, WLAN (802.11, HiperLan2, etc)
•
Personal area coverage, Personal Area Networks, PAN (Bluetooth, IrDa, etc)
There are many different standards for wireless communications specified by
different standardisation organisations such as ETSI (ETSI, 2002), ITU (ITU,
2002), IETF (IETF, 2002), and IEEE (IEEE, 2002). Sometimes the same standard is defined by more than one organisation. Sometimes there are several different standards for the same purpose. One example of this is the large number of
(2G) standards for cellular telephony. In Europe the GSM system was standardised, Japan developed the PDC system, and North America uses GSM but also the
TDMA and CDMA systems. One task when standardising the next generation
(3G) of cellular telephony system was to define a worldwide standard (Universal
Mobile Telephony System or UMTS). Unfortunately, the outcome was a set of
standards instead of a single standard. In order to design a unit that will work
worldwide, all of these standards must be implemented. These standards are at
least possible to combine in one unit but we have to wait for the next generation
of cellular telephony for the world’s first worldwide standard.
Other standards are accepted worldwide but are for some reason less attractive
in some countries. One such example is the IEEE standard for wireless LAN
(WLAN), 802.11b. The standard is available worldwide but with different
number of channels available in the assigned frequency spectrum. In North America and most of Europe a large set of channels (11-13) are available, but in France,
Spain and Japan only one or a few channels are available. This makes this standard
much more interesting to use in those countries where many channels are available.
There are a few factors to have in mind when discussing wireless data communication in an EIS perspective:
•
Range, how large area can the wireless network cover?
•
Bandwidth, what is the bandwidth capacity in the network?
•
Scalability, how many users can the network manage?
•
Mobility, how does the network support mobility for the users?
•
Security, does the technology have support for security and privacy?
•
Infrastructure, does the technology need infrastructure and if so how
expensive is it to use?
•
Protocols and Services, which protocols, services and network mechanisms
are supported by the network?
•
Interactivity, does the network support interaction between the users and
the system?
•
Standards, are there standardised technologies that fulfil EIS requirements?
•
Quality of Service, is there a need for QoS in the system and if so how should
it be implemented?
42
Technical System Aspects
The answers to the questions above will be different for each wireless network. As
we can see there are many technologies for wireless data communication and it
can be hard to decide which one to select for a system. But do we need to choose
only one? The short answer is no. A solution where more than one access network
is supported by a system, to enable that different access forms is used to interact
with the system, is called Multi Access. (Multi Access is short for Multiple Access
Network. The Access Network is the wireless part of a network that interacts
with the users.) Multi Access makes it easier to support different kinds of units
in a system. Since the different access forms have different characteristics, such
as bandwidth capacity, mobility support etc, the design of a system supporting
Multi Access is a somewhat complex task. Much effort is needed to ensure that
the same services are supported for users independently of the access network currently used.
The Multi Access solution is defined from a user perspective. Multi Access
could also be discussed from a system perspective. In this case we can se different
wireless access networks for different purposes in the system. For example, in an
EIS one network could be used to handle the communication between the PIDs
and the CCU, another network could handle the communication between sensors
and the PID, and a third could handle the communication between the CCU and
the Shared Phenomenon.
Always Best Connected is another concept where the fact that different networks have different coverage and capacity is used to optimise the available
communication capacity for a user. The most common characteristic of wireless
networks is that the maximum bandwidth decreases when the coverage increases.
Therefore it is interesting to use more than one (access) network to be able
to always choose the best connection available. Seamless handover (roaming)
between different access systems has been a hot topic lately, and many organisations now claim to have solved the problem. One example is a system where the
users have access to both WLAN and GPRS (GSM) networks. The bandwidth
capacity of the WLAN is much higher than the capacity of the GPRS network but
the GPRS network has a much better coverage. If the user automatically chooses
the best available network he will choose the WLAN whenever it is available and
use the GPRS network when the WLAN is out of range.
Data Communication in Emergent Interaction Systems
It is possible to identify where in an EI System data communication is needed and
which requirements the communication techniques must satisfy. The following
communication links can be identified in the EI model between:
•
the PIDs and the Compile and Compute Unit (CCU)
•
the shared phenomenon and the CCU
•
the Administration unit and the CCU
•
the EI system and other EI systems
We could also add three links, which are not actually visible in the model:
•
between distributed parts of the CCU
•
between the PIDs and sensors
•
or between other units in the system
Each of these seven links will be discussed below. Note that the communication
between two nodes does not need to use the same link in both directions. There
can be reasons to use different communication links/technologies between two
nodes. The reasons can be capacity, speed, mechanisms, scalability, etc. It is also
Technical System Aspects
43
possible that Multi Access solutions are wanted for one or more links in a system.
All communication in the EIS must be designed to make it possible to give realtime feedback to the users and participants in the shared phenomenon. This sets
high requirements on the data communication solutions. Different systems will
have different purposes and capabilities and therefore the exact demands on the
communication support will be different. Each scenario must be analysed to identify the needs and only then it is time to try to assign different communication
techniques to meet those needs.
Communication between PIDs and CCU
What are the requirements for data transmission between the PIDs and the CCU?
The amount of data to transmit and in which situations and locations, are factors
that will affect the choice of communication. It is very likely that some kind of
wireless (radio) transmission should be used for this link. The solution should be
scaleable to be able to handle a varying number of actors. The amount of data can
vary between different systems and different PIDs. Because of scalability issues the
communication technology used should be an inexpensive, standardised technology with capacity to handle a large number of units. The communication could
go via public or dedicated networks. Some examples of existing communication
systems and techniques that could meet those needs are Carrier Pigeons, Cellular
Phone Systems (GSM, CDMA, UMTS, etc), WLAN, etc.
One way to ensure the scalability of the communication network is to use
multicast or broadcast (one-to-all mechanisms) instead of unicast (one-to-one
mechanisms) when distributing data. A problem with multicast is that it is not
supported by all wireless network technologies. The reason for this is that the
wireless network usually has much more disturbances and data loss in its transmissions. This is usually an unwanted network situation for multicast distributions.
There is research in an area called Reliable Multicast, which is applicable when
distributing multicast messages over wireless links. An introduction to Reliable
Multicast can be found in the IETF Reliable Multicast Transport Charter (Kermode & Vicisano, 2001).
The bandwidth requirements are probably high for the links (especially if unicast is used) and the response times must be short to ensure real-time characteristics of the system.
Communication between Shared Phenomenon and CCU
The communication between the shared phenomenon and the CCU could use
wired or wireless networks, whatever is most suitable for the specific application
and context of the EIS, i.e. depending on what the shared phenomenon is and
what the purpose of the system is. The real-time requirements must also be fulfilled for this link.
Communication between control and CCU
This communication link enables the system to be administrated and controlled.
The demands on security and authentication are high for this link. Availability
must also be ensured so that the system always can be administrated and perhaps
stopped if something is about to go wrong. The bandwidth requirements are
probably not as high as for other links such as between PIDs and CCU. If the
system should be possible to administrate from a wireless client or not has to be
decided for each implemented system.
Communication between EI system and other EI systems (External
Feedback and Data)
For this communication link unicast communication could be used if there are
only one or a few other systems, but if there are a large number of external systems
multicast should be taken into consideration. If a wired link is used the network
conditions are probably good enough for implementation without the use of Reliable Multicast solutions.
44
Technical System Aspects
Communication between distributed parts of the CCU
This communication link exists in system architectures where the CCU functionality is distributed in the system and located in different system nodes, i.e. the
PIDs or in distributed CCUs. This link has a lot of characteristics in common
with the link between PIDs and CCU, but here the distributed computation in
the CCU must also be taken into consideration. In this scenario the distributed
CCU have a lot in common with parallel computers, and therefore suitable solutions could probably be found in that area of computing science.
Communication between PIDs and sensors
This communication link exists to enable the PIDs to collect data from sensors
(which are not located inside the PID). The data is sent from the PIDs to the
CCU. The physical link between the PIDs and the sensors could be wired (a
cable) or wireless (e.g. Bluetooth). Whatever physical link is used the interface
should be some kind of standardised interfaces for communication with sensors.
The reason is that it should be easy to replace one type or brand of sensors with
another without redesigning the interfaces.
Other links between units in the system
There could also be other links between units in the system (unit-to-unit), e.g.
between PIDs. In some architectures there could be a need for other communication links. The characteristics for these links will differ from system to system and
will not be further discussed here.
Protocols and Services
Different networks support different sets of protocols and services and that must
be taken into consideration when selecting a network technology for an EIS. Ethernet networks, for example, support the TCP/IP suite of protocols, which are
used all over the Internet. TCP/IP is not always the best solution over wireless
links so it is possible that some other protocols could be more effective to use.
Cellular networks, such as GSM and UMTS, support other protocols and services such as SMS, EMS, MMS, WTP, and WAP. These are specially developed to
work well in wireless conditions. For some EISs this could be suitable.
Other efforts have been made to adapt the TCP/IP protocol suite to wireless
conditions. One example is the development of MobileIP (Roberts & Patil,
2002), which enables IP clients to move around and have the same accessibility
(e.g. address) wherever they are connected to the network. Another adaptation
to TCP/IP is IPSec (IETF, 2002), which implements better security in Internet
networks, something that is very interesting in easily accessible wireless networks.
Other networks have security built in from the start. One example is the
802.11b WLAN standard and its Wired Equivalent Privacy (WEP). Unfortunately, this is a very weak security standard, which easily can be broken.
There are different networking mechanisms supporting different types of communication. The most commonly used mechanisms are Multicast, Unicast, and
Broadcast. Multicast (one-to-many) allows that the same packet/data can be sent
efficiently to many different destinations. Unicast (one-to-one) sends packets/data
to one designated recipient. Broadcast (one-to-all) sends data to all recipients in a
network. There are also some less known and more specialised mechanisms such
as Anycast and Geocast (Ko & Vaidya, 2000), which can be useful in special situations. Geocast is a mechanism to deliver messages to all hosts within a given
geographical region. In EI the impact multicast and broadcast could have on the
scalability is very interesting to evaluate.
Security
Security in EI is an interesting and important topic to discuss. What requirements
on security, privacy, integrity, and authentication can be identified for EI and
what techniques can be used to satisfy those requirements? Security is a complex
Technical System Aspects
45
topic and there are many different definitions of security and different opinions of
what risks are acceptable. For any particular EIS it is important to define a security policy, which specifies how the security mechanisms shall be implemented in
the system. The hard part is to find a level of security that gives enough protection without making the system too difficult to use. Different applications should
have different security policies that match the risks that can be identified for each
application.
The need for security is higher in wireless systems because it is much easier to
gain access to the physical links in such a system. Security in wireless systems is a
very interesting area to study and there are examples of systems where large effort
has been spent on ensuring appropriate security. One example is the FlyingLinux
project (Escudero, Hedenfalk & Heselius, 2001) at the Royal Institute of Technology in Sweden. This project aims at providing wireless access to the institute’s
computer network for their students and employees at their premises and at the
student apartments near by.
Another example of wireless security is in cellular telephony, for example GSM,
where a SIM (Subscriber Identification Module) card in every mobile telephone is
used to identify a subscriber and storing some vital information needed to securely
communicate over the wireless part of the network.
Different methods exist for implementing security in data communication systems. One commonly used method is encryption, which can be used to encrypt
data so that only the intended receiver understands the message. Another usage of
encryption is for authentication of the participants in a data exchange.
Another interesting issue, which applies to wireless communication, is location
privacy, i.e. keeping a person’s position and location secret (Escudero, Pherson,
Pelletta, Vatn, & Wiatr, 2001).
Information about computer security can be found in The Department of
Defence Trusted Computer System Evaluation Criteria, (DOD-5200.28-STD),
also known as the Orange Book, which is somewhat of a de facto standard for
computer security today
Security in EI systems is a good candidate for further studies in upcoming EI
projects. When designing an EIS it should be a prioritised task to analyse the
needs for security, authentication, authorisation, encryption, etc.
Open Issues
A this stage not many answers have been formulated to the question of how the
units in EISs should communicate. So far, we have identified a set of questions
that need to be answered in the continued work on EI. This section lists some of
these open issues, which needs to be resolved.
Ad-hoc or Infrastructure Network: We can divide communication networks
into those with infrastructure and those without. In Ad-Hoc (or peer-to-peer)
systems all communication takes place directly between the units without passing through other nodes in a supporting network. Infrastructure systems such as
cellular telephony systems are built and maintained by an operator, who delivers
communication capacity and services to the users.
Another difference between systems is if they are public and for general purposes or not. Can everyone use it for free (or for a charge) or is it a private and
dedicated network built for a special purpose and only available for some special
group of users such as a company or an institute?
Here follows an unsorted, incomplete list of communication issues to have in
mind when studying the communication for an EIS application.
46
Technical System Aspects
•
Should the system support Multi Access or not?
•
Should radio signalling use free or licensed radio frequency spectra?
•
What are the requirements on range and coverage for the wireless network?
•
Scalability, how many users should the system be able to handle and how
do we design systems that can handle different number users?
•
What are the systems requirements on security?
•
Should the wireless network support user roaming between different cells
and networks?
•
What type of addressing should be used (IPv4, IPv6, etc)?
•
Can the system be built with existing solutions or must new technologies
be developed?
•
What bandwidth needs and requirements can be identified for the communication links in EI systems?
Traffic Patterns
The data traffic generated by an EIS can be analysed to identify traffic patterns.
Different systems and applications create different categories of patterns. The
composition of the traffic, amount of data, variation and symmetry are examples
of properties that can identify patterns. By observing those patterns it is possible
to analyse how the system really is working and how the users interact with the
system. Categories of patterns can be identified and utilised to create, remove
and/or change the traffic patterns in a system. If different technical solutions are
needed to handle traffic measurements in different kinds of EISs is another issue
to resolve.
Traffic Patterns in EIS
The traffic pattern in an EIS depends on different factors such as the system architecture, number of actors, how active the actors are, how much each actor interacts with the system, the contexts and the data communication networks capacity,
characteristics and limitations, and the applications used. By analysing the traffic
it is possible to find answers to question such as: who are communicating, how
often and by sending how much data, and what are the response times of the
system? Trends, categories, different usage, roles, and bottlenecks could also be
identified. Other aspects to analyse are the dependency between the network traffic and the number of actors in the system, and how the system architecture affects
the patterns. What effects does the data communication capacity and characteristics have on the observed traffic?
An interesting question is whether the traffic in the system can be controlled,
thus altering the traffic pattern. How can some trends be amplified or attenuated?
How do we measure the traffic and which traffic in the system is interesting to
measure? Can the specification of an EIS be analysed to predict how the traffic will
flow in the system? One example of a study of the patterns of network traffic in a
system can be found in (Greenhalgh, Benford, & Craven, 1999), which describes
the following method of analysis:
•
capture the network traffic in the system
•
identify the main types of traffic
•
identify the bandwidth usage for different nodes in the system and compare with their roles and their level of participation
Technical System Aspects
47
This method, although used to analyse the traffic in another type of system, can
be applied to EI systems. If the task is to analyse a real EIS in order to find out how
it is working and how the actors use it, suitable tools for capturing the network
traffic must be found. One example of such a tool for ethernet networks is Ethereal (Etherreal, 2001). How to use another tool, ntop, for traffic measurements is
described in (Deli & Suin, 2000). Another tool that could be used to analyse the
traffic in an EIS is the Multi Router Traffic Grapher (MRTG) . Tools to analyse
the traffic in wireless networks also exist. One example for cellular telephony is the
TEMS product family (TEMS, 2001). Examples of tools to analyse WLAN are
WildPackets AiroPeek (WildPackets, 2002) and Sniffer Wireless (Sniffer, 2002).
Exactly how to analyse the Traffic Patterns of EI systems is a topic for further studies, for example using a prototype EIS.
Another use for traffic patterns is to analyse and verify if Quality of Service
requirements are fulfilled and correctly implemented in the system, or if such
mechanisms are needed or not.
48
Interaction
7. Interaction
Interaction can be analysed with conversation as a model: a cyclic
process in which two or more participants alternately listen, think
and speak. The quality of the interaction depends on the quality
of each of those subtasks (listening, thinking, speaking) (Crawford,
2000). If we apply this definition to the HITI model, the participants are the Humans (actors), the Things and the Information/
Ideas. Of course, the conversation model has its limitations, particularly in the context of EIS: interactions are not limited to turn-taking
but can be continuous and going on in both directions simultaneously; interactions will commonly not be neat two-party direct interchanges, but be asymmetric with regard to input and output, involve
a third party as middle hand, etc.
In the interaction part of an EIS we will focus on the parts that directly involve
the actors. The main issues of this section are how to:
•
collect input to the system
•
feed back the processed information
•
make the actors’ experience of the EI application enjoyable
Input collection from the actors and their surroundings
As primary input to an EIS, different physical parameters can be utilised, such
as temperature, pressure, gas, position, speed, acceleration, light and sound. There
are roughly three categories of input that are applicable in this case. First, sensors
for unobtrusive data input to the EIS. Second, the PID itself can be used for data
input by for example pressing a certain key at the right time, usually requiring
certain awareness on the actor’s part - but note that the actor may be less aware
or even unaware of it as being input to the EIS. Third, video cameras - located
on the actor, in the PID or in the environment - can be used to measure movement in a group, how crowded a place is, in what mood people are, and so on,
without the participants knowing of it. The video image can also be used as input
to an Augmented Reality system (AR), when the visual properties of the shared
phenomenon are registered from the individual actor’s point of view.
Sensor input
When choosing sensors one would have to consider what to measure, size, standards, economy, accuracy or resolution, linearity and time aspects, power consumption, saturation, range or field of view, sample rate and noise filtering. Depending
on the situation of use one may consider putting sensors on the actor’s body or
to have them in the environment. Sensors on the body should be small and not
disturb the actors in their interactions with the real world. Having the sensors in
the environment on the other hand may generally be expected to give less data
and lower resolution, by making it harder to focus on individual actors.
In general, there are two types of sensors: active and passive. Active sensors can
produce, transmit and receive data (e.g. infrared motion detectors), passive sensors can only produce data (e.g. thermistors). Sensors can be divided into types
and the kind of stimulus energy from the environment that these types can convert to electrical signals to the EIS (Barfield & Caudell, 2001).
Interaction
49
•
Mechanical sensors can sense position, acceleration, force, shape, mass and
displacement. Can be used to detect actor’s or object’s position, weight and
movement.
•
Biological sensors can sense heart rate, body temperature, neural activity,
respiration rate, skin resistance, etc. Can be used to detect the actor’s emotional and physical state.
•
Acoustic sensors can sense sound volume, pitch, frequency, phase and
changes. Can be used to detect sound and for interpreting speech.
•
Optical sensors can sense light emission, refraction, light wave frequency,
brightness and luminance. Can be used for computer vision detection, IR
motion/presence detection.
•
Environmental sensors can sense temperature, humidity, carbon dioxide
level, etc. Can be used for monitoring the conditions of the environment
that the actors are in.
PID input
The Personal Interaction Device, PID, is a fundamental vehicle for input in the
EIS. It can be a cellular phone, a PDA or some kind of wearable computer (see
Emergent Interaction Systems, page 17). (It might even be based entirely on remote
sensing equipment, without any material parts carried by the actor, but we will
not explore this alternative in the following.)
The PID can be used as a carrier of several types of input (and output) devices.
The interaction via the PID might not be as hands-free and unobtrusive for the
actor as sensor or video input. Hand-manoeuvred PIDs are mostly suitable when
the actor has one or both hands free to interact with the PID. If true hands-free
is a requirement for the application, other types of input technology should be
considered.
The most obvious type of PID input device consists of some kind of tangible
components that the actor manipulates mechanically. When designing physical
interaction artefacts it is important to incorporate some kind of affordance
(Norman, 1990) – perceived properties that help the user determine how it possibly can be used. This kind of physical input devices can be divided into two
groups:
•
Tactile devices. Designated buttons, compact keyboards, scroll wheels or
track balls are some examples. These devices give the user instant feedback
via the mechanism inside the product.
•
Touch-only devices. Touch pad, touch screen and data gloves are some
examples of this kind of apparatus. If this kind of input device is selected, it
is important to give the actor instant feedback when data has been put in:
for example a clicking sound, a blinking light or alternated graphics.
Video input
Video input can give a lot of information to the system about the actors and
the shared phenomenon to the system. This information can be processed and
interpreted in a broad range of ways. This creates a great degree of freedom when
designing the application, but it will also restrict the system due to its demands
for high bandwidth and extensive computational power. We can divide the video
inputs into two groups:
•
Sensory video, which is video used for detection, monitoring and recognition only. The images themselves are not presented to the actors. The video
can be registering other kinds of input than light; it can register chemical
emissions and heat radiation and so on.
•
Display video is used for real time presentation for the actor of the real
environment, often with superimposed 2-D or 3-D virtual objects (called
Augmented Reality, AR). Unlike Virtual Reality ( VR), AR supplements reality,
rather than completely replacing it.
50
Interaction
Feeding back processed information
Feedback is essential; without it there is no dynamics in the system. The content
of the feedback is closely connected to what the goal of the EIS is. In this section
we are concerned with the form of the feedback: what forms of feedback are possible and what forms of feedback will be able to effectively reach the actors, eventually affecting their behaviour? Considering that all the usual five senses of human
beings - vision, hearing, sensing, tasting and smelling - can be engaged in the
feedback, singly or in any combination, and that many senses allow for several
dimensions, complex feature detection, learned abilities, and more - the design
space for the feedback is truly enormous. Many other questions arise in designing the form of the feedback for a particular EIS. Should all actors be aware that
there is a feedback? What the form of the feedback is? What the content of the
feedback is? Should the feedback (normally) be conscious or unconscious? Close
to the actors or in the background? Should the feedback be direct or indirect? If
everyone is to be exposed to more or less the same feedback, we might for instance
consider using:
•
Big displays- can everybody see it? Will people care to look at it?
•
Loudspeakers - you cannot close your ears as easily as your eyes (but closing
your eyes usually makes you more helpless than holding your ears).
•
Changing the temperature - blow cold (or warm) air at the group.
•
Vibrations in the floor (ground)
•
Air/gas, could smell be used as feedback?
If on the other hand we decide to deliver the feedback individually we might do it
via the PID. The technical problem here is to distribute the same (or an individually differentiated) signal, to a lot of PIDs. Traffic problems and communication
problems have to be solved. Examples of output devices that might be used:
•
Small, individual displays - but who will look at their PID instead of watching
the big event?
•
Tactile feedback, by using systems like Braille pads or dynamic materials
whose surface structure can be digitally controlled.
•
Earphones, ranging from small ear plugs to headphones
•
Force feedback, haptic and physical feedback, which could also be delivered
via physical things in the environment, such as tools, chairs, etc.
•
Augmented Reality displays, like optical see-through Head Mounted Display,
HMD, or video see-through HMD (see Figure 13).
Video of
real world
Scene
generator
Head
position
Position tracker
Figure 13. Basic principles of HMD
AR systems. Left: optical seethrough system, Right: video seethrough system - adapted from
Barfield and Caudell. (Barfield &
Caudell, 2001).
Position tracker
Head
position
Graphic
images
Video camera(s)
Real world
phenomenon
Scene
generator
Monitor(s)
Real world
phenomenon
Monitor(s)
Graphic
images
Optical combiner(s)
Video
compositor
Combined
video
Interaction
51
Augmented Reality HMDs still has their technical drawbacks. That might discourage us from using it for actors in a real-world context (Barfield & Caudell,
2001):
•
Size, the present systems are very bulky and awkward to use. Neither the
size of the hardware nor the connections (cable or wireless) has been
developed very much. They are custom made or commercialised prototypes.
•
Complexity, especially video see-through systems are structurally complex
and hard to maintain in operable condition, in other words vulnerable.
•
Safety, the video see-through HMD makes the actor effectively “blind” in
case of power cut-off. In that case the actor should not be driving a vehicle,
or be engaged in any kind of critical activity requiring vision.
•
Resolution, the present micro displays on the market can produce images
in the range of 640x480 to 1024x768 pixels. This resolution is far less than
the resolving power of the human fovea (the high-resolution spot of the
retina). This is most apparent in optical see-through AR systems, where
a computer-generated digital image is superimposed on the real world
image. The computer image is jagged while the real world looks as usual,
smooth and - well - real.
•
System delay, even with state-of-the-art technology there will be a delay.
Video streams have inherent delays in the tens of milliseconds. The monitor
also needs time to update an image; a monitor that completely refreshes
the screen at 60Hz has a frame time of 16.67 ms.
Adjusting the output to the actor’s abilities
In the design of interaction using a PID appliance, one should consider all human
modalities, and let the actor interact with the system both consciously and unconsciously. In some cases the actor’s feelings and affects might be of interest (Picard,
1997). Our knowledge of the world is initially sensational; stimulus over a certain
intensity level activates sensory receptors; vision, hearing, tactility, olfactory and
taste are our senses that can receive the system output. In practical terms vision
and hearing are preferred when dealing with large quantities of information being
transferred over a shorter time period; see the table below:
Table 10. The human peripheral
sensory capacity as approximate
values. Note that these figures
describe the information load
before conscious information
processing. Since our consciousness’ computational capacity is
about 7 (±2) bits per second,
an autonomous filtering process
(Zimmerman, 1989) reduces most
of the sensory information.
* Coldness, heat, pain, touch etc.
#
Smell
Sense:
Sensory bandwidth factor:
(bits/second)
Vision
Tactile*
Olfaction #
Hearing
Taste
10 000 K
1 000 K
100 K
100 K
1K
By combining two or more of these cognitive input channels it may be possible
get through more information per second to the actor. In the case of EIS we must
consider how fast we want our system to be. If we have a slow system, there might
be a waste of bandwidth to use a fast channel to transfer the information and vice
versa. In this early stage of EIS theory there are no rules or guidelines to follow,
except to say that it depends on the context of use.
Visualising the information
When visual feedback is used, the best way to visualise the information is highly
application dependent. Still, there are some useful guidelines (regrettably not
completely consistent with each other) on the general principle of form following
content.
Norman (Norman, 1991), argues for the importance of minimising the cognitive gap between a representation and what it represents in order to get a natural
interaction with artefacts. For example, distinguishing between additive and substitutive dimensions (see Figure 12), it is important that additive dimensions are
represented by some additive representation, substitutive dimensions by some
52
Interaction
substitutive representation. A mix-up is very frustrating for the user, causing
unnecessary cognitive load.
•
If the information is quantitative, one should use delicate combinations of
points, lines, a coordinate system, numbers, symbols, words, shadings and
colour ( Tufte, 1983).
•
If the information regards maps, colouring, layering and symbols will be
utilised ( Tufte, 1990).
•
If the information is in a substitutive dimension, e.g. different groups of
individuals, use a substitutive representation.
•
If the information is in an additive dimension, e.g. a percentage of a population, use an additive representation.
A
B
C
D
A Substitutive Dimension
A
B
C
D
An Additive Dimension
All visual distinctions should be made as subtle as possible while remaining clear
and effective for the purpose. Sometimes parallel information streams can be utilised to bring about clarity, efficiency, forcefulness, rhythm and balance. Multiple images can also be used to reveal repetition and change, pattern and surprise
(Tufte, 1997).
Asynchronous awareness
Feedback in an EIS will commonly be continuous and real-time but in some
applications the actors might be able to choose when they want to take part of
the feedback. In a pause, a break, or an uneventful period of the phenomenon the
actor can take time to study the information available so far. The data collection
from the actor can be continuous, but the extent and characteristics could change
when the actor explicitly takes part of the feedback.
Timing is certainly an issue that needs further exploration, e.g. the effects of
different feedback delay, jitter, and update frequency as it relates to the type of
application.
Some EISs might be running continuously, others could be active just when
an actor is present in a certain area (spatial restriction), or during certain time
intervals (chronological restriction), or on request from an actor (personal restriction) or when a critical mass of actors are present (emergence restriction).
Building the actors’ experience
An EIS is a combination of objects, events, and services, populated by a number
of actors existing and acting in a social environment, a physical environment, and
an information environment. The complexities implied by EISs obviously relates
to two of the trendier areas of social science: Large Technical Systems, LTS (Mayntz
& Huges, 1988) and Social Construction of Technology, SCOT (Bijker, Huges &
Pinch, 1987) which both concern complex systems that often are beyond the
actors’ (or anyone’s) comprehension. Donald Norman maintains, in The Invisible
Computer that computers are too difficult to use, and that simple information
appliances are needed (Bergman, 2000). The use of a PID, considered as an information appliance, may have the effect of keeping down complexity from the individual actor’s point of view, even though the actor with that same device enters an
EIS with complex transactions and processes beyond comprehension. One may
Figure 12. Substitutive and additive
dimension. Each of the ovals represents a value along the dimension from A to D. In the substitutive
case, the representations replace
one another. In the additive case,
each successive representation
includes the previous. Examples of
additive dimensions are loudness
and brightness. Examples of substitutive dimensions are pitch and
hue - adapted from Norman
(Norman, 1991).
Interaction
53
wonder whether (digital) EISs may have a general effect of shifting the complexity
distribution to make the individual’s role less complex, but the system more complex. If so, how far do we want to go in that direction? (We would probably want
to stop short of the architecture of an ant society.) If the shift is relative rather than
absolute, we may rather see the introduction of EISs as a way of making a more
complex society possible.
Within the area of Industrial Design research, theorists talk of the trinity of
good design; industrial design is the process of producing useful, usable, and
desirable products (Weed, 1996). The usefulness (purpose) of an EIS system can of
course be debated from case to case. Obviously, if the actors think that the EIS is
just a waste of time, their motivation and attitude towards the system might drop
dramatically. Usability concerns ergonomic and cognitive issues; e.g. we should
not have PIDs that are difficult to hold or with illogical arrangements of buttons.
Desirability is considered to be the most unpredictable part of the design craft.
What makes a product desirable? In most cases it is closely connected to context
and culture; designing a PID for youths in Norway differs a lot from a PID for
senior Singaporeans. When designing a product, all three parts of the trinity must
be taken into consideration.
One way to improve the quality of design is to conduct ethnographical user
studies to determine which kind of prototype to design, an approach successfully
adopted by e.g. Nokia. The look and feel of the EIS is very important for success,
since the human actors are the prime movers of the system.
Open issues
We have only been able to begin to answer a few of the questions about EIS interaction and user interface. Much depends on the application; the high-level model
is too unspecified and abstract to give any leads towards a successful user interface.
In this kind of novel interfaces, all the problems and possibilities will not surface
until a prototype has been built and tested in a reality-like environment. When
the application prototype has been tested by the actors, an iterative process can
start with ethnographical user studies, concept design, early user tests, evaluation,
redesign, detail design, user tests, evaluation, and redesign - which will result in
the final user interface.
To sum up, EIS interaction promises to be a very interesting research area, even
though many of the problems are in common with other types of applications.
When specific EIS concepts has been chosen, we can go deeper into detail on
how the feedback can be presented to the actors in the best way. At this point,
we believe that a flexible system where the individual actor can choose type of
presentation is preferable. Flexibility is also desirable in choosing type of input
sensors or devices, especially in ad-hoc systems where the actors bring their own,
personal devices.
It is also important to create useful applications; otherwise negative attitudes
might bias the actors’ experience of the EIS. Much of the current research in
interaction technology concerns future concepts, which are mostly unavailable in
the near future. This suggests that one should start out with fairly uncomplicated
concepts and successively add on features as the EIS research program evolves.
54
Sociological Aspects
8. Sociological Aspects
How does a collective “think”? What do we mean with thinking?
Can there be different kind of groups and how do they react? How
does social delusion (mass “hysteria”) happen? What kind of feedback will different kinds of people react to? How can intentions
and emotions of a group of people be estimated? Can there be systems where the users believe that they interact but actually do not
(placebo effects)? These are some questions concerning emergent
interaction systems for which there could be answers in the social sciences. The purpose with this section is to emphasise the importance
of the social aspects when studying, designing, implementing, and
running emergent interaction systems.
Simply speaking a group of people with something in common, which is in
focus of their communication, could be called a community. One important characteristics of a community is the communication, without which it would be just
a number of people focused on the same interest. There are two main reasons
why communities are of interest for emergent interaction system research. First,
emergent interaction systems can be used to support the emergence, maintenance,
and the phase-out of communities. Second, a lot of research concerning different
aspects of communities has been done, from studies covering quite technical
aspects to studies covering more sociological and psychological aspects of communities, and studies in between (Stolterman, 2001). A community can be characterised by a number of characteristics (Croon & Ågren, 1998; Jacobsson, 2000;
Valtersson, 1996), see the list below. An open question is which of them are relevant for emergent interaction systems.
•
virtual and/or physical
•
kind of medium
•
time aspects: fast, slow
•
openness, private sphere
•
activity level, history
The structures of a community will also set the tone for the behaviour of its members; it will serve as a context for behaviour. The structures could be religious or
cultural, and depend on age and gender. For instance it is not enough for an individual to have strong religious beliefs, it is also necessary that the beliefs occur in
a community with such beliefs and that the community structure reinforces the
individual beliefs. This is the influence of the community structure, as described
in (Stark, 2001).
There are groups of actors in almost all forms of communities; actors with a
similar way to act, behave, think, etc. Such groups can be characterized by several
parameters such as: how well known the group is, what it is that makes it a group,
how active the group is, how easy it is to identify a group or members of a group,
the self-awareness of membership, the dynamics of the group, etc. Some issues
that concern emergent interaction systems have to do with mechanisms to identify groups and group members and mechanisms to control the behaviour of different kinds of groups. There is a need to identify relevant ways to characterise
groups (interesting parameters).
There will be no emergent interaction if the actors are very few; so one question is how many users are needed. What is the critical mass required, for a certain
emergent interaction system, before we can even talk about emergent interaction?
Given a collective that is big enough the next question is how does a collective
“think” and what do we mean by “thinking”? That leads us to reflect on how
Sociological Aspects
The Seattle Windshield
Pitting Epidemic
Suddenly a lot of people started
to report that the windshield of
their car has been damaged, they
reported tiny pit marks in the
glass. The episode started on
March 23, 1954. On April 14th the
police had logged over 3000 vehicles with pit marks. On April 16th
the police logged 64 pitting complaints, and 10 on the 17th, but
after that date, not a single further
report was received. The police initially suspected vandals, but as the
number increased, it soon became
evident that this was not the right
explanation. Speculations concerning sandflea eggs and atomic fallout from hydrogen bomb tests
were spread. However an investigation a few years later determined that the pits had always
existed. Influenced by the rumours
and spurred by a few initial cases
amplified by mass media, people
started looking at instead of
through their windshields.
55
social delusion can happen - how does something like “the Seattle Windshield Pitting Epidemic” emerge (Bartholomew, 1998)?
Several key factors on mass or collective delusion could be found in this particular story. From the presence of ambiguity and anxiety, to the spread of rumours
and false plausible beliefs over to a redefinition of the potential threat from general
and distant to specific and imminent. Interesting factors include human perceptual fallibility, mass media influence in spreading the fears, recent geo-political
events, and reinforcement of the false belief by authority figures and people in
institutions of social control.
If a specific emergent interaction system would have an external observer that
could predict something like a riot, what would be the best way to stop it? – Go
in and manually change the feedback or the time constant for the feedback, or
maybe something else? What could be the impact of having outside observers or
control persons? Would the users care? Is there a risk for a 1984 scenario or will
people just not use the system? Considering that people in a crowd have a tendency to be easy to lead we might build the emergent interaction system with or
without external control, depending on the purpose of the system.
Emergent interaction systems are a kind of applications where security, integrity, and privacy issues are important – people want to be alone, they are afraid
of being logged, and they worry about the data being transmitted in a secure
way. There is a risk for losing the control over the system with an escalation of
unwanted effects. There is another aspect of security, the risk that an unauthorized
person takes the control over the system. That definitely could cause unwanted
effects.
An emergent interaction system collects data from actors in the system. If the
system treats data from all actors equally the system is a democratic system. If the
system treats the actors unequally it is an undemocratic system. It is also possible to
imagine systems that dynamically change their democratic/undemocratic behaviour. For example, in the normal case the system is a democratic system, but under
some circumstances the system turns into an undemocratic system, giving one or
several actors a more prominent role in the feedback loop. Some of the interesting
issues are social: how and when is it considered appropriate to use a democratic or
an undemocratic system?
Wrange’s Average Citizen project plays with the normal structures in society
(Wrange, 2001). A real person (Monika) that best matches the average statistics
of the society (in a number of parameters: age, number of children, etc.) represents the community. By giving her the same conditions for communicating her
(and thus - in some sense - the community’s) opinions that politicians and other
prominent citizens have, the normal structures are sidestepped. The idea with the
projects is to study how Monika’s opinion affects the society.
Should the actors be aware of participating in the emergent interaction system,
of the existence of a group, of the manner in which they may affect the system,
and to what extent? Could we have placebo effects – would it be possible to fake
(parts of ) the feedback loop and still give the actors the same experience of really
being a part of the event? It seems important to identify and characterise levels of
user awareness, maybe create a taxonomy.
Open Issues
In this section more questions than answers have been created; it is an open field
with a lot of interesting research to do. Building an emergent interaction system,
the sociological aspects would have to be considered in advance and measured
during a period of testing to make sure that no really bad effects will emerge.
Potentially relevant scientific disciplines include psychology, sociology, pedagogy,
cognitive science, artificial life, theology, economy, and more.
56
Data, Information, and Knowledge
9. Data, Information, and Knowledge
What can be computed? What data are needed to make intelligent
computations? What are data, system data, personal data, and user
input? What kinds of representations of data, information, and
knowledge are suitable for the kind of computations that EI applications fall back on? Answers to these questions and similar can be
found in the areas of computing science and information science.
The purpose with this section is to bring out the computational
aspects of emergent interaction - the processing of data, information, and knowledge transformation, with a focus on the Compile
and Compute Unit in the model and the computation of the feedback function. The shared feedback loop in an EIS consists of a number of logical
components (see the model description on page 17), where the compile and compute function plays a central role. Many of the other components are discussed
in previous sections. The Interaction section and the Technical System Aspects section discuss the technical aspects of the data collection and presentation parts. The
Sociological Aspects section discusses these aspects from a human perspective.
One of the most prominent facts of computing science is that not all mathematical functions are computable, in terms of theoretical as well as practical
limits of time and memory resources - even for the fastest computers (top500.org,
2001). For example, to solve the problem of the travelling salesman* with 40 cities
requires O(39!) elementary calculations. If we have a very powerful computer that
is able to test 1015 routes per second#, solving this problem will still take many
times longer than the lifetime of the universe. Since quick feedback and is important in emergent interaction, the computational time and memory requirements
need careful analysis.
The compile and compute functionality can be designed for different ‘levels of
ambition’:
•
Basic feedback, i.e. compile data into feedback information. For example,
compute max, min, and mean values, display distributions, etc. That means
that the system leaves the high-level interpretations of the information to
the actors.
•
Analysed feedback, i.e. analyse and identify the interactions and behaviour
in the system. In this case, the computation performs some of the highlevel interpretations of the information in the system. For, example identifying categories of behaviours, matching individual data against collective
data, etc.
•
Controlled feedback. Equipped with a context model (which must be continuously updated) of the actors and other parts of the environment external
to the technical system, the technical part of the EIS (the CCU in particular)
can be made to have some idea of what is going on in the system as a
whole. Given that the compile and compute unit has instructions about
what is considered desired system behaviour, and has some methods for
controlling the behaviour, feedback could be dynamically engineered to
take the EIS in the desired direction.
The functional model of EIS that was introduced in section, Emergent Interaction Systems, leaves many design issues open, such as the question of the level of
decentralisation of the compile and compute functionality. Hence, it is relevant
to study different computing paradigms and how well they suit different parts of
EISs, different system architectures, etc.
The data collection plays an important role for the compile and compute functionality. First, which information is picked up from the users and the environment sets definite limits for what can be computed. Second, what we want to
achieve with the EIS bears on what information is appropriate to deliver as feed-
* A salesman have to visit all cities
but want to minimise the distance
to travel, the salesman is forbidden
to visit a city more then one time.
This problem seems to be trivial.
#
The fastest computers today,
which are clusters of many computers, have a peak performance
on 10 12 elementary operations per
second.
Data, Information, and Knowledge
57
back, and must also guide the design of the data collection system. Third, there
are now sensors for almost any basic physical variable, but the problem is how to
take care of the data and give it a reasonable interpretation. Generally, the computational issues of EIS can be expected to be harder to deal with than the measuring
issues.
There are groups of actors in almost all forms of communities, actors with
similar way to act, behave, think, etc. (see section Sociological Aspects). There are
also recurring behaviour patterns without any obvious connection to groups or
established (sub) communities. From that perspective, if we wish to use analysed
feedback, there is a need to develop relevant methods to characterise and recognise
groups and behaviours.
There are many clustering algorithms, such as Latent Semantic Analysing/
indexing LSA/I (Dumais, Furnas, Landauer, Deerwester & Harsman, 1988; Foltz,
1990; Landauer & Dumais, 1997; Rehder et al.; Soto, 1998), Self Organisation
Maps (SOM) (Kohonen, 1988),K-nearest neighbours (Belew, 2000), Supported
Vector Machines (SVM) (Hearst, 1998), Bayesian Networks (Belew, 2000),
Markov based methods (Belew, 2000), etc., that are of interest for the CCU.
Many of these algorithms are used in the fields of data mining and information
retrieval, as well as in the fields of user modelling, collaborative filtering, social
navigation, and context awareness (Grouplens, 2002). One important research
issue is to identify properties of EISs and EI applications that make it easier to
choose techniques for user modelling and the design of the feedback; e.g. the
timing aspects of an application are important in this process. The techniques
themselves are also of interest to study, e.g. to make comparisons between them
in order to get a better idea of pros and cons with them.
Simulation of complex systems (such as ant societies, traffic situations, urbanisation, etc) is also a relatively active research area in computing science and related
areas (Resnick, 1994; Ropella, 1999), Simulations of that kind can be used as
a tool to study and develop emergent interaction systems, and test and analyse
how they work. For example, in EIS simulation different techniques, architectures
and application areas can be demonstrated, analysed, tested, or evaluated. Another
interesting use of simulation is to let it complement a real system in order to
build up system awareness. This can be used to decrease data traffic in parts of the
system, or to control the overall behaviour in the system. What to simulate and
how to do it needs to be investigated. Another issue to resolve is how to handle
the results from the simulations. Identifying new research topics could also be an
output from this work. One such idea is to see if it is possible to develop methods
for identifying the level of interaction and dependences between actors, behaviours, and knowledge structures.
Open Issues
To summarise, some of the open issues in this area are:
•
Study the different approaches to the level of centralisation of the “intelligence”.
•
Define the important characteristics of EISs from a data mining/clustering
perspective.
•
Development of fast and “memory greedy” algorithms for the processing of
the collected data.
•
Study different techniques for modelling knowledge structures.
•
Study how to mix the real and the simulated worlds for the system awareness issues.
•
How simulation environments like Swarm can be used to study the EI concept, etc.
•
Develop methods for identifying the level of interaction, especially
between ideas or knowledge structures
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Pre-study Outcome
10. Pre-study Outcome
The pre-study started with a tentative definition of emergent interaction. One
of the objectives was to test, refine, and deepen the initial notion and see if a
stable (project group) consensus on the emergent interaction concept would form.
Another objective was to pave the way for future, comprehensive studies of emergent interaction. This report can be seen as an umbrella spanning and defining
the area of emergent interaction. The purpose with this section of the report is
to summarise the results of the pre-study and suggest a general direction for the
future research in the emergent interaction area. The Designing for Emergence subsection summarises our reflections on the problems and possibilities on designing EI systems. The Emergent Interaction in a Context subsection is an overview
of the context in which EI exists. The subsection Possible Application Areas section
shows the large variety of proposals for EI applications, which have been identified
during the pre-study. The Prototype Requirements subsection lists suggested general
requirements for prototype EIS. The Open Issues subsection is a listing of proposal
for research within the EI area. The Suggestions subsection contains recommendations and suggestions for further work in the emergent interaction area.
Designing for Emergence
This pre-study has started an examination of the conditions for a type of applications supporting and exploiting interaction between the individual and the collective, theoretically inspired by the notion of emergence. It is appropriate that the
first four sections have dealt with Emergent Behaviour, Emergent Interaction, Emergent Architecture, and Emergent Interaction Systems. The novelty factor implied by
the emergence concept can be seen in a number of new applications building
on new technology plus the individual-collective relation, with sometimes quite
unexpected result. E.g. the GPS (Global Position System) technology has originated several novel applications, like GeoCaching and Digital Angel, and the
HTTP (Hyper Text Transfer Protocol) has resulted in a number of new and unexpected web applications such as MovieLens (MovieLens, 2001). Babelfish (Babelfish, 1999), etc.
Is it really possible to design emergence, is it possible to design the unexpected?
It may seem that “designed emergence” is a contradiction in terms. And of course,
if we believe that, then the idea of designing emergent interaction systems comes
to an immediate halt. Unpredictable outcome is inherent in the concept of emergence, but what we might be able to do is to design for emergence. A basic methodology for the standard EIS project of the future might go like this. 1. Think
about and decide on a very high level what kind of result, in terms of this or that
value or parameter the EIS should have. 2. Design for emergence, that is, design
a system that satisfies some identifiable (believed to be) necessary requirements
for such effects, and which might (we believe) produce them if we are lucky. 3.
Implement and run a prototype (possibly as a simulation). 4. Evaluate how far the
system goals are satisfied. 5. If the system is a failure then try to analyse why it was
unproductive or counterproductive and start over. If the system is a partial success, analyse the emergent system and try to understand what happened and try to
identify crucial parameters and design decisions. Then redesign (modify, adjust),
evaluate and iterate until the result is satisfying.
The first point is that, even though we cannot anticipate how a planned emergent system will behave and thus, if we are lucky, how it will deliver the wanted
effects, we may yet be able to put together a system of which we have reason to
believe that it may produce the wanted effects. The second point is that, once we
have an existing emergent system, good or not so good or even counterproductive,
then we have something that can be analysed, explained and understood, after the
fact.
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This approach to the design of emergent interaction systems – let us call it emergent design – can be compared with standard methods of designing information
systems, building on a number of well-known design principles (Margolin &
Buchanan, 1995). Emergent design is a type of iterative design and also has some
resemblance with the participatory design approach (Hackos, 1997), where the
interplay between the users and the designers of the (technical) system is an
important part of the development process. Participatory design, however, is a
traditional development methodology in that it focuses on how the task is performed. Emergent design, by contrast, has its focus on the wanted overall effect
and purpose of the application, and the conditions for emergence, and it works
by iterative redesign guided by emergent system analysis, after the fact.
In a more advanced form of emergent design, we may even make the design
activity part of the system being developed. The designers are on-line actors in the
system. They try to control and guide the system behaviour into what they deem
to be the right direction, serendipitously taking advantage of lucky but unforeseen
effects, opportunistically changing their minds about what the right direction is –
based on the system’s actual development in time. According to Stolterman information technology is the perfect technology to create what he calls tectonic systems.
“A system can, of course, be designed without organization principles, or only
with locally (regionally) organization principles. We can label such system as
tectonic.”
(Stolterman, 2000)
The emergent design approach opens new dimensions for design, e.g. simulations
of complex systems may play a central role. Simulations of complex systems fall
back on an analysis of the basic primitives for the interaction, resulting in a wellstructured model of the ongoing phenomena. Simulation and the possibilities to
control the direction of behaviour development and analyse how different control
apparatus affect the system, are powerful tools in the design of emergence. Mixing
the simulated world (virtual) with the real world is another interesting option.
One example is discussed below.
This pre-study has identified several problems and open issues with emergent
interaction, which are necessary to have in mind for designers and implementers
of EISs. Reaching a critical mass is one of these potential problems. Simulation
can prove to be a generally useful tool. Simulation models offer the possibility to
start the system in simulated mode, phase it out and phase-in real mode. In the
beginning the system includes a number of simulated actors and a simulation of
the technical framework, with the designers acting in it. As more real actors join
the application and real EI-units are up and running, the designers and simulated
actors can be phased out.
Emergent Interaction in a Context
Emergent interaction is not an isolated concept. Due to the generality of the
concept and its connections to a broad variety of topics, there is much ongoing
research, development, a number of interesting applications, organisations, etc,
that can help to set emergent interaction into a context. The purpose with this
part is to give a view of this context in which emergent interaction has emerged
and exists.
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Pre-study Outcome
Applications
With regard to applications, the Arena/IT-Hockey and eStreet, developed at
Mäkitalo Research Center in Luleå, are related and of obvious interest. Arena is a
future-oriented programme for the development of new services, applications and
technologies that support different types of public events and enhance spectator
experiences, mainly in sports (like IT-Hockey), cultural and trade-fair contexts.
eStreet is a collaborative programme for developing and testing new mobiletelephony services and technologies for commercial and public-service information in a real-life setting (MRC, 2001b).
Telia Mobile’s application FriendFinder is another application of interest where
the mobile phone users can share their own position with their friends (Telia,
2001). Digital Angels is an application that combines location monitoring and
monitoring of selected biological functions. That makes it possible to find a
person, animal or object anywhere in the world, anytime, and to do medical
monitoring over distance (Digital Angel, 2001).
Other examples in the area of positioning are Geocaching, which is an adventure game for GPS users. Participating in a cache hunt is a good way to take
advantage of the features and capability of a GPS unit. The basic idea is to have
individuals and organisations set up caches all over the world and share the locations of these caches on the Internet. GPS users can then use the location coordinates to find the caches. Once found, a cache may provide the visitor with a wide
variety of rewards. All the visitor is asked to do is if they get something they should
try to leave something for the cache (Inc, 2001).
Figure 14. Example of GPS art from
a walk in Brighton (Melin, 2001).
GPS-art, drawing pictures by tracing your own walking path, is another existing
example of how positioning systems can be used in a new emergent way, a way
that the system designers did not intend when they developed and launched the
GPS in 1989 (Pryor & Wood, 2001). The sport of orienteering has also started to
use GPS to visualise the participators’ positions, for example superimposing the
runners’ results as if they started at the same time.
The web and the manifold of web-application have emerged from a very
simple application protocol (http) on the TCP/IP stack. Hence, the web it self
is an interesting EIS to study. In addition MovieLens (MovieLens, 2001) and
Amazon.com (Amazon.com, 2002) are two web-applications that we use in this
report as examples of EISs with a focus on the virtual room, to this two application the concept of web-portals can be added to exemplify this kind of emergent
interaction systems.
Technical Frameworks
With regard to technology we have found the Russian wireless peer-to-peer communicator Cybiko Xtreme to be an interesting appliance that can be useful as a
test bed for future applications and prototypes (Inc, 2002). Wireless Local Area
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Networks, WLAN (Armenta, 2002), and the Bluetooth (Bluetooth, 2001; Miller
& Bisikian, 2000) technology for mid-range and short-range communication are
basic technologies ready to use, as well as cellular phone technologies, especially
2.5 and 3 G platforms, GPS,and GIS. The Ericsson Erisoft’s Event System (Ericsson, 2002) and similar platforms such as Digital Angel systems makes it possible
to start implementing EISs and applications without putting lots of resources on
implementing the infrastructure for EIS.
Microvision’s display based on the virtual retina display technique from HITL
is a very interesting technique for presenting visual feedback on personal level in
EISs (Microvision, 2002; Tidwell, Johnston, Melville, & Thomas A. Furness III,
1995).
Orad is a company with many interesting technologies aimed to enhance the
experience of a broadcasted arena event. For example techniques for: tracking positions of the actors in real time and visual effects on broadcasted events (Orad, 2002).
Wiki is a collection of web pages, which can be edited by anyone, at anytime,
from anywhere. Ward Cunningham created the concept in 1994 (Cunningham,
2002). The name originates from wiki-wiki, which is the Hawaiian word for
quick. This technology could be used to create virtual EI systems on the Internet.
Research and Development Projects
Even if the field of emergent interaction research is new, there are many organisations running research and development projects relevant for the further understanding and development of the emergent interaction field. It is hardly possible
to give or to have a total view of all ongoing projects with relevance for emergent
interaction. Thefollowing brief walkthrough is an attempt to giveat least some
idea of the ongoing research relevant for emergent interaction.
MIT Media Lab, at Massachusetts Institute of Technology, Cambridge, is
doing research in many areas relevant to EI. One example is the Things That
Think consortium (MediaLab, 2001) with a focus on making things that interact with their surroundings. Another important example is the affective computing research group (MIT, 2002) with their focus on “measuring emotions” with
biosensors, and using these techniques for various applications.
The Center for Lifelong Learning and Design (L3D) at the University of Colorado at Boulder is another important research organisation (L3D, 2002) for the
EI view. They also do research in a very broad field with many exciting ideas and
applications in which the LSA algorithm is used to analyse knowledge structure
and development of knowledge structures (Berry & Dummais, 1994; Deewester,
Dumais, Furnas, Harshman, & Laundauer, 1990; Dumais, Furnas, Landauer,
Deerwester, & Harshman, 1988; Foltz, 1996; Foltz & Dumais, 1992; Knowledge Analysis Technologies, 1999; Landauer & Dumais, 1997). The GroupLens
Research at the University of Minnesota in the field of collaborative filtering,
(Riedl & Konstan, 2001) is also interesting for the research on EI. Mainly for
the kind of system they study, but also because they attempt to utilise the LSA
algorithm in their applications (Konstant, 2001).
Humle lab at the Swedish Institute of Computer Science (SICS) (SICS, 2002b)
at Kista, has a number of relevant projects, especially the projects with a focus on
social computing (SICS, 2001b) and social navigation projects like PERSONA
(SICS, 2002c). Geonotes (SICS, 2001a) is another project at Humle lab with relevance for the EI view. It is relevant for the attempt to merge the physical and virtual worlds with an application that makes it possible to make notes connected to
geographical objects (like Post-It notes on physical objects). Chalmers Media Lab,
Gothenburg, with their Digital Senses project goes in the same direction and does
research related to problems in the borderland between the physical and virtual
worlds (Chalmers, 2001)
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Pre-study Outcome
The Department of Informatics at Umeå University, Sweden is doing research in
several fields with relevance for the research on EI – IT-democracy and design are
two areas – the Net-Life group with their focus on virtual communities may be
the most relevant for the research view on EI (Stolterman, 2002), for their studies
on various aspects on being on the net.
The research field that has made emergence a fundamental concept, is referred
to with a multitude of different names, e.g. Complexity, Complex Adaptive Systems, Emergence, Self Organization, Artificial Life (Alife), etc. This is problematic, since it makes it very hard to overview the field. Three Nobel Prize laureates
founded the Santa Fé Institute (SFI), with the ambition to bring researchers
together in order to explorethe science of complexity (Goldberg, 2002). The SFI
pioneered the field and is still an important centre for this type of research. Many
other groups have also come to specialize in the field, for example the MIT AI-lab
(Brooks, 2002), the Center for the study of complex systems at the University
of Michigan (Simon, 2002), the People, computers and design group at Stanford
(Winograd, 2002), and the Complex systems group at Chalmers in Gothenburg
(Lindgren, Mehlig, & Nordin, 2002).
The Computer and Network Architectures laboratory (CNS) at SICS conduct
research in the context of ad-hoc networks and communication for appliances.
Especially the research about ad-hoc networks is relevant to EI (SICS, 2002a).
The Mäkitalo Research Centre (MRC) at Luleå Technical University, Sweden,
is a research centre for wireless technology and applications. At MRC new mobile
Internet products and services are created and developed. Examples of research
programmes are Arena and eStreet (MRC, 2001a, 2001b, 2001c).
There are many interesting projects in the arts and humanities with relevance
for emergent interaction, especially for the ideas concerning the design for emergence and how to communicate ideas to individuals and groups in new ways.
Måns Wrange’s Average citizen project (Wrange, 2001) and Kenneth E. Rinaldo’s
art project Emergent systems (Rinaldo, 2001) exemplify the latter; in Wrange’s
case by representing the society’s opinion with one physical person, and in Rinaldo’s case with a manyfold of interesting forms of presentation of the system status.
Animationshuset with their focus on the use of the animations as a form for interaction is another institution conducting research with relevance for EI systems
(Löwgren, 2002).
Research concerning the language that art directors and movie directors use in
their communication with the actors is interesting from a design perspective on
EIS. HUMlab at Umeå University is an interdisciplinary laboratory for human
informatics, digital culture and art, and a meeting place for humanities, culture,
information and media technology. Some examples of HUMlab projects are English language in transformation, Virtual weddings, Streamed media in language
education, Magic Touch, Cultural simulation, Aggressive behaviour in online communities, and Virtual ice (Svensson, 2002).
Journals and Conferences
Journals and conferences are both natural channels for spreading ideas in the
research community. The list below is a selection; of course there are many more
that are relevant for spreading ideas concerning the concept of emergent interaction.
Journals
·
Personal and Ubiquitous Computing, (Springer, 2002).
·
Mobile Networks and Applications (ACM, 2002b).
·
Wireless Networks - The Journal of Mobile Communication, Computation and Information (Kluver, 2002)
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·
International Journal Universal Access in the Information Society UAIS
(Stephanidis, 2002).
·
Human-Computer Interaction, (Moran, 2002).
·
Complexity International is a refereed journal for scientific papers dealing with any area of complex systems research. (Green, 2002).
Conferences and Workshops
·
2nd International Symposium on Smart Graphics (Butz, Krueger, Olivier,
Schlechtweg, & Zhou, 2002).
·
Complex Systems (CS02) - Complexity with Agent-based Modelling
(Namatame, Green, & Aruka 2002).
·
DIS2002 Designing Interactive Systems. A venue for serious reflection
on the practice of designing interactive systems, exploring the aesthetic, social and cultural dimensions of new technologies (Sutcliffe &
Verplank, 2002).
·
Artificial Life VIII The 8th International Conference on the Simulation
and Synthesis of Living Systems (Standish, 2002).
·
The annual ACM CHI conference (ACM, 2002a).
·
ACM International Symposium on Mobile ad hoc networking & computing (Hubaux, 2002).
Possible application areas
A large number of ideas for EI applications have been proposed and organised in
nine categories. A complete listing of all the application ideas for EI can be found
in Appendix A. The nine categories are:
1) Knowledge Society Events, supporting the emergence of knowledge both on
the individual level and in society/community level.
2) Exercising Events, enhancing the experience of collective athletic activities
like spinning, aerobics, dancing or swimming.
3) Home Activity Events, with the idea to support the emergence of communities focused on home activities; make it easier, more fun, feel affinity when
eating dinner, watching TV, sleeping, etc.
4) Professional Events, applications to feel presence over a large distance, like
meeting, factory floor, problem solving and design and empathy training.
5) Public Space Events, for rational reasons like making shopping more effective or looking up bus timetables, or for pleasure, like visiting restaurants,
pubs or exhibitions.
6) Political Events, supporting the democratic process, both communication
activities and the control apparatus, in terms of demonstrations, elections,
avoid/track crime activities or even war.
7) Communication Events, for shortening and bridging of distance, car-pooling,
tourist guidance, implicit traffic control, extended videophone conferencing, etc.
8) Arena Events, to extend and enhance the concept of arena events, for example make the audience more active or participating, or widening the arena
into the virtual world for theatre, track and field, or collaborative art.
9) Community Events, supporting activities intended to increase the engagement, attendance, kinship or similar qualities in applications like hunting,
instant communities, gardening, social life, or to create new contacts.
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Positive and negative aspects
The general discussion has resulted in a group consensus that the concept of
emergent interaction could and should be used to increase and enhance social life
with participation and engagement in some sense, and with new ways of forming
acquaintances. Prototype systems of this kind would be an attraction and would
make the concept more concrete and visible, it might also create a general feeling
that EI applications are cool and trendy.
The identified associations between emergent interaction applications and
Orwell’s 1984 scenario put the finger on the main weakness of the EI concept the secrecy issues, the integrity issues, and the risk for promoting also negative
tendencies in the society. The general discussion has also identified a number of
other worries.
Prototype Requirements
The activities for finding application ideas resulted in about seventy suggestions.
These systems are all more or less realistic to implement, especially as a prototype
serving to test ideas and to use as a research platform for studying different aspects
of EI. In order to evaluate and rank the ideas, it is necessary to set up prototype
requirements. The requirements cover technical aspects such as system platform,
time and cost, as well as utility aspects and some more pragmatic aspects. It is
hard to put the requirements in priority order, so they are simply arranged into
four categories: Cost Requirements, Technical Requirements, Effect Requirements,
and Security Requirements. This categorisation is ambiguous, (i.e. some of the
requirements fall into more than one category) and each requirement is described
under just one category.
Cost Requirements
One important aspect of the feasibility of a project is the cost. We have focused
on the costs for implementation of a system platform, travels, personal resources
and regular tests. In order to cut the travel costs, the event must be located in the
near region or be more or less a virtual event. It is also good to have something
to demonstrate in the near region. To implement an EIS system from scratch is
costly. One solution is to build a prototype upon existing platforms, such as Ericsson Erisoft’s Event System platform (Ericsson, 2002) and Digital Angel platform
(Digital Angel, 2001) based on GPS and WLAN technologies. This is also a technical requirement and a motive requirement; it is interesting from Ericsson’s point
of view to evaluate their platform in a research system, to find pros and cons with
their technology.
One way to cut the costs for the implementation of a prototype is to associate
master thesis projects to the implementation project. In order to minimise the
cost of evaluation of different aspects of the EIS it is necessary that the event
occurs repeatedly or constantly. A one-time event will not do. This is also an effect
requirement; interesting effects may not emerge in a short run. E.g. a community
is normally a relatively slowly developing phenomenon. Another way to reduce
the cost for development is to define open source projects where volunteers participate in the development of the application. The projects can be presented on
the Internet, for example (McGovern, 2002) and thereby be available for participants all over the world.
Technical Requirements
Emergent interaction covers a very broad spectrum of research issues ranging from
technical to sociological. The technological view is focused on studying data communication, with traffic patterns, possible WLAN technologies, and evaluating
new technologies in large. This has lead to four technical requirements on a prototype implementation. First, the potential for the use of 2,5G or 3G mobile
Pre-study Outcome
65
telephony terminals and/or variants as PIDs is an important factor for a future
market evaluation of the system and therefore an important technical requirement on a EI prototype. Second, a similar requirement is the support for different
communication interfaces and PIDs. Third, the potential usage of new technology, such as wireless (HiperLan2, 802.11a, etc), for the communication is also
a valuable factor, it is necessary to minimise the bottlenecks in the communication and one way to that is to use as good as possible techniques for communication. Fourth, data must be easy to access and compile, technologically as well as
cognitively. From a technical point of view is necessary to use existing and stable
techniques for data collection, and to utilise standard interfaces for the communication with sensors.
Effect Requirements
Even if it is hard to predict the impact of an implementation, one of the strongest requirements on a prototype is that the prototype should create an emergent
interaction effect (obviously). One research issue associated with that requirement
is how to identify or prove such effects. Another requirement is that it must be
an interesting effect for all kinds of actors in the system; otherwise we risk ending
up with a system without any actors. Also, the prototype must allow variations in
the feedback so that their effects on the actors’ experience of the system can be
studied, e.g. feedback with a natural, statistical, or more surrealistic character. A
basic requirement on a prototype implementation is that it must be easy to follow
up and evaluate. This puts some restrictions on the system, how distributed it is,
the size of the test groups, the kind of event, how long it will take before interesting things begin to happen, etc.
Security Requirements
Effort must be laid on security aspects even for the EI prototypes. At least a first
draft of a security policy should be specified and used when designing prototype
systems. In the early projects the policy can specify both which security measures
that shall be implemented and those who will not.
Summary of the requirements
To summarise, the following requirements are the result from a discussion about
how to implement prototypes. These can be seen more as a set of recommendations to chose from than mandatory requirements.
•
2,5G or 3G potential and/or variants
•
Built upon the Event System platform
•
Easy access and compilation of the data
•
Interesting effect on the participants/users
•
Interesting for a proposed owner of such a system
•
Interesting parts for UCIT, the project and the project parts
•
It should use an event that occurs repeatedly and/or always
•
Master thesis task should be possible associate with the development
•
Possible to do follow up and evaluation of the result
•
Possible to implement during the spring 2002
•
Support for different communication interfaces and PIDs
•
The event shall be in the Umeå (campus?) region
•
The prototype should create an Emergent Interaction effect (obviously)
•
Usage of new technology, such as WLAN (HiperLan2, 802.11a), etc.
•
The uniqueness of the application is important for the choice of prototype
system
•
Security aspects must be considered
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Pre-study Outcome
Open Issues
Many of the sections in this report have listed issues for further studies. The
intention with this section is to draw attention to some of them, and the wide
scope of research tasks for EI identified in this pre-study. Each area can be studied separately in small research projects or together with others in larger research
projects.
One example of issues to resolve is the largely hypothesized positive and negative aspects of EI that originated from the brainstorming activities. Many of these
statements lack verification, and it is important to find out of which of them correctly describe the actual situation.
Another interesting area to study is which architectures to use when designing
different EI applications. Many research topics can be found within this area,
such as how communication protocols and mechanisms should be specified and
implemented. Different technologies and topologies can be designed and evaluated. Other examples are how to design the systems to ensure that they are scalable and able to handle large numbers of actors. Related to this are issues of how
to satisfy the requirements on data communication, network capacity and services. Different technologies and standards and their use in different situations to
handle the need for communication in the EIS can be studied.
The design of user interfaces for EISs is another important area for research
and development, to ensure that the interaction works well. This is essential to
create the wanted effect and to make the EIS attractive to use. By creating scenarios, interesting ideas and concepts for the interaction between users and the
different EIS applications can be tested and evaluated.
There are many unresolved issues about computation. Which existing algorithms can be used and is there a need to develop new algorithms? Can computation be distributed between actors in the system and what mechanisms are needed
to ensure that this works as intended?
The different aspects of security, integrity, authentication, authorisation, (location) privacy, etc for emergent interaction systems, make up a large research area.
Methods for implementing security and integrity policies could also be studied.
This is at least partly related to the sociological aspects and effects that EI applications could create. How should systems be designed to avoid unwanted effects?
Many open issues remain to be resolved in the sociological area.
A more technical issue is which sensors can be used in EI systems and how they
communicate with other actors in the EIS. What data can be collected from the
participants and what can we get directly from the shared phenomenon? Is there
a need to develop new sensors for EIS applications?
What EI aspects and applications can be tested and evaluated by simulations?
One example is evaluation of protocols. Another use is to simulate parts of an EIS.
For example, by simulating a large number of users one could test and evaluate
applications without a large number of test pilots.
This is only a few of the areas for research and development that have been
mentioned in this report. It is an extensive field to cover. The next section therefore presents more specific ideas about how to proceed with our study of emergent
interaction.
Suggestions
How should the result from our pre-study be used? This report can be seen as a
framework for emergent interaction research, serving both as background information and as an outline of the possible research directions for the near future.
Emergent interaction systems have potential to generate a market for commercial
products. Emergent interaction research and development has a great potential to
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67
engage both universities and the industry. There is much ongoing research and
development activities around the world with relevance for emergent interaction.
The fact that all participants in the pre-study (Cognitive Computing Lab, Digital
Media Lab, Interaction Design Lab, Virtual Reality Lab, and Ericsson Erissoft)
were able to identify relevant issues to study and interesting ideas to develop shows
that the UCIT research program on emergent interaction is well anchored.
The following activities have been identified as high-priority issues in developing the field of emergent interaction, and should be included in the research program.
Implementations
A small number of EIS prototypes need to be built. The main motive is the necessity to have some test environment that can provide empirical support and feedback, in order to develop the emergent interaction concept further. In choosing
prototype we obviously want it to be of interest for all participants in the projects,
i.e. all UCIT labs, other academic participants, and industrial participants such
as Ericsson. Another requirement is the potential interest of a proposed owner of
such a system. The time aspect of the implementation also constrains the choice of
prototype system, e.g. kind of available techniques, the complexity of the system,
etc. The prototype must be possible to implement in the near future, for two reasons. First, we need it to continue our studies. Second, it is important to be able
to illustrate and demonstrate the concept; it will be much easier to establish the
concept with one or two implementations to point to. The choice of prototypes
also depends on the focus and goal of the research program and what the participants think are important for them.
Besides the prototypes, simulators would also be helpful. Simulators are needed
for the further development of the emergent architecture concept and the emergent design approach, but are also useful for basic research on emergence in complex systems.
When developing EI prototype systems it is probably best to start in a small
scale, with already proved techniques, to cut the costs and get a smooth start of
the project. We also recommend reducing the complexity of the first systems. One
way to do this is to skip the mobility issues in the first versions. By involving
students doing their master theses the EI concept is introduced on a broad front,
especially to the system developers of tomorrow, and we get much of the work
done at a low cost. Another recommendation is to perform as much of the prototyping in the near region. It is also wise to select a recurring or continuous event
for the application, to be able to perform detailed tests and verifications.
To quickly establish the concept of emergent interaction systems, we want prototype systems that are quick and simple to implement. Use as simple technology
as possible and make sure the solution is scalable. The design space of EISs is very
complex and so is the research area. Therefore, we think it is necessary to develop
two or three different and complementary prototype systems, to cover some of
the variety previously identified for EISs. For example, an application in a closed
environment (exercise events) with a relatively small number of users could be
complemented with a large open space application for a large number of users,
and a virtual system based on web technology.
Applications and prototypes implemented in the early phase of the research
program, must be designed in such a way that they easily can work as research
platforms, i.e. easy to make changes in, test new concepts, log data, etc. Three
candidates have been selected: spinning, collaborative art, and campus communities. The prototype requirements discussed above have been the basis for the discussion and selection of those three ideas.
68
Pre-study Outcome
•
Spinning – the main idea is to study the possibilities to enhance the experience of collective exercising with an EIS. This is an exercising event, in a
closed room (IKSU, 2001). Generally, there is a wish in this group of actors
to measure their performance. The kind of basic set-up that this prototype
requires is relatively simple. The actors sit on their bikes, which makes it
possible to start with a mostly wired infrastructure. There are many interesting research issues concerning social interaction, data, information, and
knowledge, data communication, etc., in this prototype. Its greatest advantage is that it allows starting in a small scale with a potential to extend
the project in many directions. A closed-room event is mostly associated
with a classic system design approach, but it also allows us to test adhoc/temporary infrastructure solutions, which means that emergent design
may be relevant in a longer time perspective.
•
Collaborative art – the main idea with this application is to create an
event in which a collective produce art by acting and interacting. Appendix
C- Collaborative Art, describes one example, which is a combination of an
arena event and a public space event. This prototype makes it possible to
test an open-room application. The application could be used to test an adhoc/temporary network, develop emergent architecture, and try emergent
design. Hence, development of simulations and an Emergent Interaction
Protocol (EAP) would be two important research issues for the implementation of this application. This prototype has the potential to involve both
humanistic parties such as artists and social psychologists as well as technical parties like mobile phone operators and developers of infrastructure
solutions.
•
Campus communities – the main idea with the prototype is to support the
emergence of knowledge, on the individual level and on the community
level; i.e. a knowledge society event. This can be done by feeding back
information about knowledge activities in the campus area - in the shortterm perspective but also in a long-term perspective. The early focus for
this prototype is on the virtual room, but it has potential to be an application in between the physical and the virtual. E.g. analysing informal meetings, connect cafeterias, etc. are things that can be implemented in the
prototype. Its virtual character will be mirrored in the design of the feedback loop and the technological choices. Web technology will be the base.
This application, too, can be used to test the emergent design approach
and ad-hoc/temporary infrastructure solutions. Umeå University is one possible partner, together with providers of infrastructure solutions.
From an Umeå perspective, the proposed applications cover three characteristics
of the city and its citizens. First, there are many people in Umeå doing some sort
of physical exercise, individually or in groups. Second, the cultural life of Umeå
is flowering, with many cultural events. Third, Umeå University and other education institutes play a central role in the everyday life in Umeå.
All proposals fulfil the requirement of being something to show. In that respect
the collaborative art prototype may have the greatest impact, both as a research
object and as a commercial object. The character of the room is different in each
proposal (closed, open, and virtual). Assuming that the closed and the virtual
room prototypes rely on well-known technical frameworks, they may be the easiest to implement. The campus prototype may be the one that would be most valuable for the society in large, in particular the near region.
Research and Development
The pre-study has identified many interesting basic research issues that need to be
studied, gathered into 21 focus areas. The four sections Technical System Aspects,
Interaction, Sociological Aspects, and Data, Information, and Knowledge cover the
focus areas and discuss the related open issues - summarised in the Open Issues
subsection above. Emergent design and emergent architecture are two ideas produced by the pre-study, which need to be further developed. We should:
Pre-study Outcome
69
•
develop a set of Emergent Architecture Protocols (EAP), which is a communication protocol stack for the emergent architecture
•
identify and develop new artefacts (emergent interaction units), based on
the EAP, that makes it possible to start implementing emergent interaction
systems based on ad-hoc/temporary infrastructures
•
develop the use of simulations in the design of emergent interaction applications, involving studies of the basic concept of emergence, and how to
characterise the basic primitives for interaction.
Establishing the Emergent Interaction Concept
For the success of emergent interaction the concept needs to be anchored in the
scientific community as well as in the commercial world. There are connections
between these two, and the process of concept establishing must include work on
the local, national, and international level. This work should have high priority
and the pre-study suggests that a special project should be launched to work with
these issues. Of course each of the sub projects of the research program must take
their own responsibility for establishing the emergent interaction concept. The EI
establishing project can work with:
•
seminars, locally to establish connections and find potential partners
•
presenting the ideas on courses at university level, e.g. design exercises
and in master thesis projects where different aspects of EI are in focus
•
arranging international workshops
•
making use of personal contacts to spread the idea and information about
results and plans
•
presenting scientific results at conferences, workshops, etc. and in scientific
journals
•
a web site for the emergent interaction research program. Internet publishing encourages people to give comments and ideas for further studies and
applications
The Emergent Interaction in a Context section above, discusses some of the channels that this project has access to.
Market studies
Emergent interaction has a potential to generate a market for commercial products on many levels. There are signs already today that such a market is beginning
to form. Here are some examples of what the pre-study has identified as potential
products or markets:
•
the EAP has potential to generate ideas for applications, similar to how the
development of HTTP has generated ideas for web applications
•
given EAP, there is a potential market for EIUs
•
emergent architecture has the potential to generate commercial products
at the infrastructure level, for example infrastructure for content providers
of the 2.5 and 3G mobile phone platforms
If one believes that EI has the potential for this, market studies must be done to
study the conditions for commercialising EI-related products.
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Pre-study Outcome
External financing
The research program obviously needs funding. It is of vital importance to apply
for financing from different research councils and funds, and the industrial/
commercial establishment. Part of this process and necessary for success is to have
good partners from the academia and the industry. The pre-study has formed a
basis for this work, and this report will be a useful reference for funding applications.
Summary
When this pre-study project was conceived in early 2001, a number of expected
outcomes and purposes with the project were discussed. Creating a better idea
of emergent interaction and preparing for a larger study was defined as the main
purpose of the pre-study. The readers of this report and the people that gave us
the assignment should judge if we have succeeded. Of course, we in the project
group do believe we have!
Independent of the concrete outcome, the project has been valuable in many
ways, on an individual level as well as on an organisation level. We have done
our work in an open-minded and creative atmosphere. The way that the group
has worked with the twentyone relevant areas (each with one responsible person)
has been quite successful. For example, the focus areas have guided the choice of
topics for the seminars, and have been used in the organisation of the report (see Focus area map). The experiences from the project can be summarised as: fun, lots
of new experiences, broad, exciting, demanding, and creative.
Appendix A – Ideas on EI-applications
Appendix A - Ideas on EI- Applications
Knowledge Society Events
Classroom, learning
+ Involvement
– Privacy issues
+ Wake up the students
– Dangerous to loose the control of the
system
+ Knowledge is an emerging and social
phenomena
– Brainwashing
+ Can make the classroom more
appealing
+ Possibilities to prohibiting harassment
bullying (mobbing)
Feedback from a class
+ Effectiveness of resources
– Integrity·
+ Quality
– Stress
+ Experience/ event
+ New phenomenon /behavior
Keeping track of a research society
Examinations
Finding Information
Self Knowledge
Exercising Events
Dance, disco music
+ Cool
– Hard to start
+ Distributed
– Risk for self oscillation
+ Atmosphere
+ Dynamic·
+ Profiles
+ Categories
– Removes tradition
Exercise event - IKSU
+ Nearness
– Hard to replace the human leader
+ Repeated
+ Receptive persons
Training, work out
Spinning/Team cycling
+ Distributed
– One-track
+ More effective
– What to measure
+ Pepping
– How give feedback
+ Feedback to the leader
– Unpredictable
+ Easy to measure
– Not everyone is doing it
+ Closed community
– Short-term
+ Clear border
– Too focused activity
+ Easy to enhance the experience
+ Good for your health
+ High acceptance for data collection
+ Often regular activity
+ Social activity
71
72
Appendix A – Ideas on EI-applications
Home Activity Events
Home economy administration/buy-sell
Eating dinner
+ Everyday activity for everyone
+ Common experience
+ Social activity
– Somewhat hard to measure (taste)·
Privacy issue
– 9 a clock a front of TV
+ You could have a positive influence on
what people are eating
+ Not yet IT-polluted
+ Many social navigation possibilities
Cleaning
Reading
Dressing
Sleeping
Public Space Events
Atmosphere detection, estimation/
evaluations/feedback of queues, restaurants, etc
+ Spread load
– Segregation
+ Quality effects
– No spontaneity
– Less development and considerations
– Unwanted effects
– Standardisation
Down town - cheapest prices, choice of
place to go, e.g. restaurant
+ Winning time
– PDA is needed
+ Individualised
– Unwanted effects
+ Effective use of resources
– Standardisation
+ Quality effects
+ Experience/Event
Auctions
+ Faster
– Destroys the event
+ Better price
– Too fast
– Whom does it benefit?
Campus/Nursing home/Offices
+ Effective use of resources
– Integrity
+ Experience/Event
– Stress
+ Safety
+ Humanity
Public spaces/exhibitions/waiting room/
squares
Shopping areas
Pubs
Libraries
+ Big diversity of people
– Privacy
+ Opportunity to make new acquaintances
– The will to carry the sensors
+ Neutral (nobody owns the territory)
– Dangerous to loose the control of the
system
+ Not common intention
– Unclear who should have the control
Appendix A – Ideas on EI-applications
73
Parties
+ Common intentional
– Drunk people might ruin the equipment
(puke warning)
Parking place
+ Effective use of resources
– Boring
+ Environmental
– Wrong target group
– Small target group
– Competition problems
Professional Events
Dissertation
Meetings
Farming
Problem solving
Product development/design/factory
floor
+ Effective use of resources
– Integrity
+ Experience/event
– Stress
+ Safety
+ Humanity
AL forest simulation (distributed VR)
+ Creates knowledge about forests
– No emergent interaction, or?
+ Easy to collect data
+ Possible to speed up time
Empathy training/development
+ Solves the lack of empathy in society
– Privacy issues
+ Focused on human needs
– Hard to interpret data
+ Easy to measure data
+ Easy to create adrenalin shocks
Political Events
War
Riots
Gangs, Groups
+ Control
– Mobbing
+ Surveillance
– Crowds
+ Less violence
– Injustice
+ Organisation
Demonstrations, Police actions
+ Democracy
– More violence
+ Economy
– Escalation
+ Right equipment
– No surprises
+ Easy to measure
– Security problems
+ Everybody
– Does it work, is the result a better
democracy?
Avoid/track/see crime
Demonstrations
Love-peace-and-understanding
IT-democracy
Simulation of economical systems
74
Appendix A – Ideas on EI-applications
Communication Events
Car-pooling
Subway - Where should I stand to find a
place to sit
+ Effective use of resources
– Computational problems·
+ Environmental
– Stress
+ Humanity
– Security
+ Huge population
– Not in Umeå
+ Repeatable
– People wants to be alone
+ Possible to compare groups in similar
situation
– Interference
Tourism/Round trips/guiding
Charter
Silent communities/bus/ train
+ Nothing else happening
+ No way to escape
Traffic -Affect other drivers, traffic
flows, emergency vehicle
+ ...of advantage to society
Extended telephone/video conference
- Move to a new context, virtual
environments/meetings, meet new
people
+ Democracy
– Boring, grey
+ Commitment
– Demands capacity
+ Distance spanning
– Not something that is new.
– Too big
+ Easy to find money for
+ Economy
Arena Events
Theatre
+ Closed area/local
– Demands that you engage in the play
+ The public (as paying) allows to decide
more
– Does it have any positive effect?
+ Can create more interaction
– Huge demands on the actors
Sports arenas/ Track and field/down
hill/orienteering
Formula 1
+ Money
– Expensive system
+ It would help the drivers, the teams at
the pit stops
– Secrecy
+ Few events
– Does it already exist?
Festival - Where is it best?Where is it
most crowded?
+ Individualised
– Very few events
Concerts
+ Enhances experience
– We don’t want to choose
+ The right songs
– No new songs
+ Fewer extra tracks
– Dependent of the audience
+ Less tomatoes thrown
Survivor like programs/shows. (Docy
soap) - Switch context, connects existing shows
+ Commercial interests
– Difficult industry ( TV )
+ Hot
– Expensive prototype
+ Everyone is a participants, 24-7.
– Loads of technique.
+ Collaboration with (Strix)
Film/Movie
Net Work Games
Top charts
Appendix A – Ideas on EI-applications
“City battle”++
+ Already based on a on interaction
– Once a year event
– Whom profits?
Create Collaborative art
games/competitions
+ Experience/event
– Just a game
+ Fun
+ Humanity
Pokemon, DigiMon, DigiBird applications.
+ Enormous market
– Difficult to understand the market
+ Easy to find test pilots
– How to charge?
+ Playfulness
– What is new?
+ Easy to please
+ Many existing concepts to expand
+ Tokyo as a lab (DoCoMo)
+ Brainstorm with children/youths
Sound/Voice controlled cameras monitoring audience reactions. The sound
level is collected among the audience
and a server calculate where there
is most activity and the camera is
directed towards those people. The
image can be presented on a big
screen TV.
Art happenings - Exploring new ways to
express art and to make art happen in
real time
+ Maybe a growing area
·
Community Events
Communities, what’s happening
+ Individualised
– Where to find the people
– What do they have in common?
Religion/ New age
Social life flirt, etc
Instant Communities - create groups/
communities (instantly) whenever
people get together
+ The group could later on be used
to send out information, requests, and
reminders.
What/Who is hot? (ICQ, Communities)
- Non-pleasure situations (Is there
a doctor present?), search criteria’s,
opposite attraction
+ New
– Hard to get started
+ Cool
– Critical mass
+ Business and pleasure
– What terminals to use?
+ Young market
– Uniform
+ Groups could be created afterwards
from logged data (who was there and
personal profiles) when a need is identified.
+ Scalable
Community building/hobbies
Hunting
Agriculture
Gardening
75
76
Appendix B – Focus Area Map
Appendix B - Focus Area Map
Section in the report
Application areas
Categories and characteristics
Communication
Communities
Computability Aspects
Data Collection
Democratic and Undemocratic systems
Feedback
Model
Physical-Virtual Systems
Presentation and Interaction
Sociological Aspects
Control Systems
Scenarios
Security
Simulation
System Architecture
System Awareness
Timing
Traffic Patterns
User Awareness
Data, Info and Knowledge
Sociolgical Aspects
Technical System Aspects
Focus Areas
Interaction
Unclear
Applications
Relevant
EI Scenarios
High relevance
Emergent Interaction
Main topic
Appendix C – Collaborative Art
77
Appendix C - Collaborative Art
The basic idea with this application is that a collective (which may be distributed
over a wide area) will produce art together. The work of art, for instance a picture,
will emerge from the behaviour of the members of the collective, using the work
of art itself as the feedback. (Alternatively, one might choose to see the behaviours
and behaviour patterns as the real work of art, like a performance or a happening.)
Different groups control different aspects or parts of the work of art. The group
concept is very broad. For instance, groups can be defined spatially, logically, etc.
UMEÅ
OBS
BJÖRNVÄGEN
DOWN-TOWN
STRÖMPILEN
JFIE JREFJ OS
JGIJG AOPE
AÄIOJ AG
Figure 15. A naive example of collective art, with some graphics and
message displays.
Figure 15 exemplifies the idea of collaborative art. Four major commercial areas
of the city of Umeå define the groups. Each group controls one part of an image
of a human body. The behaviour in each group (perhaps normalised with respect
to group size, etc.) can determine which part of the body a group controls and
the shape of that part. The size of the controlled parts can also be determined in
a similar way. Another variant is to randomly associate a part of the body to a
particular group.
This work of art also includes some “text displays”. These can be used for commercial purposes, to control the flow, or to generate collaborative poetry or stories
compiled and edited from SMS messages contributed by the actors.
It is possible to play with the democracy dimension in this application by
varying the actor’s impact on the feedback, triggered by quite specific individual
actions. E.g., a person that has just bought a pair of shoes could be rewarded with
total control over the shoe-part for the nearest fifteen minutes. One could have
a lottery as part of this application, where the participants “get” lottery tickets
simply by being in the region for the application.
Technical aspects: the application could use large public displays in each area;
given 3G mobile phones, they could be used as personal displays; also RDS-radio
messages could be used to distribute feedback. The application is scalable, both
in the number of participant, and from a technical perspective with the introduction of new technologies. Genetic algorithms can be used to generate the appearance of each part of the image. Shannon’s theories (Shannon, 1948) can be used
to generate poetry and stories from the SMS flow, similar to how the “Shannonizer” (Shannonteam, 2002) transforms a given text into a “Shakespeare text”. Also
other algorithms could be used to compute textual feedback, e.g. genetic algorithms, or LSA together with text summary algorithms.
78
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