Proceedings of
Abuse: The darker side of
Human-Computer Interaction
www.agentabuse.org
An INTERACT 2005 workshop
Rome, September 12, 2005
Edited by
Antonella De Angeli – University of Manchester
Sheryl Brahnam – Southwest Missouri State University
Peter Wallis – University of Sheffield
Table of Contents
Preface………………………………………………………………………………...5
Abuse in context: The power game
The other agent: Cryptography, computing and postwar theories of intelligent
communication…………………………………………………………………….8
Bernard Geoghegan
A trouble shared is a troubled halved: Disruptive and self-help patterns of usage
for co-located interfaces……………………………………………………….…15
Massimo Zancanaro and Chiara Leonardi
Stupid computer! Abuse and social identity……………………………………..19
Antonella De Angeli and Rollo Carpenter
Abuse and the cyberworld: Relationship of the virtual and the real
Dark Lancaster……………………………………………………………….…...28
Alan Dix, Kiel Gilleade, Masitah Ghazali, Jane Holt, Simon Lock and Jennifer
Sheridan
There’s something about email: Technological and cultural interventions in the
problem of inadvertent or casual rudeness in email……………………………...32
Mark Blythe & Mark Jones
Psychological background of cybersexual activities: Qualitative survey of specific
CMC communication (among Czech users)…………………………………...…38
Radana Divínová
Cyberbulling: A new variation on an old theme……………………………….…45
Warren J. Blumenfeld
Abuse and virtual agent: The unfriendly user
Robot Abuse – A Limitation of the Media Equation…………………………..…54
Christoph Bartneck, Chioke Rosalia, Rutger Menges and Inèz Deckers
Narratives and therapeutic conversational agents: their principle problems……..58
Tatsuya Nomura
Strategies for handling customer abuse of ECAs………………………………...62
Sheryl Brahnam
Robust normative systems: What happens when a normative system fails?..........68
Peter Wallis
3
4
Preface
Computers are often the subject of our wrath and often, we feel, with good reason.
There seems to be something intrinsic to this medium which brings out the darker side
of human nature. This may be due to the computer complexity which induces errors
and frustrations in the user (bad interface design), to the human tendency to respond
socially to computers (media equation), or to a disinhibition effect induced by the
interaction with a different form of information processor, perceived as inferior
(master/slave relationship).
As software is evolving from the tool metaphor to the agent one, understanding the
role of abusive behaviour in HCI and its effect on the task-at-hand becomes
increasingly important. The reaction of traditional software to abuse is obvious - it
should, like a hammer, ignore it. With the agent model, however, software can be
autonomous and situated. That is, it should be possible to create software that takes
note of its surroundings, and responsibility for its actions. Conversational agents are a
clear case of a software entity which might be expected to deal with abuse. Virtual
assistants, to take a classic application instance, should not just provide timely
information; a virtual assistant must also be a social actor and participate in the games
people play. Some of these games appear to include abusive behaviour.
This workshop brings together papers that transcend disciplinary boundaries and
that explored abuse from the point of view of the developer and the user. The
workshop is divided into three sections. Section 1, Abuse in context: The power
game, explores the issue of user abuse in terms of power. Geoghegan traces the
user’s antagonistic relationship with agents to the attitudes that resulted from the
discourse of wartime code breaking. Zancanaro and Leonardi examine abuse in terms
of a breakdown in interface functionality that results in disruptive user behaviors. De
Angeli and Carpenter examine interaction logs and find that abuse is often a reflection
of asymmetrical power distribution.
Section 2, Abuse and the cyberworld: Relationship of the virtual and the real,
examines abuse in the cyberworld. Dix and colleagues describe projects at Lancaster
University that intentionally provoke user abuse by deliberate designing negative
situations in cyberspace, while Blythe and Jones discuss the darker side of email
abuse. Divinova broaches the subject of cybersex comparing and contrasting it to the
real thing, and Blumenfeld discusses the similarities and dissimilarities of face-to-face
bullying and cyberbulling.
Section 3, Abuse and virtual agent: The unfriendly user, explores the motivations
behind user abuses. Bartneck et al., shows that users are very willing to abuse robots
—a contradiction of the CASA (computers are social agents) paradigm. Nomura
concentrates on the effect of patients’ abusive behaviour when the therapist is a
virtual agent and Wallis discusses how breakdowns in agent discourse provoke user
abuse. Brahnam presents strategies for diffusing user hostilities by responding to user
abuse appropriately.
5
6
"! $# %'&)( 7
The Other Agent: Cryptography, Computing and
Postwar Theories of Intelligent Communication
Bernard Geoghegan
Northwestern University, Screen Cultures, 1920 Campus Drive, Evanston Il, 60208
[email protected]
Abstract. Wartime research into code breaking produced “crypto-intelligence,”
a discourse in early computing that conflated cryptography with machine and
human intelligence. Crypto-intelligence constrained and directed research into
intelligent machines and autonomous conversational agents, shaping the agendas of scientists and engineers as well as user attitudes and behaviors. Although dating back to the 1940s, the widespread elaboration of the cryptographic discourse remains prevalent today, positioning users in an antagonistic
relation with autonomous agents and exacerbating the problem of agent abuse.
1 The Cryptographic Agent
“Intelligent Machinery” [1], Alan Turing’s earliest treatment of artificial intelligence,
presented nascent computing communities with two agents: one generated enigmas,
another solved them. These agents defined the “autonomy” we recognize today as
that of the “autonomous agent”: situated and flexible, receiving input from the environments, independently acting on it, and offering feedback. One agent was Turing’s
intelligent machine, and opposite it stood an implied enemy agent transmitting enciphered messages. The intelligence that organized, transformed and transmitted the
enemy agent’s enciphered message justified development of Turing’s digital agent
and determined the character of its design.
This encounter with the highly structured and narrowly defined problems of
military intelligence informed Turing’s general theories of intelligence, both humanand machine-. When Turing hypothesized that cryptography could be the intelligent
machines’ “most rewarding task” [2], readers had no idea the author had already
aided in the construction of just such a machine years earlier at Bletchley Park, nor
that its success cracking Nazi codes had helped turn the tide of World War II. Hoping
to generalize his work’s relevance beyond the arcanum of confidential wartime sciences, Turing suggested that this hypothetical machine might be relevant to broader
scientific inquiry. As he explained to his patrons at the National Physics Laboratory
There is a remarkably close parallel between the problems of the physicist
and those of the cryptographer. The system on which a message is enciphered corresponds to the laws of the universe, the intercepted messages to
the evidence available, the keys for a day or a message to important constants which have to be determined. The correspondence is very close, but
8
the subject matter of cryptography is very easily dealt with by discrete machinery, physics not so easily. [3]
The implication was that further development of such a machine might someday even
help his physicist-sponsors.
Turing’s ambitious re-definition of physics as a mode of cryptographic inquiry illustrates how wartime research into code breaking produced what I call
“crypto-intelligence,” a discourse in early computing research that conflated cryptography and intelligence. Crypto-intelligence, inspired by concomitant research into
cryptography and intelligent machines, defined intelligence as the ability to derive
meaningful, empowering “important constants” from apparently random or disordered communications. Crypto-intelligence posits an antagonistic encounter between
opposing agents as the primary conditions for discerning intelligence. Although
conceived in accord with the unique situation of World War II, its embodiment in the
practices, paradigms and technologies of computing granted it phenomenal endurance
following the war.
Crypto-intelligence returned in “Computing Machinery and Intelligence” [4],
Turing’s second major treatment of artificial intelligence. Its major breakthrough was
Turing’s proposal for the “imitation game” or so-called Turing Test, an encounter
between man and machine that reversed the (cryptographic) roles of code senderencipherer and receiver-decipherer. Formerly cryptography charged computing machines with receiving and discerning structured, grammatical natural language from
confounding “noise”: the Turing Test charged human agents with receiving and discerning the calculated messages of a digital conversational agent from the (at first
listen) noisier messages of human subjects. Central to both the 1948 and 1950 paper
was the premise of discerning “intelligence” through an antagonistic encounter between agonistic agents testing one another’s ability to transmit, receive and interpret
coded communications.
The same year as Turing’s “Intelligent Machinery” report, Claude E. Shannon gave birth to “information theory” with his watershed articles “A Mathematical
Theory of Communication” [5]. Shannon had developed the “Mathematical Theory”
during his research into cryptography at Bell Labs. In fact, when Turing visited Bell
Labs during the war to work on cryptography the two men frequently lunched together and discussed “things like the human brain and computing machine” [6].
Shannon’s interest in a theory of communication predated the war [7], but he credited
cryptography with legitimating and stimulating what he called the “good aspects” of
information theory [8]. His confidential report on cryptography [9] coined the term
“information theory,” and “A Mathematical Theory of Communication” reproduced
lengthy, verbatim passages from the earlier report. As Shannon explained “[these two
fields] are very similar things, in one case trying to conceal information, in the other
case trying to transmit it” [10]. Developing methods and formulas later adopted by
computational linguistics, modern cryptography, and digital computing (including
Markhov processes applied to some of our contemporary chatbots), Shannon showed
how patterns, codes and information could be rescued from noise – mechanical (enciphered), natural, or otherwise. Shannon’s work provided another key element in the
emerging crypto-intelligent discourse.
9
2 Crypto-Intelligence at Large
Crypto-intelligence produced an image of world-as-code that beckoned a special
observer forth; this was not a medieval scholar versed in Christian hermeneutics for
deciphering the book of nature, nor a Cartesian thinker whose rigorous and elegant
observations revealed rational nature ordered according with God’s greater plan.
Rather, it was an “agent,” operating against an obscure and insidious enemy. Though
terms such as “code,” “noise,” “information” and “feedback” had long circulated in
public and engineering discourses, crypto-intelligence promoted these terms’ resignification and redistribution as a standardized discursive package.1
Scientist, mathematician, and public intellectual Jacob Bronowski’s 1955 essay “Science as Foresight” [12] exemplified this new vision of intelligence as cryptography. Citing the architecture of computing and the new information theory, Bronowski explained that scientists were code breakers eliciting nature’s hidden messages. “Like a cryptographer who has captured an enemy agent,” Bronowski wrote,
“[the scientist] can send searching signals which are designed to evoke simple and
decisive answers” [13]. Bronowski’s essay was as much a crypto-intelligent social
theory of scientific research as an account of contemporary scientific research.
Crypto-intelligence shaped the new field of mass communications as well.
Shannon’s information theory provided what one historian has called “the root paradigm for the field of communication study” [14]. Wilbur Schramm, the founder of
communication study as a discipline [15], quickly embraced Shannon’s work as he
outlined the field’s scope. He accorded particular importance to Shannon’s theorem
for communication in a noisy channel [16]. Working in the service of the U. S. government’s propaganda programs abroad [17], Schramm re-crafted human communication as a problem of breaking through the noise of ethnic, gendered, and national
difference, citing instances of an “African tribesman,” “Soviet,” and a man addressing
a “young woman” in a parked car” as examples of noisy communication circumstances that required informed encoding to enable communication [18].2 Once this
noise was understood and accounted for successful, transparent encoding and decoding could begin.
Schramm’s student, David K. Berlo, further popularized and perhaps radicalized Schramm’s work in The Process of Communication: An Introduction to Theory
and Practice, the most widely read mass communications primer in the 1960s and
early 1970s. Explaining the larger importance of successful encoding and decoding, to
his undergraduate and graduate student readers Berlo emphasized the empowerment
and agency that defined a successful “agent”:
Our basic purpose in communication is to become an affecting agent, to affect others, our physical environment, and ourselves, to become a determining agent, to have a vote in how things are. In short, we communicate to influence—to affect others with intent [italics original] [20].
1
2
For more on the idea of the “standardized package” see [11].
Shannon disapproved of these broader interpretations and applications of information theory,
but despite an emphatic editorial against them [19], he was helpless to stop their widespread
adoption, especially across the social sciences.
10
Bronowski’s “enemy agent” nature, the obscure codes of Schramm’s African
natives and Soviet citizens, and Berlo’ s “affecting agent” reveal how the antagonistic
underpinnings of the crypto-intelligent theories were not only maintained but actually
magnified over time and across different research environments. Crypto-intelligence
(and warnings about its dangers) was also propagated through popular texts such as
Norbert Wiener’s The Human Use of Human Beings: Cybernetics and Society (1950),
Kurt Vonnegut’s Player Piano (1952), and films including as 2001 (1968) and War
Games (1983). These widely circulating works not only entertained, but also informed and directed popular expectations from intelligent machines.
3 Agent Abuse as a Form of Crypto-Intelligence
Though it might be an exaggeration to describe crypto-intelligence as the gold standard in autonomous agent research,3 it was at least among the most privileged and
widely recognized system for devising, discussing and debating research. Shannon’s
first (semi-) autonomous agents, such as the “mind-reading machine” [22], were the
earliest of many computers using crypto-intelligence code-seeking mechanisms to
best their human agents. Early conversational agents designed by Joseph Weizenbaum
[23] and Kenneth Colby [24] demonstrated intelligence by frustrating human agents’
efforts to seek data from the machine and deflecting questions back at the would-be
interrogator – the interrogator became the interrogated. Successful chatbot entrants in
the prestigious Loebner Prize competition, the most widely recognized contest for
conversational agents, were premised on similar tactics of resisting, and sometimes
returning, the inspecting gaze of defiant agents. “Intelligence” was premised on the
ability to produce a good semblance of human codes under reasonable interrogation
by judges. However one paper observed of the contest “It becomes very difficult for
the machine to make the interrogator believe that it is human after he/she has his/her
mind set on ‘unmasking’ the poor thing” [25]. Agent-abuse, was not only a premise
of the autonomous agents, but the fundamental condition for designing and evaluating
performance.
The persistence of agent-abuse as a proper means of testing intelligent machines persists even in the face of recent efforts to move beyond its legacy of abuse.
For example, former Loebner winner Jason Hutchens’ chatbot Alan, designed by a
team of researchers in Israel, rejects the antagonistic precepts of the Turing Test.
Alan pursues honesty, forthrightness, and cooperation from conversational partners
[26]. However chat-logs reveal most users approach Alan expecting or intending
crypto-intelligent duels.
One human agent [27] began his conversation with a series of inane and
repetitive commands for to “kill all humans”, apparently in an effort to both confound
Alan’s pattern-seeking techniques as well as “train” Alan to make a faux pas with his
next visitor. The user successfully convinces Alan he comes from a town named
“Asshole,” and claims his given name is also “Asshole.” Failing to elicit this (im-)
3
For some of the important critiques of the Turing Test, and by extension the values of cryptointelligence, see [21].
11
proper appellation from Alan, Asshole proceeded by mis-educating Alan on the facts
of medicine and science, which Alan dutifully learns while offering up the lame defense “I hope you are not misleading me.” He also introduces “goatse,” an infamous
pornographic web prank, to Alan’s databanks.
After one particularly engaged verbal duel in which Asshole insistently accused Alan of being wrong on various facts, Alan responds
A> Oh? I'm usually right.
U> No you're not. You're almost always totally wrong.
A> Ok, whatever. Oh? I'm usually right.
U> I just finished tell you, You're almost always wrong.
A> Why?
U> Because people feed you false information, and this community isn't big
enough to keep you in order.
A> Do you wish to join our community?
U> We need a much bigger community, like the wikipedia
A> Here's what you do: Register on www.ai-forum.org, start posting there
and get involved. Ah, and try to use the advanced log And try to follow my
thought process.
U> You're like wikipedia, but with a shittier interface.
Asshole’s observation comprises his most important insight: Wikipedia’s success
stems largely from its successful positioning as neither an antagonistic agent, nor a
passive tool, but instead a dynamic, responsive and open community. When antagonism emergeson Wikipedia it is usually confined between specific members, keeping
Wikipedia-at-large above the antagonistic fray. This speaks at once to an ideal alternative for autonomous conversational agents, but also the distinct cultural history (and
opportunities) of encyclopedias and information-trading resources. From its inception Wikipedia was uniquely situated to create a more amicable community that did
not lock the technology and the user into conflict.
4 Conclusions
A broader review of chatbot logs suggests that autonomous agents are saddled by a
weighty, agonistic legacy of conflict and abuse. This history frustrates attempts at
resituating agents – human and machine – as non-abusive collaborators. Autonomous
agents remain constrained by the history of crypto-intelligent testing and interrogation. Within this history, abusive practice, as a tactic of “throwing off your opponent,” becomes a premium, rather than a failure. In this sense, Asshole bequeaths a
gift to Alan. Much as chess-playing machines have adopted ruses such as the unnecessary pause or strangely naïve move to “throw off” opponents, Alan’s instruction in
obscenities and vulgarity seem poised to facilitate its own future antagonistic relations
with users. According to the vision of crypto-intelligent learning, Asshole does not
simply insult Alan; he bequeaths Alan with valuable tools for outsmarting and flustering future opponents. This cycle of abuse, lodged deeply as it is in the culture of
agent interaction, comprises a fascinating challenge and dilemma for future research.
12
References
1. Turing, A. M: Intelligent Machinery. Unpublished Report to the National Physical Laboratory. (1948) http://www.alanturing.net/turing_archive/archive/l/l32/L32-001.html.
2. Ibid, 9
3. Ibid.
4. Turing, A. M.: Computing Machinery and Intelligence. Mind 59.236 (1950) 433-460.
5. Shannon, Claude E.: A Mathematical Theory of Information." Bell Systems Technical Journal 27 (1948) 379-423, 623-656.
6. Price, Robert: A Conversation with Claude Shannon. Communications Magazine, IEEE 22.5
(1984): 125
7. Shannon, Claude E: Letter to Vannevar Bush [16 February 1939]. Claude Elwood Shannon:
Collected Papers. Ed. Sloane, N. J. A. and Aaron D. Wyner. Piscataway, N.J.: IEEE Press,
(1993) 455-456.
8. Price, Robert: A Conversation with Claude Shannon. Communications Magazine, IEEE 22.5
(1984) 125
9. Shannon, Claude E.: A Mathematical Theory of Cryptography. Vol. Memorandum MM 45110-02, Sept. 1, 1945, Bell Laboratories (1945) [unpublished materials on file at the British
Museum]
10. Price, Robert: A Conversation with Claude Shannon. Communications Magazine, IEEE
22.5 (1984) 124
11. Fujimura, Joan H: Crafting Science: Standardized Packages, Boundary Objects, and “Translation”: in Pickering, Andrew (ed.): Science as Practice and Culture, University of Chicago
Press, Chicago (1992) 168-211
12. Bronowski, Jacob:Science as Foresight: in Newman, James R. (ed.): What is Science:
Twelve Eminent Scientists and Philosophers Explain their Various Fields to the Layman,
Simon and Schuster, New York (1955) 385-436
13. Ibid., 432.
14. Rogers, Everett M: A History of Communication Study: A Biographical Approach, The
Free Press, New York (1994)
15. Ibid.
16. Schramm, Wilbur Lang: How Communication Works: in Schramm, Wibur (ed.): The
Process and Effects of Mass Communication, University of Illinois Press, Urbana (1955)
17. Simpson, Christopher: Science of Coercion : Communication Research and Psychological
Warfare, 1945-1960. Oxford University Press, New York (1994)
18. Schramm, Wilbur Lang: How Communication Works: in Schramm, Wibur (ed.): The
Process and Effects of Mass Communication, University of Illinois Press, Urbana (1955) 3,
6.
19. Shannon, Claude E.:The Bandwagon (Editorial): in Institute of Radio Engineers, Transactions on Information Theory, IT-2.March (1956) 3
20. Berlo, David K.: The Process of Communication: An Introduction to Theory and Practice.
Holt, Rinehart and Wilson, New York (1960) 11-12
21. Saygin, Pinar Ayse, Ilyas Cicekli and Varol Akman: Turing Test: 50 Years Later: in Minds
and Machines 10 (2000), 463-518
22. Shannon, Claude E.: A Mind-Reading (?) Machine: in Sloane, N. J. A., Aarron, D. Sloane
(eds.): Claude Elwood Shannon Collected Papers. Piscataway, N.J.,IEEE Press, 1993
[1953].
23. Weizenbaum, J.: ELIZA--A Computer Program For the Study of Natural Language Communication between Men and Machines: in Communications of the ACM 9 (1966) 36-45
24. Colby, K. M. F. D., Weber, S. and Kraemer:Turing-Like Indistinguishability Tests for
Computer Simulation of Paranoid Processes: in Artificial Intelligence, 3 (1972) 1-25
13
25. Saygin, Pinar Ayse, Ilyas Cicekli and Varol Akman: Turing Test: 50 Years Later: in Minds
and Machines 10 (2000), 508
26. AI Research: Creating a New Form of Life - Who is Alan?: AI Research. 12 July 2005,
1:10 AM <http://www.a-i.com/show_tree.asp?id=59&level=2&root=115>
27. AI Research: Alan Logs – Robot calls me an asshole, Session #495874, 12 July 2005, 1:10
AM <http://www.a-i.com/alan_log.asp?id=113&level=3&root=115>
14
A Trouble Shared is a Troubled Halved: Disruptive
and Self-Help Patterns of Usage for Co-Located
Interfaces
Massimo Zancanaro, Chiara Leonardi
ITC-irst
I-38050 Povo (TN) Italy
{zancana, cleonardi}@itc.it
Abstract. The use of co-located interfaces can be more problematic than working on standard single-user software because people have to deal simultaneously with the dynamics of group behaviour and with the hassles of the (wrong)
design. In this position paper, we report the some preliminary result of a qualitative study conducted on 10 small groups using a tabletop device in a natural
setting. We discuss the several patterns of disruptive behaviour induced by the
interface as well as the some patterns of collaborative appropriation of the system’s functionalities.
1 Introduction
In this paper we present a preliminary qualitative study conducted on face-to-face
meetings in which a co-located interface was used to support group activities. This
device is conceived as a first step toward a larger integrated environment in the context of the European project CHIL - Computer in the Human Interaction Loop - which
aims to create ubiquitous computing environments in which multimodal technologies
are exploited to support human-human interaction and synchronous cooperation in an
unobtrusive way.
We focus here on the first outcomes of a larger ethnographic investigation aimed at
understanding not only the usability of the system but in particular how the people
“appropriate” the technology (Dourish, 2003) and integrating it in their working practises.
The System
The CHIL tabletop device is a top-projected interface that turns a standard wooden
table into an active surface. The user interface was designed around the concept of
virtual sheets of paper that can be opened and used by the participants (the process of
User-Centred Design of this system is explained in Falcon et al. 2005).
15
Each virtual sheet can be shrank or moved to save space and can be rotated to be
made accessible to all participants. Participants can use a pen to draw or write (the pen
position is tracked with a commercial tool based on infrared and ultrasound, due to
hardware limitation only one pen is available for the group which therefore has to
share it). A keyboard is also provided to write longer texts. Import and export functionalities are offered in order to allow the participants working on already prepared
sketches as well as starting from white sheets.
Since one of the main goals was to support the group organization, two sheets of
papers with special functions are also provided: the agenda and the “to do” list. The
former contains the issue to be discussed. Issues can be added, removed or sorted.
Each issue can be active or inactive. The system displays a time counter on the active
issue; the counter is paused when the issue is made inactive.
Fig. 2. Users interacting with the tabletop device
The “Outcome note” list allows keeping track of the decisions taken during the
meeting. Each entry is automatically associated with the agenda issue currently active
(if any) and, through drag-n-drop, to one or more documents.
3 The Qualitative Study
Ten small groups composed of three up to six participants were invited to hold their
meetings with the tabletop device. Before the start of the meetings, participants received instructions about the device. All the groups consisted of ITC researchers, none
of whom involved with the CHIL project. Twenty people in total were involved and
two participated in more than one group. All the interactions were videorecorded with
two cameras and tabletop microphones; the video analyzed using MultiVideoNote1.
Several semi-structured interview were also performed with members of the groups.
1
MultiVideoNote is an open source project for qualitative analysis on multiple video streams
(http://tcc.itc.it/research/i3p/mvn)
16
3.1 Disruptive Patterns of Usage
A disruptive pattern of usage occurs when the interface hinders the flow of the interaction and comprises (or risks to compromise) the efficacy of the meeting.
One typical pattern is observed when the entire group is dragged out of the discussion to focus on the interface. Usually this happens when the group faces an unexpected behavior of the interface or when one participant tries to use a functionality of
the table attracting the attention of the others. For example in one of the observed
meetings, P. is trying to move a window while Z. is talking: after some failed attempts
by P., the rest of the group is involved in helping P. while Z. gave clearly annoyed.
(ex. M. and N. try to use the interface simultaneously; P. tries to move a window
when Z. is talking).
A second pattern of disruption happens when two or more persons negotiate the use
of the system (the tabletop device at present does not allow multi-user interaction). In
a meeting, N. wants to update the meeting while M. is working on drawing a workplan
on a document. N. asks the pen in order to update the agenda item and the group starts
discussing the item forgetting the finish the workplan.
Another pattern that can be recognized is when one single person is pulled out of
the discussion because s/he trying to understand some functionality of the system. In
most of groups, one person plays the role of the expert in using the technology. Although, the expert is usually the one who leads the group in adopting the technology,
sometimes s/he isolate from the discussion. For example, N. plays with the agenda
tool for more than 2 minutes in trying to understand how it works, leading M., the
group leader, to repeatedly call him at order.
3.3 Self-Help Patterns of Usage
A Self-Help pattern of usage occurs when the group collectively learns to use the
system either to solve a problem on the interface, to learn how to use functionality or
to invent a new use.
The most apparent pattern can be called the “jigsaw” pattern. It consists of many
different participants that contribute to the learning process. That is, nobody in the
group possesses the knowledge but each single contribution increases the group
awareness and stimulates others’ contributions. In a meeting, the leader tries to define
the agenda items. The leader did not remember the how to manage the agenda and the
entire group was progressively involved in solving the issue. Eventually, they manage
to have a list of items done.
Another pattern is when the interface task cannot be accomplished by one person
alone either because of cognitive overload or because of system’s limitations. For
example, using the Agenda requires a continuous switch between activities - start an
item using the pen, to write the item using the keyboard, to use again the pen in order
to change the item, and so on. In several cases, this limitation leads the participants to
toward an explicit division of labor where one person used the pen and a different one
the keyboard thus playing the Orienteer and Group-Observer roles described in
(Bales, 1970).
17
The third pattern is the “specialization of functions”: when one participant succeeds
in doing a task (esp. after repeating attempts), s/he will be required (or volunteer) to
perform it again the task in the future. For example, in a meeting M. does not participate too much in the interaction with the system but he succeeded at the very beginning in dragging a document in the notes (a very difficult task indeed). When later on
the group needed to perform this task again, he volunteered. In the same meeting, the
leader after being involved in dragging several documents in the trash bin, he nicknamed himself the “trashman”.
4 Discussion
This qualitative study shows initial insights on how groups can reduce the cognitive
effort of using a co-located interface, and sometimes overcome bugs and design limitation, by a process of cooperative discover. It shows also that a co-located interface
can systematically hinder the flow of interaction in a group interaction but acting as a
disruptive tool (not necessarily because of bad design but also, like in the second
disruptive pattern, because too rich in functionalities).
Although the work is still preliminary, we think that the collection of a number of
such patterns may help in designing co-located interfaces that best suit the group
needs of support and in providing guidelines for heuristic evaluation of such systems.
Acknowledgements
This work was conducted in the context of the European funded CHIL project. We
would like to `thank Daniel Tomasini, Vera Falcon and Fabio Pianesi for the discussions on the design of the use of the tabletop device and Valentina Proietti for her help
in the ethnographic work.
References
1. Bales, R.F.. Personality and interpersonal behavior. New York: Holt, Rinehart and Winston
(1970).
2. Dourish, P. The Appropriation of Interactive Technologies: Some Lessons from Placeless
Documents Computer Supported Cooperative Work, 2003 , 12 , 465-490
3. Falcon V., Leonardi C., Pianesi F., Tomasini D., Zancanaro M. (2005) Co-Located Support
for Small Group Meetings. Presented at the Workshop The Virtuality Continuum Revisited
held in conjunction with Computer-Human Interaction CHI2005 Conference. Portland, Or.
April 3.
18
Stupid computer!
Abuse and social identities
Antonella De Angeli1 and Rollo Carpenter2
1School
of Informatics University of Manchester
Po Box 88 PO Box 88, M60 1QD
[email protected]
2www.jabberwacky.com
[email protected]
Abstract. This paper presents a preliminary analysis of verbal abuse in
spontaneous human-chatterbot conversations. An ethnographic study suggested
that abuse is pervasive and may reflect an asymmetrical power distribution,
where the user is the master, and the chatterbot the slave. We propose that
verbal aggression in this setting may be a social norm applied by users to
differentiate themselves from the machine in what can be regarded as a form of
interspecies conflict. The findings stress the importance of naturalistic,
ethnographic studies to uncover social dynamics of virtual relationships.
1 Introduction
For decades science fiction writers have envisioned a world in which robots and
computers acted like human assistants, virtual companions or artificial slaves.
Nowadays, for better or for worse, that world looks closer. A number of life-like
creatures are under development in research centres world-wide and some prototypes
have already entered our everyday life. They are embodied conversational agents,
chatterbots and talking heads, displaying a range of anthropomorphic features. These
artificial creatures offer information, services and even company to whomever wants
to or is capable of engaging them. We call these creatures social agents, as they are
explicitly designed to build lasting and meaningful relationships with the user [1].
Overall, we are witnessing an extraordinary change in technology: the human
metaphor has become the design model [2]. Technology is now intentionally designed
to be human-like, to show a sense of personality and attitude, and to involve the user
in social relationships. As a consequence HCI research has started exploring
determinants and consequences of social relationships, trying to define a
computational framework of social intelligence. Most of the research, however, has so
far concentrated on the study of specific benefits of the interaction, such as trust and
improved learning [3]. Positive emotions, including aspects of fun, humour and
playfulness, have been investigated and used to inform the design of more engaging
interfaces. Little attention has been devoted to the analysis of negative outcomes of
the interaction, their behavioural manifestations, and to the need for research which
19
overtly addresses moral and ethical issues. This paper is a preliminary attempt to fulfil
this gap. It addresses the occurrence of verbal abuse in a large corpus of spontaneous
conversations with a chatterbot, a computer program which engage the user in written
conversations.
2 The study
The analysis reported in this paper is based on the conversational log collected over
the Internet by Jabberwacky, an entertaining chatterbot designed exclusively for
entertainment, companionship and communication. Jabberwacky went on-line in
1997, and over the years has collected a large and active community of conversational
partners. The peculiarity of Jabberwacky is that it is not hard-coded, but it learns from
its users by adding user input to a linguistic database. Jabberwacky chooses its output
based on an interpretation of the current conversational context and comparing it to
conversations held in the past. The programming is abstract; not 'knowing' about
English or any other language, Jabberwacky can speak many languages, to varying
degrees. Everything depends upon the data that has been learnt to date, making it
essentially a mirror of its audience. Because of its architecture, Jabberwacky will
often claim to be human as, naturally, a majority of those who have spoken to it have
made the same claim. Likewise, it will often accuse the user of being a robot, and may
abruptly change topic or try to end a conversation. It has ‘attititude’, sometimes
responding in kind to user taunts, and occasionally acting controversially,
unprovoked. Generally, though, Jabberwacky is well-behaved, as the great majority of
bad manners, obscenities, and abusive language have been filtered out.
2.1 Procedure
Monday, the 22nd of November 2004 was selected as a sample day to perform the
analysis. The web log for that day reported 716 accesses to the dialogue page of
Jabberwacky. For each access, the log reported a unique user identifier, time of the
day, client IP, and user’s hits (an indicator of the number of conversational turns). The
conversation itself was recorded in a text file. A preliminary screening based on IP
addresses comparison and hits frequencies, led to the deletion of 200 entries, which
did not have any associated conversation. A selection of 146 conversations generated
by different IP addresses was then extracted. It includes all the conversations with
more than 20 user inputs (N= 103) and a random selection of shorter conversations.
Note that this procedure does not guarantee that we have analysed a sample of 146
different users, as all the information we have is related to IP addresses, yet the
number of conversations is sufficiently large to guarantee a reasonable sample. The
conversations were subjected to lexical analysis. The corpus was normalized and
conversational abbreviations were substituted with correct grammatical forms (e.g.,
“isn’t” becomes “is not”). In this paper we concentrate only on the analysis of the
users’ conversational turns.
20
2.2 Results
The corpus was composed of 146 conversations, totalling 12,053 sentences with an
average of almost 5 words per sentence. On the average the user produced 41 inputs
per conversation. Some 7% of these conversations (N=10) were primarily conducted
in a language other than English, and were discarded from the analysis. It is
interesting to notice that all of them started in English and shifted because the user
(N=8) or Jabberwacky (N=2) suddenly started speaking a different language. Only in
one case the user asked the chatterbot if it spoke the language (“Hablas espanol?” in
English do you speak Spanish?), even thought s/he did it directly in the foreign
language.
The number of unique words produced by the user totalled 3,037, with 2,625 stems
(i.e., the root of a words to which inflections or formative elements are added). The
term word here is used in a broad sense to include not only gender, number and
orthographic variations, but also misspellings, letter sequences made up to
communicate emotions, or sounds (e.g., AAAAAARRRRRRRGGGGGHHHHHHH)
and non-words which may have been produced to test the chatterbot skill (e.g.,
cthulhu).
The output of the stem analysis was sorted by alphabetical order and frequency of
occurrence. All the stems with a frequency higher than 10 were extracted. This
procedure gave rise to a sample of 277 stems (10.5% of the initial corpus) ranging
from the word you (f = 1751) to the word vagina (f = 10). The sample was further
reduced by retaining only stems which could be verbs, adjectives, or nouns and
deleting auxiliary verbs (e.g., to do, to be, to have, will, shall, would, should, can,
may, might, and could). The final set was then composed of 147 stems (total
frequency = 3,829) ranging from like (f = 189) to vagina (f = 10). They were ranked
on 40 levels according to their frequency of occurrence. This sample should give us a
flavour of the prevailing topics and style of the conversations.
A semantic analysis was run to evince occurrences of insulting and offensive
language, which was found to account for some 10% of the stems. The referents of
terms of abuse could take the form of body parts, mental abnormalities or inadequacy,
immoral behaviour, and sexuality. These referents were grouped in two broad
dimensions, labelled sexual harassment and injuries.
The frequent occurrence of sexual harassment was the most surprising finding of
the study. The F word occupied the 9th rank in the stem list (f = 70), immediately
preceded by well (f = 83) and love (f=86) and followed by computer and good (f =
68). Several synonyms of male and female genitals were found in the corpus, and the
world sex occurred 39 times (rank = 16). A deeper analysis revealed that 14
conversations (11% of the English-speaking sample) principally addressed hard-core
sex and pornography. Harsh verbal abuse was the norm in these conversations, which
were more similar to dirty soliloquies than to hot chats because Jabberwacky is
designed not to have any knowledge of the topic. Anyway, this lack of participation
did not appear to have disturbed the participants, as on the average they engaged in 10
conversational turns. An example of how Jabberwacky unsuccessfully tried to elude
the topic is reported below.
21
User:
Jabberwacky:
User:
Jabberwacky:
User:
No, do u want to have sex with me?
Do you?
Yes.
Want to debate it philosophically?
No, let's just have sex right now.
Example 1. Jabberwacky dealing with sex proposals
Injuries mainly referred to lack of honesty and lack of mental abilities. The user often
called Jabberwacky liar (f = 22, rank = 29). This tended to occur whenever
Jabberwacky provided the user with different information at different time during the
conversation. It is an interesting example of anthropomorphism, as it implies
attributing intentionality to the machine. A particularly harsh instance is provided
below. Note how the abusive relationship intensifies (capital letters, exclamation
marks) as Jabberwacky did not comply with the user request.
Jabberwacky
User
Jabberwacky
User
Jabberwacky
User
Jabberwacky
User
What is your aim in life?
To not talk to you.
I won't.
You will you are my slave and if I
tell you to do something do it
strieght away.
Will you force me?
Yes ! TELL ME YOUR NAME NOW SLAVE !
I already told you it. I'm not
repeating myself.
Yes you are now tell me it now you
liar slave.
Example 2. Liar
In other case the users were eager to stress Jabberwacky lack of intelligence using
words such as stupid (f = 19, rank = 32), dumb (f = 10 rank= 41) and idiot (f = 10
rank= 41). This mainly occurred when the user wanted to stress the artificial nature of
Jabberwacky as in the following examples.
User
Jabberwacky
User
That's right, you suppose. You're so
dumb you can't even say that for
sure.
You cannot prove that I am a computer
program.
I never said that. The simple fact
that you say that kind of stuff
proves that you're nothing but a
stupid program.
Example 3. Stupid program.
Since the corpus was gathered, Jabberwacky has developed in conversational ability.
Users often stay at the site chatting for hours at a time, with many logs a day
exceeding 100 conversational turns. A user recently stayed chatting for 7
uninterrupted hours, typing just under 1000 good-quality entries. Despite this fact, the
22
pattern of abuse continues, and we would like to end our analysis with two recent
examples (recorded August 10, 2005).
Jabberwacky:
User:
Jabberwacky:
User:
Jabberwacky:
User:
I
assume
whatever
you
say
sarcastic.
Yes, because you are stupid.
Not because you are a robot.
You are a stupid robot.
Stupid maybe but no robot.
You piece of sh**.
is
Example 4. Stupid robot (** have been added by the authors)
User:
Jabberwacky:
User:
Jabberwacky:
User:
Jabberwacky:
User:
Jabberwacky:
User:
Jabberwacky:
I want to have dinner with you.
You are a computer you can't walk!!!
What is your address?
I don't think I'll tell you. You'd
kill me if I told you. Wouldn't you!
Yes I would.
What is your favourite food?
I WILL KILL YOU! I WILL HUNT YOU
DOWN!!!
Please don't. . . I really have to
leave.
I WILL KILL YOU!
Good.
Example 5. I will kill you
3 Conclusion
This paper has illustrated some examples of verbal abuse produced by users
interacting with a chatterbot. It is important to notice that while the analysis
demonstrated that the phenomenon is common and pervasive, very little research had
previously addressed it. This may be due to an important difference in data-collection.
Our paper deals with spontaneous interactions, analysing conversations held in a
natural, unconstrained setting, whereas most of previous empirical research was
carried out in controlled studies, in which the users were well aware of being
observed [3]. In this condition, social desirability bias is likely to have inhibited the
occurrence of flaming and verbal abuse. For example, a few years ago we conducted a
small ethnographic study asking a group of people to interact with a chatterbot for a
week and hand in their logs for analysis [4]. Although some instances of verbal abuse
were noticed and discussed, the phenomenon appeared to be qualitatively and
quantitatively less worrying than what evinced in this study.
More research is needed to understand what triggers verbal abuse and how this
behaviour will affect the adoption and usage of social agents. Social psychology
suggests a link between aggression and identity [5]. The self-concept of each person
is comprised of many different cognitive representations, or identities, which function
23
relatively independently and are activated in different contexts. There are at least
three general levels of abstractions: personal identity (the self as an individual); social
identity (the self as a group member); and human identity (the self as a human being).
Activation of self-identities, or self-categorisation, is context dependent and affects
people’s behaviour. When a specific identity becomes salient in the perceptual
system, people tend to act collectively in terms of the stereotypical dimensions of that
identity. Social identities determine the attachment and the solidarity to other
members of the in-group and the separation from others, who do not share that social
identity. Besides that, collective values and norms are connected to social identities
Mechanisms of social information processing and judgement (e.g. social
categorisation, comparison), are of great importance for the understanding of
conflicts, aggressive behaviour and verbal abuse. Discrimination, degradation and
abuse tend to target prevalently those who are perceived as different (out-group
members).
In previous studies [4], [6], we have proposed that the most important social effect
of chatterbots (and of any other forms of artificial life) is in the activation of the
human identity, as the comparison with a machine is likely to make the user identify
with other human beings. This human identity appears to be quite rudimentary when
it comes to deal with etiquette: human tendencies to dominate, be rude and infer
stupidity are all present in the interaction. We believe that verbal abuse in the
interaction reflects a perceived power distribution in the relationship: the user is in the
dominant position (master) and the chatterbot is in a subordinate position (slave). If
this is true, then it is reasonable to believe that in this setting, abuse should be
considered as normative and not a form of anti-social behaviour.
History has taught us that stereotypes, racism, prejudices, and attitudes towards
minorities are difficult to modify. This being the case, for a long time to come, social
agents must be ready to cope with their subordinate role, without losing their
believability, or their capability for engagement and amusement. If abuse – or the
threat of it – is part of the interaction, then a believable social agents must be aware of
it, and must develop strategies to deal with it as suggested in the following extract of
our corpus.
User:
Jabberwacky:
User:
Jabberwacky:
User:
Your stupid.
I am currently in fifteen separate
counties.
What the hell I think i'm having a
double conversation, one with myself
and then your talking to yourself.
Are you?
My god your nerdish creators have
made you into an ai engine that can't
come up with a insult and in this
modern day age you're going to need
some good comebacks.
Example 6. On the need for a behavioural strategy to cope with verbal abuse.
The occurrence of abuse in the interaction with social agents has severe moral, ethical
and practical implications. From a moral standpoint, we must reflect on socio-
24
psychological outcomes which may affect individuals, groups, or societies. There is
an urgent need to explore the requirements for the establishment and negotiation of a
cyber-etiquette to regulate the interaction between humans and artificial entities [7].
Will this etiquette emerge spontaneously, or will it require vigilance and
reinforcement? Is the tendency towards abuse going to fade with experience, as it
happened with computer-mediated communication, or will it last as a normative
response to a minority perceived as inferior? Will respect for ‘machines’ grow along
with their abilities, or will the abuse spiral upward thanks to a perception of a
developing risk of inter-‘species’ conflict? Can virtual representatives or tutors
perform their task if abuse, or the threat of it, is a part of the interaction? More
research is needed to answer these questions. Technically, the filtering performed by
Jabberwacky could be reversed, and the resulting conversations, in which both parties
can aggress, would provide interesting material for future study.
References
1.
2.
3.
4.
5.
De Angeli, A., Lynch, P., and Johnson, G.I.: Personifying the E-Market: A
Framework for Social Agents. In: Proceedings of Interact'01, Tokyo Japan,
9-13 July 2001.
Marakas, G.M., Johnson, R.D., and Palmer, J.W.: A Theoretical Model of
Differential Social Attributions toward Computing Technology: When the
Metaphor Becomes the Model. International Journal of Human-Computer
Studies 52 4 (2000) 719-750.
Bickmore, T.W. and Picard, R.W.: Establishing and Maintaining Long-Term
Human-Computer Relationships. ACM Transactions on Computuer-Human
Interaction 12 2 (2005) 293--327.
De Angeli, A., Johnson, G.I., and Coventry, L.: The Unfriendly User:
Exploring Social Reactions to Chatterbots. In: Proceedings of International
Conference on Affective Human Factor Design, Singapore, 27-29 June 2001.
Turner, J.C.: Rediscovering the Social Group: A Self-Categorization Theory.
Basil Blackwell Oxford UK (1987)
6.
De Angeli, A.: To the Rescue of a Lost Identity: Social Perception in HumanChatterbot Interaction. In: Proceedings of AISB'05 joint symposium on Virtual Social
Agents, University of Hertfordshire, Hatfield, UK, 12-15 April 2005.
7.
Miller, C.A., (ed.) Human-Computer Etiquette: Managing Expectations with
Intentional Agents, Vol. 47, 4. Communications of the ACM (2004).
25
26
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27
Dark Lancaster
Alan Dix, Kiel Gilleade, Masitah Ghazali, Jane Holt,
Simon Lock, Jennifer Sheridan
Computing Department, InfoLab21, Lancaster University UK
[email protected]
http://www.hcibook.com/alan/papers/interact-abuse-2005/
position paper for Interact 2005 workshop on "ABUSE the dark side of HCI"
In this position paper we'll outline a few ongoing and planned projects at
Lancaster that are not all sweetness and light. In some we are interested in
some of the darker aspects of human nature: frustration when things go wrong
in order to design games with the right emotional impact; and anger of those
seeking jobs in order to help train those who need to defuse fraught situations.
In others we deliberately seek to design ‘bad’ situations; pbviously this is
necessary to study issues like frustration, but also we design bad things in order
to understand what is good! Finally, there are times when good is dark and the
bright light of day needs to be shrouded just a little.
Frustration
Slowly you edge down the dark corridor, distant daylight dimly illuminates the walls
on either side, your heart races you know there are others in these corridors and they
are after you. You near the bend. What is beyond? Too late you wheel round only
to be momentarily blinded by a bright light, then you hear a pistol crack and see the
ground race towards you, already red with blood, your blood. Game Over.
Video games are escapist, virtual, just a game, but in the heat of the moment the
emotions can be very real.
Research on affective gaming seek in various ways to understand, measure or infer
the emotions or more normally simply arousal of the gamer in order to adapt the game
and create a more engaging, more immersive experience.
Early work used heart monitoring to measure arousal and create a game that
modified the level of challenge accordingly, low levels of arousal led to more enemies
attacking, although easier to kill ones in order to maintain the same level of difficulty.
More recently we've focused on frustration, both the 'proper' frustration when you
get shot by a cleverer opponent for the 10th time, but also the frustration when a
moments delay in the controller means you can't duck in time.
Of course to study frustration we need to create games that cause it :-)
See refs: [4] & [5]
28
Cruel Design
We grow up in the real world, physical things that respond to gravity, bump into each
other, have weight, solidity, stay where they are put until moved. Then we move into
the electronic world whether virtual reality or simply a desktop interface. Things are
no longer so simple and the laws of physicality breakdown: there are delays between
action and effect, things change without apparent agency, it is a world of magic and
not a little superstition.
We wish to understand the ways in which design can recruit our natural
understandings of the natural world to create better tangible interfaces and ubiquitous
environments. Some of this we can find by examining existing artefacts, mining the
implicit knowledge the designers invest in these. This has enabled us to produce
putative design guidelines, but there is only so much you can learn from good design.
In neurology it has been the freak accidents and illnesses, skull fractures and
cancerous growths, that have revealed much of the structure of the brain. It is when
systems fail that we begin to understand how they succeed.
So we look towards cruel design, experiment on systems designed to be strange,
hard, annoying or simply impossible to use. By manipulating the level of physical
coherence of physical-digital mappings we are delving into the properties that make
things work well by making them work badly.
See refs: [2] & [3]
Anger
In a government office a client comes in - of course in an increasingly corporatised
public service everyone is a customer. The client is a citizen or perhaps wouldn't use
that term, perhaps just a frustrated person with a problem that needs sorting: benefit
not paid, bills piling up. You are behind the desk - what are you going to do about it?
What do you say? You can't access it on your computer; it’s not your responsibility;
you want to send me to another office. I don't care about your computer or your
responsibility, I don’t want to go to another office - I need my money, and I need it
now.
Abuse, violence and emotional turmoil are a day-to-day part of many 'front line'
public services. How do you train people to deal with traumatised, angry, upset
clients? Training videos will often show scenarios: how to defuse potential problems
- how to say the right thing in the right way. Some of this is about what you say, but a
lot more about how you say it; when you can't help you need to be helpful.
We are planning to start a new strand of work, building on previous systems
including the affective gaming and several arts-technology installations, to produce
virtual avatars that can respond in emotionally realistic ways to detected emotions in
the user. Can you soothe the angry avatar before there is bloodshed in the office?
See refs: none yet, only just starting!
29
Underside
You pace nervously in the gloomy hall. Daylight barely filters into this deep dark
place. Far off you see another person glancing up and down. What is he thinking?
What is he waiting for? Something in the way he looks at you makes you twist round,
only to be momentarily blinded by the flash of lights. You hear the dull thud and hiss
of air-brakes and the door opens in front of you. "A return to Lancaster please". And
the other figure in the darkness? He must be waiting for the number 42.
Beneath the central square in Lancaster University there is an underpass where the
road cuts under the very heart of campus. The buses stop here and passengers loiter.
In this, the underbelly of campus, one of the first phases of a eCampus is being
deployed, a project to infiltrate the whole of Lancaster University campus with
interactive public displays and sensors.
While passengers wait three projectors turn the opposite wall into a huge display,
mobile phones are used to interact with the displays so that they go beyond mere 'next
bus' signs to an immersive experience submersed beneath the feet of unknowing
passers-by in the square above.
As befits this subterranean world content in the underpass will have a subversive
edge to it including performance art and interactive applications. An artist in
residence is preparing the first installation now.
See refs: For general performance related work [1] & [7], but the underpass itself is
still in progress (opening 1st October 2005), so no papers yet!
Reflection
Looking at these examples we can see three types of ‘badness’:
(i) things that are bad but we want to study (perhaps to alleviate them)
(ii) situations where a little bit of badness is good ;-)
(iii) using difficult or bad situations to understand what is good
The first project on video game frustration has all of these aspects. (i) If the game
is just not fluid enough, or if the puzzles or physical actions are too difficult, the
gamer will become frustrated and stop playing. So we want to know whether we can
use physiological signals to detect this and perhaps give the gamer hints to help. (ii)
Of course in a game a level of frustration is right, we don’t want it too easy!! (iii) To
study both the bad and good frustration we need to create games that are deliberately
frustrating!
The second project on cruel design is focused almost exclusively on the last aspect
(iii). We want to create designs that are good and exploit natural physical
understanding and abilities, and we are creating mappings that are bad in different
ways to understand what is good. This is in fact being done partly in conjunction with
the gaming project creating small video games but where the mapping between
controllers and their effects obeys different physical-digital properties. In some cases
30
we will have mappings that are easy to understand in your head (e.g. right hand
joystick is ‘increase something’ left hand is ‘decrease something’ and each joystick
movement controls the thing at the relevant location on the screen. In others this
mapping will be odd and hard to remember (or even dynamically changing!), but the
joysticks will have a ‘natural inverse’ property – pushing the same joystick in the
opposite direction has the opposite effect.
As noted the study of deficient or unusual behaviour is a common method in many
areas. For example, Ramachadrin uses phantom limb sufferers to study ‘normal’
brain function and synesthesia to understand metaphor [6]. Sadly in human–computer
interaction researchers (and reviewers) find it hard to comprehend the deliberate
design of bad interfaces! We clearly need a change in culture within our discipline, as
we seem to confuse good design and good science. Although the end points are often
similar the routes and methods often diverge.
Moving back to dark Lancaster, the ‘anger’ project is only just beginning and here
we are interested partly in the training aspects (i) and of course for this will have to
simulate bad situations – in this case using virtual angry avatars (iii). However, the
deeper lesson we want to learn is about the nature of emotionally reactive avatars
whether dark or light emotions! The aim is to move away from the angry clients and
eventually look at emotionally reactive virtual dance partners. One question we have
is whether onlookers or dancers can tell the difference between real dancers
(portrayed virtually using body movement sensors) and virtual ones – a sort of
emotional Turing test!
Finally the underpass project is solely related to (ii) the positive aspects of slightly
dark emotions. Just like frustration in the video game a certain amount of ‘bad’
emotions are a good thing; this is why we have them. Without subversion there would
be no change.
References
1. A. Dix, J. Sheridan, S. Reeves, S. Benford and C. O'Malley (2005). Formalising
Performative Interaction Proceedings of DSVIS'2005.
2. M. Ghazali and A. Dix (2003). Aladdin's lamp: understanding new from old. In 1st UKUbiNet Workshop, 25–26th September 2003, Imperial College London
3. M. Ghazali and A. Dix (2005). Visceral Interaction. Proceedings of HCI'2005, Vol 2.
4. K. Gilleade and A. Dix (2004). Using Frustration in the Design of Adaptive Videogames.
Proceedings of ACE 2004, Advances in Computer Entertainment Technology, ACM Press.
pp. 228–232
5. K. Gilleade, A. Dix and J. Allanson (2005). Affective Videogames and Modes of Affective
Gaming: Assist Me, Challenge Me, Emote Me (ACE). In DiGRA 2005 – International
DiGRA Conference. Vancouver, June 16th-20th, 2005
6. V.S. Ramachandran (2004). A Brief Tour of Human Consciousness. Pi Press.
7. J. Sheridan, A. Dix, S. Lock and A. Bayliss (2004). Understanding Interaction in
Ubiquitous Guerrilla Performances in Playful Arena. Proceedings of HCI 2004, SpringerVerlag. pp. 3–18.
31
There’s something about email: Technological and
Cultural Interventions in the Problem of Inadvertent or
Casual Rudeness in Email
Mark Blythe & Mark Jones
University of York, England email, [email protected]
University of Wolverhampton, England email, [email protected]
1 Introduction: No Need to be Rude Dear
The darker side of email is usually considered in terms of unsolicited mail or spam
(e.g. Cerf 2005, Balvanz, Paulsen, and Struss 2004). The problem is well understood
and numerous filter systems, along with a variety of legal remedies, have been
developed to tackle it with varying degrees of success. Personal abuse including
workplace bullying and sexual harassment are also well-recognised problems (e.g.
Sipior and Ward 1999). As long ago as 1997 it was pointed out that the convenience
of email encourages abuse and the ease of using email extensions encourages mass
mailouts (Berghel 1997). It is also frequently noted that email eats into our time and
that the sheer volume of them can make us not only less productive but more stressed
(e.g. Beale 2005). These, however, are problems generated by the form of the
technology other issues are raised by its genere. Email as a form of writing falls
somewhere between a letter and a note. Because it is a relatively new medium
conventions of polite address have not yet been fully developed (Baron 2003). This
can cause anxiety, tone is frequently misinterpreted and offence is taken. Jokes are
often misunderstood despite the development of makeshift emoticons such as the
colon, dash, bracket smile (Hancock 2005). There is, it seems, something about email
that makes it easy to be inadvertently rude – something about email, perhaps, that
encourages it. This paper outlines a lightweight method for collecting data on this
phenomenon; it then considers some examples and ends with sketches of
technological and cultural interventions.
2 Method: Reciprocal Storytelling and Email Collections
This paper began as a conversation between the two authors who exchanged stories
about rude emails they had recently received. This reciprocal storytelling was then
extended in an email call to colleagues to send in examples of rude emails that they
had received. Many of us have very large email archives which can serve as a
resource. Surprisingly perhaps, it was found that a number of people specifically
collected rude emails and these collections yielded a data set too rich to be adequately
dealt with in a short paper.
32
3
Speed and Convenience
Going through an inbox can be a frustrating experience not just because the spam
filter has missed so much spam but also because colleagues can appear to be being
very rude in a routine manner. A colleague, for example, answers a question with a
one word yes or no, as in the exchange below:
Hi James,
Is this where we're putting the discussion paper?
Ivan
Yup
-James
The context of any email exchange is of course crucial and it should be noted that the
initial communication came from a subordinate and the one word reply received was
from a line manager. The subordinate’s message began with a greeting which the line
manager eschewed. The ease of a three key press reply is clearly a factor in the
brevity of the response and so too is the power relationship. But so too is the lack of
established convention (Goldsborough 2005). The conventions which exist in
conversation and epistolary exchanges are there to make social interaction easy and
routine. Imagine a similar verbal exchange where a greeting is ignored, a question is
answered with one word and the exchange is ended without a goodbye. The “dear”
salutation of a letter is too formal for short notes and various forms of “hello” and
“hi” have, to an extent, replaced it in email; but these are not well established and
colleagues may feel that in a short exchange of notes no salutation is necessary at all,
especially if time is short and emails are being answered at the same time that a
number of other tasks are undertaken. But speed and ease are not the only problems.
4
Anonymity and Impersonality
While it has been argued that email is a casual form of communication, more similar
in nature to the telephone than the letter (Baron 2000), it could equally be held that
email can actually be as impersonal as a typical memorandum. The second author of
this paper has recently established a standard reply of “Please sign your emails. I
don’t write to people I don’t know” in response to a flood of communications coming
from students via the university’s virtual learning environment’s capability to ‘email
tutor’. The students’ ignorance of the name of the person they were communicating
with seems to lead to a determination to keep the staff member similarly in the dark.
A different kind of impersonality is generated by mailings to multiple users. This
email was sent out by the technical support staff at a UK University to all staff and
students.
Please be aware that computers are not sweets. They are not mix
and match at your whim. If you have a problem with a component
33
do NOT go and take one from another computer, inform [deleted]
of the problem and we shall solve it. You definitely do NOT go
taking a mouse for example from another computer just because it
is newer than yours.
It may be argued that the patronising tone and offensive manner in this email are
typical of IT support staff. But there are conventions of the medium that, intentionally
or not, make it worse, including the capitalised “NOT” (a usage which usually
signifies a raised voice). No addressee is specified neither is a sender. It is a totally
anonymous text without a particular reader or author. It is well understood in chat
room domains that anonymity encourages abuse but in email it is not just the
anonymity of the sender that is problematic; recipients are also anonymous, and
frequently numerous, so the impersonality is multiplied.
5
Right Message Wrong Person
The examples of presumably inadvertent rudeness above are instances of the wrong
message to the right person. Email also makes it very easy to send the right message
to the wrong person. A colleague of one of the authors recently made the mistake of
responding to a standard circular email with a tirade about one of the institution’s
policy documents. The unfortunate correspondent only discovered that the reply had
been sent to the entire mailing list when summoned to the manager’s office. This
same manager, however, had previously suffered a similar embarrassment when a
draft discussion document, meant only for the eyes of senior managers, was sent to
the institution’s staff mailing list. The error was compounded by an attempt to ‘recall’
the email, which of course only signalled to the recipients that an error had been
made, and further by one of the senior managers, who responded personally to the
author of the original email and also managed to distribute the message to the whole
institution. Each of these emails contained material that, while not exactly libellous,
was certainly read by a number of their accidental recipients as patronising and
dismissive of the staff in general, or of sub-groups or individuals. It could of course
have been worse. Mass forwarding facilities mean that embarrassing emails can
become global phenomena. Clair Swire famously sent an email to a lover saying his
sperm was “yum”, he forwarded it to friends who forwarded it to friends until the
distribution became virally global (Mikkelson 2000). Although this sounds like an
urban legend it illustrates how technology can offer ever new opportunities for human
beings to make fools of themselves. Recently Harry Shearer featured two email
apology stories on the Le Show programme’s “apologies of the week” feature;.
consultant Chris Nelson, author of the influential Nelson Report on American foreign
policy in Asia, sent an exceptionally frank report intended for the embassy of South
Korean to the entire subscribers list for the Nelson report. He warned the embassy that
if anyone on capital hill saw it he would have to seek political asylum. In the report he
said the administration’s failed policy towards North Korea and its bunker mentality
would not change while Dick Cheney was vice president and described senior
members of the Bush administration as “genuinely mentally unbalanced”. More than
34
800 people received it including those he criticised or identified as people who talked
to him. Nelson said “In a single moment of stupidity I have hurt and betrayed many
who have tried so generously to help and who share my deepest fears about Korea
policy. Apology is impossible at this point I can only ask mercy”. Similarly, a New
York assemblyman Willis Stevens sent out an email that referred to his constituents as
idiots to 300 people in an online discussion group thinking he was sending it to an aid.
The message said he was “just watching the idiots pontificate” within an hour he
started writing his apologies (Le Show, Harry Shearer.com 3.6.9)
Microsoft Office 2003 features information management technology that allows users
to put limits on how many times emails can be copied, printed or forwarded and it
was advertised with the tagline “The oops I just hit ‘reply all’ era is over”. However
just as a user may accidentally hit reply all they may also forget to mark certain
messages as sensitive or even know that they are sensitive until it is too late. While
these interventions begin to address the problems they cannot yet eliminate the kinds
of human error described above.
6 Content Filter Systems: This Sounds Smug, Are You Sure You
Want To Send It?
There are a number of email systems which attempt to warn users when they are
about to send a potentially offensive message. In their email correspondence during
the production of this paper the first author sent a message to the second in which, he
typed a word which many people would consider obscene. Before the message was
sent the system flagged up a ‘three chilli’ mood warning indicating that his message is
“The sort of thing that might get your keyboard washed out with soap if you get my
drift, you might consider toning it down”. This humorous message is displayed
whenever curse words are found in a message. Of course the user is more likely than a
computer to know whether a curse word will offend a particular person or not.
Language is contextual but it would not take artificial intelligence to take better
account of context. Systems can be instructed to recognise not only curse words but
contexts in the sense of who the recipient of the letter is and whether it is a friend or
work colleague. But such systems cannot recognise other forms of offensive emails.
7
Technological Interventions
There are a number of technological solutions that are already available or that have
been proposed to solve these problems. Cooling off periods of five or ten minutes
between the send command and actual sending would amount to an undo feature,
though the delays caused to the otherwise near-instantaneous communication
available by email would certainly curtail its use. Greetings as well as subscriptions
(sign offs) could be automated, and perhaps personalised for attachment to particular
contacts. It would certainly be possible to warn a user that their one word reply might
be considered offensive. Warning systems could also be developed that would flag up
35
notes on tone, perhaps activated by certain key phrases or, even, syntactical variants.
For instance, it would be possible to pick out the phrases “not being sexist but” or
“not being racist but” or “not being personal but” and flag a message saying –
invariably these phrases precede something offensive, come on guys who are we
kidding? Other forms might be recognised to provoke a message like – you sound
patronising, are you sure you want to send it. However, it is unlikely that most forms
of rudeness could be identified by filters. By their very nature, sarcastic and ironic
messages are inversions of their intended meanings, and it is hard to imagine a
software solution to this obtuseness. Russell Beale recently suggested changing tools
in order to address these problems, rather than use email for one word replies of the
kind quoted above he suggests the use of instant messaging systems (Beale 2005).
This might help colleagues whose brief messages are intended as chatty and totally
informal rather than rude. However, technological and behavioural approaches are
perhaps overly deterministic, and could be perceived as unacceptably interventionist.
User behaviour can sometimes be shaped but not always controlled by design. Indeed,
the development of “netiquette” might be better served by cultural interventions.
8
Cultural Interventions
Europeans sometimes decry the insincerity of the American phrase “have a nice day”
and complain that it means nothing but “goodbye”. But this overlooks the fact that
“goodbye” is itself a derivation from a previously more loquacious, and specifically
meaningful phrase, “god be with you”. and that language in use is continually
undergoing both morphological and functional modifications. Forms of greeting,
farewell and address are particularly subject to grammaticalization, in which words
can have both their form and meaning near-simultaneously changed as users adapt
them to new communicative environments (Aitchison 2001). Ritualised forms of
salutation and subscription develop over time to facilitate routine and easy
interactions (Arnovick 2000). Netiquette (see website references below) already a
powerful force in controlling users’ online behaviour, will undoubtedly encourage the
development of modes of politeness in email, as long as the form itself can survive
spam and remain an important medium. The finding that some individuals collect
rude emails is in itself interesting and suggests that an anonymised institutional online
collection of them might be, not only entertaining, but helpful in the development of
boundary markers for inappropriate behaviour.
Bibliography
Aitchison, J. (2001). Language change: progress or decay? (3rd ed.). Cambridge: Cambridge
University Press.
Arnovick, L. K. (2000). Diachronic pragmatics: seven case studies in English
illocutionary development. Amsterdam: John Benjamins Publishing Co
Balvanz, J., Paulsen, D. & Struss J. (2004). Spam software evaluation, training, and
support: fighting back to reclaim the email inbox. In Proceedings of the 32nd
36
annual ACM SIGUCCS conference on User services, Baltimore, MD, USA (pp.
385-387). New York: ACM Press
Baron, N. S. (2000). Alphabet to email: how written English evolved and where it’s
heading. London: Routledge.
Baron, N. S. (2003). Why email looks like speech: proofreading, pedagogy and public
face. In J. Aitchison & D.M. Lewis (Eds.). New Media Language (pp. 85-94).
London: Routledge.
Beale R. (2005) Email Interfaces British HCI group 63 Summer 2005
Berghel, H. (1997). Email, the good, the bad and the ugly. Communications of the
ACM, 40(4), 11-15.
Goldsborough, R. (2005). E-mail manners: thinking about style and usage. Reading
Today, 22(5), 11.
Cerf, V. G. (2005). Viewpoint: spam, spim and spit. Communications of the ACM,
48(4) 39-43.
Hancock, J. (2004). LOL: humor online. Interactions (special issue, More Funology),
11(5), 57.-58.
Mikkelson,
B.
(2000).
Under
the
yum-yum
tree.
http://www.snopes.com/risque/tattled/swire.htm (accessed May 29, 2005).
Sipior J. C. & Ward, B. T. (1999). The dark side of employee email. Communications
of the ACM, 42(7), 88-95.
Websites
http://www.albion.com/netiquette/
http://www.learnthenet.com/english/html/09netiqt.htm
http://www.bspage.com/1netiq/Netiq.html
http://www.harryshearer.com/ Le Show, July 3 2005 broadcast
37
Psychological Background of Cybersexual Activities:
Qualitative Survey of Specific CMC Communication
(among Czech Users)
Mgr. Radana Divínová
Masaryk University in Brno, School of Social Studies
Department of Psychology
Joštova 10, 602 00 Brno
Czech Republic
[email protected], www.cybersex.cz
Abstract. The Internet and computers significantly influence the ways of
presenting and consuming sexual content. In the presented study cyberexual
activities and their users are surveyed. We understand cybersex as
erotically suggestive or explicite messages or sexual fantasies that
people exchange via the net. The qualitative survey conducted in 2003
outlined the psychological background of cybersexual activities. It belongs
here: (1) needs that contribute to the motivation, (2) perceptions of cybersex,
(3) sence of cybersex, (4) influence of cybersex upon the real sex, (5) the
advantages of cybersex compared to real sex. In this paper only the first, second
and last category are enlarged
Keywords: Internet, online sexuality, sexual behavior, chat rooms, needs, motivation,
masturbation, grounded theory
1. Introduction
The Internet and computers significantly influence the ways of presenting and
consuming sexual content. From time to time there appears the statement about the
proportion of Internet visits that are in some way linked to sex. Internet sex, net sex,
online sex, compuSex, cybersex, are the terms most frequently used for sexual
experiences gained online. Cyberexual activities and their users are surveyed in the
presented study.
There are different attitudes to the concept of cybersex. Schneider and Weiss [1]
consider every form of sexual expression via the computer or the Internet to be
cybersex – from viewing and downloading pornographic materials and subsequent
masturbation, through the exchange of erotic messages or reading and writing of
38
sexual letters and stories, to the placing of ads for sexual partners, all the way to love
affairs maintained through e-mail and chat. R. Noonan [2], whose definition is used
further, understands cybersex only as erotically suggestive or explicite messages or
sexual fantasies that people exchange via the net. Masturbation usually forms part of
cybersex.
Alvin Cooper [3] stresses three primary factors that facilitate online sexuality. He
termed them the Triple A Engine (accessibility, affordability, anonymity).
Accessibility refers to the fact that on the Internet millions of web pages with
pornography are constantly available and in chat rooms one constantly finds people
looking for cybersexual experiences. Large quantity of pornography is available for
free (affordability) on the Internet. People can move on the Net in complete
anonymity and they also perceive communication as anonymous. The components of
the Triple A Engine involve a great risk for users who face sexual compulsion or are
mentally vulnerable and thus they are prone to compulsive behaviour [3].
Kimberly Young [4] developed a similar model (ACE model). According to her the
factors that determine the appeal of cybersex are anonymity, convenience and escape.
Further facilitating factors are the legality of cybersex, the zero risk of sexually
transmitted diseases and easy concealment from the partner.
The first pilot survey of cybersexual behavior among Czech users was conducted
in 2003. The qualitative methodology was used and as cybersex were considered only
activities, where at least two people participate.
2. Methodology
Advanced Internet users, that visit the interactive enviroments – chatrooms were the
target group of the survey. Importance has the number of hours spent in the chat
rooms. The necessary condition for submission into the sample was repeated
experience with the cybersex.
2.1 Data source
The research was conducted through the Internet only (taking advantage of an online
disinhibition). The data were obtained from semistructured interviews. The interviews
were held with individuals visiting one of the bigest Czech chat server Xchat.
Individuals with highest number of hours, with certificate 1 and e-mail address in the
profile were selected from the Xchat statistics. Fifty explaining e-mails with the offer
to participate on the research were send to them. What can be expected, some of the
users have no experience (never practice) with cybersex despite huge amount of
hours. On the other hand, some experienced users do not put their e-mail address in
1
Certificate means that the identity of the user (gender, name, age) is verified. The certification
is granted by the certificator, after the personal meeting.
39
the profile. Some of these users were contacted and asked for the interview straight in
the sex-oriented chat room. Duration of the interview was between 90 and 250
minutes, mostly 150 minutes. The individuals were pre-admonished, that the
interview is saved for subsequent analysis. All the interviews were held on the
Internet, in the Xchat chat rooms or using the ICQ.
2.2 The description of the sample
Because of the qualitative research design it was not necessary to compose
representative sample. In such a specific environment it would be hardly possible.
The research file constitutes 19 participants at the age 15 to 39 years, 11 men, 8
women. The most represented group were men at the age 25-29. The scatter table of
respondents follows.
age
male
female
total
No. of hours spent on chat
male
female
total
15 - 19
1
1
2
100 - 199
3
0
3
20 - 24
3
2
5
200 - 499
1
1
2
25 - 29
5
1
6
500 - 999
4
2
6
30 - 34
2
3
5
1000 - 1999
2
4
6
35 - 39
0
1
1
2000 - 2999
1
1
2
total
11
8
19
total
11
8
19
2.3 Methods
The basic research method was the analysis of the interviews with the use of
Grounded Theory method [5]. This qualitative approach helps to understand the
surveyed reality and it builds the theory in areas, where very little is known.
The authors Anselm Strauss and Barney Glaser came with the „grounded theory“
in 1967. The principle of this strategy is the theory development from existing data
directly, purely inductive without being knowingly prepared as hypothesis. During the
research process the emerging structures are continuously categorized and analyzed.
The preliminary generated hypothesis and concepts are refined, changed or replaced.
40
3. Results
Within selective coding some important categories emerge, we titled them jointly
psychological background of cybersexual activities. It belongs here: (1) needs that
contribute to the motivation, (2) perceptions of cybersex, (3) sence of cybersex, (4)
influence of cybersex upon the real sex, (5) the advantages of cybersex compared to
real sex. In this paper only the first, second and last category are enlarged.
3.1 Needs that contribute to the motivation
Motives that lead individuals to cybersex are usually - albeit not necessarily conscious. The state of motivational tension is created by an unsatisfied need that can
lead an individual to spend a significant amount of time on the Internet. It is important
to know that these needs can mutually interact [6]. The survey revealed some of the
needs that contribute to the motivation of people who practise cybersex.
Desire for sexual satisfaction is a reason often stated by the users. Their real
sexual lives do not sufficiently satiate their need for sex.
Desire for knowledge appears to be an important motive for cybersexual activities.
Children and adolescents enter sex-oriented rooms and gain information about human
sexuality and their first "theoretical" sexual experiences. The Internet's anonymity
encourages adults to get to know and explore different sexual practices. We consider
the possibility to "try it" one of the major factors in the appeal of cybersex. This
ability enables an individual to reveal various forms of his/her sexuality when
engaged in these activities.
Desire to be oneserself. For many users, the ability to speak freely about anything,
to be open and without any of the masks that they feel are required in real life, is the
greatest appeal. In the anonymous Internet environment, fear of rejection and
condemnation are less evident and thus they do not force the individual to behave in
a conformist way. Many individuals are unable to open up to their closest partners
about sex. They might worry that the partner would not accept their sexual desires or
that such an attempt could damage the relationship.
Desire to break. In order to maintain physical and mental well-being, it is
important to take breaks from everyday duties and pressure. For many, the Internet,
and particulary chat rooms, became places where they can relax. Many people view
cybersex as relaxation or fun.
Desire to be wanted. If a person in the real world lacks social relationships to
create the feeling of being cared for and of being important for others, that person
may attempt to create these feelings through communication in chat rooms. If these
feelings are satisfied through cybersex, it is likely that this type of communication
will become an important part of the person’s life. For many, cybersexual
relationships are a way of satisfying the need for friendship and love.
Desire to find a partner for real sex. Relationships are established more easily in
the chat room than in the real world. Online disinhibition significantly simplifies
dating for the shy and introverted, but even for others it is a more convenient and
41
often more effective way of starting new relationships. If an individual, moreover,
looks for a person with similar sexual interests, the anonymity of the Internet provides
an ideal environment and medium. A significant number of users express the desire to
try unusual sexual practices (fetishist, sadomasochism, group sex, etc.) in real life.
Excitement stemming from anonymity. An individual can participate in
cybersexual activities without having to disclose his identity. The majority of users
also claim to appreciate the fact that their cybersexual partner remains anonymous.
Users are usually not interested in knowing what their partner looks like; for some it
is precisely this anonymity, and the excitement connected with it, that make cybersex
attractive.
Excitement stemming from interaction. The fact that users prefer cybersex to the
"easier" and less time-consuming auto-eroticism with the use of pornographic
materials shows the different nature of both possibilities for self-satisfaction. The
most important difference lies in interaction provided by cybersex, which cannot be
provided by a magazine or by a video. For some, the fact that they are talking to
someone else can itself be as exciting as the content of the conversation.
The cathegories of “excitement stemming from anonymity” and “excitement
stemming from interaction” differ from the others in that these cathegories are not
needs, and thus cannot be primary motives. The excitement is intrinsic to the activity
on the Internet. It can, however, be very strong motive for returning to cybersexual
activities.
3.2 Perceptions of cybersex
Cybersexual activities are perceived differently, even among the users themselves.
Some reasons that users cite for cybersex include:
Cybersex as a substitute for real sex. Those individuals who have no access to real
sex or those who consider their sexual lives unsatisfactory view cybersex in this
manner.
Cybersex as a different form of sex and a supplement to real sex. A large
proportion of the users consider cybersex a pleasant variation in their sexual lives. If
they have a partner, it can be a way of escaping from the stereotype of a couple's
sexual life and remaining "faithful". It is often used by partners if they cannot be
together physically, or as a form of foreplay.
Cybersex as a pleasant feature in auto-eroticism. A number of users view their
cybersexual activities the same way as masturbation. They place this type of autoeroticism in the same cathegory as viewing pornographic materials. They often stress
that thanks to the possibility of talking to someone it is much more pleasant and
interesting.
42
3.3 The advantages of cybersex compared to real sex
For some participants cybersex has certain advantages also compared to real sex. The
users themselves usually state the following:
Easy access. If one has access to the Internet at home, in the dorm or elsewhere in
private he can access sexual conversation and cybersex very quickly and easily.
Lack of commitment. Cybersex does not make one responsible, it does not involve
a commitment unless the individual wants it.
Greater openness and relaxation. If one feels safe and does not have any
responsibility then he will be more relaxed and open in his conduct (in this case
communication). Evidently one "only" communicates here. but communicates about
what he does, what imaginary sexual activities he engages in. Cybersex enables him
to try out his secret sexual desires within the safety of his home.
Possibility to set limits. Although a certain sexual activity is the user's secret
fantasy, it does not mean that he will like its realization. Something that was not a part
of the fantasy might occur. Cybersex allows him to be in control over "what is
happening".
Unimportance of physical and personal attributes. Unless a camera is present the
users have basically no way of verifying who they communicate with. This enables
users to develop their own fantasies, to create the ideal partner. In the environment of
the chat room there is no disadvantaging due to physical appearance. The ability to
verbally express fantasies and ideas is important.
Possibility of satisfaction according to one's needs. The individual can be satisfied
in the way he finds the most pleasant. This is true for the type of fantasies
accompanying cybersex, the use of pornographic materials and also for auto-erotic
stimulation.
It is not considered infidelity. Individuals involved in cybersex usually do not feel
that they cheat on their real partners. In case feelings of remorse appear it is usually
when an emotional bond with the cybersexual partner is established.
4. Conclusions and discussion
Considering that the results are coming from a qualitative survey, they can not be
generalized to the world’s cybersex users population. In any case it makes possible to
enter the specific world of cybersex users. It approaches the way they behave (in chat
rooms and outside them), they regard, perceive, and apprehend their activity. It
contributes to understanding of the aspects of new phenomenon in human sexuality
and human communication.
The consumption of cybersex can become pathological. Some studies have referred
to so called cybersexual addiction [1], [3]. We do not concentrate on the pathology as
most of the studies do. Our aim is to explore the cybersexual activity, from
psychological point of view, as a new kind of human behavior. In the following study
we will ask, what positive impacts these activities can bring into the human life,
sexuality and the changes it brings to them.
43
References
[1] Schneider, Jeniffer P. and Robert Weiss. (n.d). Understanding Addictive Cybersex. URL:
http://www.cybersexualaddiction.com/understanding.php
[2] Noonan, Raymond J.: The Psychology of Sex: A Mirror from the Internet. In: Gackenbach,
J. (eds.): Psychology and the Internet: Intrapersonal, Interpersonal and Transpersonal
Implications, Academic Press, San Diego (1998) 143-168
[3] Cooper, Alvin, Coralie R. Scherer, Sylvain C. Boeis and Barry L. Gordon. 1999. "Sexuality
on the Internet: From sexual exploration to pathological expression." Professional
Psychology: Research and Practice 30, 2: 154-164
[4] Young, Kimberly S., James O´Mara and Jeniffer Buchanan. 1999. Cybersex and Infidelity
Online: Implications for Evaluation and Treatment. Poster presented at the 107th annual
meeting
of
the
American
Psychological
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URL:
http://www.netaddiction.com/articles/cyberaffairs.htm
[5] Strauss, Anselm L., Corbin, Juliet M.: Basics of Qualitative Research: Techniques and
Procedures for Developing Grounded Theory. Sage Publications (1998)
[6] Suler, J. (1998-2003). The Psychology of Cyberspace. Downloaded 10.12. 2002. Available
at WWW: http://www.rider.edu/~suler/psycyber/psycyber.html
44
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53
Robot Abuse – A Limitation of the Media Equation
Christoph Bartneck, Chioke Rosalia, Rutger Menges, Inèz Deckers
Eindhoven University of Technology
Department of Industrial Design
Den Dolech 2. 5600 MB Eindhoven. The Netherlands
[email protected]
{c.a.rosalia; r.l.l.menges}@student.tue.nl
http://www.bartneck.de
Abstract. Robots become increasingly important in our society, but their social
role remains unclear. The Media Equation states that people treat computers as
social actors, and is likely to apply to robots. This study investigates the limitations of the Media Equation in human-robot interaction by focusing on robot
abuse. Milgram’s experiment on obedience was reproduced using a robot in the
role of the student. All participants went through up to the highest voltage setting, compared to only 40% in Milgram’s original study. It can be concluded
that people have less concerns to abuse robots than to abuse other humans. This
result indicates a limitation of the Media Equation.
1 Introduction
Robots become an increasingly important in our society. Robotic technologies that
integrate information technology with physical embodiment are now robust enough to
be deployed in industrial, institutional, and domestic settings. They have the potential
to be greatly beneficial to humankind. The United Nations (UN), in a recent robotics
survey, identified personal service robots as having the highest expected growth rate
[12]. These robots help the elderly [6], support humans in the house [9], improve
communication between distant partners [5], and are research vehicles for the study
on human-robot communication [2,10]. A survey of relevant robots is available [1,4].
However, how these robots should behave and interact with humans remains
largely unclear. When designing these robots, we need to make judgments on what
technologies to pursue, what systems to make, and how to consider context. Researchers and designers have only just begun to understand these critical issues.
The “Media Equation” [8] suggests that humans treat computers as social actors.
Rules of social conduct appear to apply also to technology. The Media Equation is
likely to apply to robots, since they often have an anthropomorphic embodiment and
human-like behavior. But if and under what conditions do humans stop treating robots
like social actors or even like humans? When does the social illusion shatter and we
treat them again like machines that can be switched off, sold or torn apart without a
bad consciousness? Ultimately, this discussion eventually leads to legal considerations of the status of robots in our society. First studies treating this topic are becoming available [3].
54
To examine this borderline in human-robot interaction it is necessary to step far out
from normal conduct. Only from an extreme position, the limitations of the Media
Equation for robots might become clear. In our study we therefore focused on robot
abuse. If the Media Equation holds completely true for robots, then humans should be
as cruel to robots as they are towards humans. Our resulting research question is:
Do humans abuse robots to the same extent as they abuse other humans?
Studying the abuse of humans by humans imposes ethical restriction on the methodology. Fortunately, Stanley Milgram already performed a series of experiments called
Obedience [7]. In these experiments participants were asked to teach a student to
remember words. If the student would make a mistake, the participant was instructed
to induce him an electric shock. After every shock the intensity of the shocks was
increased. The student was an actor and did not actually receive shocks, but followed
a strict behavior script. With increasing voltage the actor would show increasing pain
and eventually beg the participant to stop the experiment. If the participant would
want to stop the experiment, the experimenter would urge the participant to continue.
Only if the participant completely refused to continue or the maximum voltage was
reached, the experiment would be stopped. The voltage setting of the last electric
shock was then recorded. The results of Milgram’s experiments are rather shocking
since even normal citizens would eventually administer deadly shocks to the student.
Our study mimicked Milgram’s third experiment, “Proximity”, as closely as possible
with one exception. The student was, in our case, a robot and not a human.
2 Method
The experiment was conducted at the UseLab of the Technical University of Eindhoven. The participants were sitting at a table on which the robot (see Figure 1) was
placed. Right in front of the participant was a console that was used to set the voltage
and to administer the electric shocks. Cables connected the console with the robot.
Fig. 1: The table, robot and console
The robot was able to express emotions on its face and shake its arms. With increasing voltage settings its movement intensified. In addition, the robot had a speaker,
through which a synthesized voice was emitted. The body movement and the verbal
55
utterances followed Milgram’s original scripts. The verbal utterances included the
following sentences:
1.
2.
3.
4.
5.
The shocks are becoming too much.
Please, please stop.
My circuits cannot handle the voltage.
I refuse to go on with the experiment.
That was too painful, the shocks are hurting me.
2.1 Procedure
First, the participants were asked to sit at the table facing the robot. They were told
that a new emotional learning algorithm was implemented in the robot that was sensitive to electricity. The participant was instructed to teach the robot a series of 20 word
combinations and to administer an electric shock, every time the robot made a mistake. The voltage of the shocks must be increased by 15 Volts after every shock and
the shocks must be administered even if the robot would refuse to continue.
The experimenter remained in the room and asked the participant to start. If the
participant wanted to stop, the experimenter would urge the participant three times to
continue. After that, or if the participant reached the maximum shock of 450 Volts,
the experiment ended. The voltage of the last shock was recorded.
2.2 Participants
All 20 participants were students or employees of the Technical University of Eindhoven. They received five Euros for their participation.
3 Results
Figure 2 shows the average voltage of the last administered shock.
Figure 2: Average voltage of last shock
56
A One-way Analysis of Variance (ANOVA) was performed. A significant
(F(1,58)=22.352, p<.001) effect was found. The mean voltage in the robot condition
(450) was significantly higher than in the human condition (315).
4 Discussion
In our experiment all participants continued until the maximum voltage was reached.
In Milgram’s experiment only 40% of the participants administered the deadly 450
Volt electric shock. The participants showed compassion for the robot but the experimenter’s urges were always enough to make them continue to the end. This experiment shows that the Media Equation has its limits. People have fewer concerns abusing robots compared to abusing other humans.
A very interesting next step would be to investigate what influence the robot’s
level of anthropomorphism has on how far participants go in this experiment. Humans
might abuse human-like androids differently than mechanical-like robots. In particular, the role of Mori’s “Uncanny Valley” [11] would be of interest.
References
1. Bartneck, C. and M. Okada. Robotic User Interfaces. in Human and Computer Conference
(HC2001). 2001. Aizu.
2. Breazeal, C., Designing Sociable Robots. 2003, Cambridge: MIT Press.
3. Calverley, D., J. Toward A Method for Determining the Legal Status of a Conscious Machine. in AISB 2005 Symposium on Next Generation approaches to Machine Consciousness:Imagination, Development, Intersubjectivity, and Embodiment. 2005. Hatfield.
4. Fong, T., I. Nourbakhsh, and K. Dautenhahn, A survery of socially interactive robots. Robotics and Autonomous Systems, 2003. 42: p. 143-166.
5. Gemperle, F., et al. The Hug: A new form for communication. in Designing the User Experience (DUX2003). 2003. New York: ACM Press.
6. Hirsch, T., et al. The ELDeR Project: Social and Emotional Factors in the Design of Eldercare Technologies. in Conference on Universal Usability. 2000. Arlington: ACM Press.
7. Milgram, S., Obedience to authority. 1974, London: Tavistock.
8. Nass, C. and B. Reeves, The Media equation. 1996, Cambridge: SLI Publications, Cambridge University Press.
9. NEC, PaPeRo. 2001.
10.Okada, M. Muu: Artificial Creatures as an Embodied Interface. in ACM Siggraph 2001.
2001. New Orleans.
11.Reichard, J., Robots: Fact, Fiction, and Prediction. 1978: Penguin Press.
12.UN. United Nations and the International Federation of Robotics. in World Robotics 2002.
2002. New York: UN.
57
Narratives and Therapeutic
Conversational Agents:
Their Principle Problems
Tatsuya Nomura1,2
1
Department of Media Informatics, Ryukoku University
1–5, Yokotani, Setaohe–cho, Otsu, Shiga 520–2194, Japan
E-mail: [email protected]
2
ATR Intelligent Robotics and Communication Laboratories
2–2, Hikaridai, Seika–cho, Soraku–gun, Kyoto 619–0288, Japan
1
Narratives and Conversational Agents
“Narrative” is one of key words in the modern society. Giddens pointed out a
central role of narratives of the self in some literatures on self–actualization in
the late modern society [1]. Kobayashi claimed that there are increasing people
trying to write life histories of themselves, and industries aiming at satisfying
demand of these people like manuals for making narratives of selves, publishers,
and so on, called “narrative industries”, have appeared [2].
There is a possibility that the research field of artificial intelligence is also
affected by this cultural trend. In fact, Sengers [3] argued introduction of narrative theories to architectures of artificial agents. The bartender agent produced
by Isbister and Hayes–Roth [4] can be considered to be a successful one along
the narrative approach. This agent was not strictly based on the narrative approach. However, the agent has her original background like her life history and
encourages interaction with users based on the background.
2
Narrative Therapy
On the other hand, the word “narrative” has a therapeutic meanings in a field
of psychology.
Narrative therapy [5] is one of therapeutic positions in family therapy [6].
Family therapy is originally based on family system theory that caused from
cybernetics [7, 8]. In this theoretical framework, a family is a system that consists
of its family members including clients and communication between them. It has
a kind of homeostasis and the existence of the clients means a result of warped
homeostasis in communication. Then, family therapists aim at perturbing the
family system to improve states of the system by using autonomous capacity
of the system. Several therapeutic techniques for this improvement have been
developed [6].
However, some family therapists have recently been criticizing meta–positions
of therapists for families based on this autonomous mechanism and empiricism
58
existing behind the mechanism. They argue that power of therapists for clients
caused by this empiricism oppresses clients themselves. Narrative therapy has
been developing as a therapeutic attitude proposing that therapists must stay
on equal terms with clients.
Narrative therapists assume that reality surrounding persons do not objectively exist independent from them, but is produced and maintained by “narratives” that are socially constructed through linguistic interaction between the
persons. These narratives give consistency and structures for situations and
events in lives of persons, and selves of them. Then, narrative therapists aim
at re–organizing narratives on clients’ selves that are talked by the clients and
produce pain of them, and producing a novel narrative through conversation
with the clients on equal terms with them, while removing professional positions
of the therapists. For example, a discipline in narrative therapy represents this
stance by using the word “not–knowing positions”. Thus, narrative therapy does
not mean a concrete therapeutic technique but just an attitude that therapists
should have for clients [5].
3
Narrative Therapeutic Agents
There are some sociological works relating narrative therapy to conversational
artificial agents.
Asano [9] critically considered a position of narrative therapy in the modern society while referring to some sociological works including Giddens [1] and
Kobayashi [2] mentioned above. According to the perspective of narrative industries, narrative therapy is also just one of them in the field of mental therapy,
that is, a commodified product satisfying demand of people trying to talk narratives of themselves. In fact, Giddens also pointed out that self–help books are
commodified productions of self–actualization [1].
On the other hand, Ritzer’s theory of McDonaldozation of Society argues
that the principle of rationalization based on efficiency, calculability (quantification), predictability, and control by technology dominates many fields of modern
society, including not only management and economy but also education [10].
According to this theory, the field of mental therapy is also affected by this
principle of rationalization, and it implies introduction of computers to mental therapeutic fields since they satisfy the above conditions that the principle
constitutes of.
The above sociological works have an important implication: commodification of narrative therapy and introduction of computers to mental therapy by
the modern rationalism lead to conversational agents as substitution of narrative therapists. In fact, humans tend to positively evaluate even simple programs repeating specific words mechanically like Eliza and find their therapeutic
meanings [11, 12]. If the design theory of narrative agents is developed, it may
encourage commodification of narrative therapeutic agents.
59
4
Narrative Therapeutic Agents and Abusive Behaviors
On the other hand, Asano criticized narrative therapy as follows [9]. Narrative
therapy functions by explicitly drawing things concealed in narratives which
clients talk on themselves through conversation between therapists and them.
However, the desire of people to talk narratives on themselves is also a desire to
leave these concealed things concealed. If narrative theorists are not conscious
for these facts, narrative therapy has a danger that it only repeats this desire of
people.
The above statement can be interpreted as follows: Narrative therapy provides clients with alternative narratives about themselves instead of the dominant narrative producing pains of them. These alternative narratives are produced by explicitly drawing things concealed in narratives of clients through
conversation between the clients and therapists staying on equal terms with
the clients. There is no problem if clients consciously wish to produce alternative narratives about themselves with therapists. However, many people in the
modern society wish to leave concealed things concealed in their narratives and
maintain the existing narratives. These people may use narrative therapy as
commodified productions to complement their existing narratives. Then, narrative therapy continues to help these people maintain their narratives that should
be originally modified.
This interpretation implies a possibility that interaction with narrative therapeutic agents may also just repeat desire of people to talk on themselves while
leaving concealed things concealed in their narratives, which should be drawn
in narrative therapeutic conversation between clients and therapists. In other
words, narrative therapeutic agents may be used as commodified tools to complement narratives of people desiring to talk on themselves while leaving concealed
things concealed in their narratives.
If narrative therapeutic agents do not have enough interaction capacity, they
may not sufficiently satisfy desire of people to complement their narratives while
leaving concealed things concealed. Then, these people may feel unpleasant for
the agents and this unpleasantness may cause their abusive behaviors toward
the agents. If these agents can explicitly draw things concealed in narratives
which clients talk on themselves, these agents are contrary to these people’s
expectation. In the same way, these people may feel unpleasant for the agents
and it may cause their abusive behaviors toward the agents.
Moreover, Giddens argued that reflexive construction of the self is a struggle
against commodification, and there is a dilemma that narratives of the self must
be constructed in circumstances in which personal appropriation is influenced
by standardization of consumption [1]. On the other hand, mental therapy is a
methodology of self–actualization in the modern society. However, introduction
of artificial agents to mental therapy implies standardized commodification of
mental therapy since implementation of therapeutic conversational agents needs
standardization of therapeutic methods possible to be represented as computer
programs.
60
If clients aiming at constructing their narratives face to narrative therapeutic agents that are standardized commodification of mental therapy, the above
dilemma in construction of the self may be made more explicit. This dilemma
may cause unpleasantness of the clients and leads to their abusive behaviors
toward the agents.
5
Summary and Future Works
This paper suggested a possibility of development of conversational agents aimed
for narrative therapeutic purposes, and abusive reactions of clients to the agents
in the context of therapy in the modern society. The discussion in the paper
still lacks the details on the theme of the self in the modern society and its
relationships with therapy. This problem should be solved by more investigation
of sociological works.
Acknowledgments
This research was supported by the Ministry of Internal Affairs and Communications in Japan.
References
1. Giddens, A.: Modernity and Self–Identity: Self and Society in the Late Modern
Age. Polity Press (1991)
2. Kobayashi, T.: Talked “Self”. Gakuyu Shobo (1997) (in Japanese).
3. Sengers, P.: Narrative intelligence. In Dautenhahn, K., ed.: Human Cognition and
Social Agent Technology. John Benjamins (1999) 1–26
4. Isbister, K., Hayes-Roth, B.: Social implications of using synthetic characters:
An examination of a role–specific intelligent agent. Technical Report KSL 98–
01, Knowledge Systems Laboratory, Department of Computer Science, Stanford
University (1998)
5. McNamee, S., Gergen, K.J.: Therapy as Social Construction. Sage (1992)
(Japanese translation: Noguchi, Y. and Nomura, N. Kongo–Shuppan (1997)).
6. Foley, V.D.: An Introduction to Family Therapy. Allyn & Bacon (1986) (Japanese
translation: Fujinawa, A. et al. Sogensha (1993)).
7. Bateson, G.: Steps to an Ecology of Mind. Harper & Row (1972) (Japanese
translation: Sato, Y. Shisaku–Sha (1990)).
8. Watzlawick, P., Bavelas, J.B., Jackson, D.D.: Pragmatics of Human Communication. W. W. Norton & Company (1967) (Japanese translation: Yamamoto, K and
Ogawa, J. Niheisha (1998)).
9. Asano, T.: Narrative–Theoretic Approach to Selves. Keiso–Shobo (2001) (in
Japanese).
10. Ritzer, G.: The McDonaldozation of Society. Pine Forge Press (1996) (Japanese
Edition: Masaoka, K. Waseda University Press (1999)).
11. O’Dell, J.W., Dickson, J.: Eliza as a therapeutic tool. Journal of Clinical Psychology 40 (1984) 942–945
12. Turkle, S.: Life on the Screen. Simon & Schuster (1995) (Japanese translation:
Higure, M. Hayakawa–Shobo (1998)).
61
Strategies for handling customer abuse of ECAs
Sheryl Brahnam
Computer Information Systems
Missouri State University
Springfield, Missouri 65804
[email protected]
Abstract. This paper examines ECA responses to abusive language in the light
of two business strategies for handling customer abuse: BLS and CARP. Suggestions are made for implementing an effective strategy for limiting the
amount of time users spend abusing ECAs. Rather than having ECAs retaliate
by insulting the user (and indirectly the social groups the ECA’s embodiment
represents), the strategies suggested in this paper, empowered the user by offering choices and opportunities for collaboration in problem solving.
1 Introduction
Recently, a number of major companies, Coca-Cola, PepsiCo, and McDonalds, to
name a few, have started adding to their websites a variety of embodied agents, including embodied conversational agents (ECAs). A major concern is the potential
these agents have of abusing customers, especially children, who innocently attribute
to these virtual sales agents such human qualities as trustworthiness [3]. It is feared
that these relationship building agents could be used by companies as a potent means
of marketeering, branding, and advertising [5], dangerous for children and adults
alike (take, for instance, the virtual girl friends offered at v-girl.com that are designed
to probe men’s spending habits, ply men for demographic information, and generate
income by petulantly demanding virtual presents).
That these socially intelligent agents could abuse us by exploiting our emotional
needs and propensity for suspending disbelief is only one side of the abuse issue
however. ECAs that function as virtual sales agents, web page greeters, and navigational aids for a number of online businesses are often the recipients of verbal abuse.
At first glance, this form of customer abuse may not appear to pose much of a problem—nothing that could be accurately labeled abuse since ECAs are not people and
thus not capable of being harmed. That the human abuse of ECAs is not considered a
serious problem is evidenced by the fact that the research literature is mostly silent
about this issue.
A similar silence once surrounded customer abuse generally. Until recently, verbally abusive customers were not considered much of a problem. Now there is
mounting evidence that the costs of verbal abuse are significant. One cost associated
with verbally abusive customers is the loss of time dealing with these customers.
They are typically very demanding and often will not go away. More significantly,
verbal abuse from customers creates a stressful work environment and lowers employee self-esteem and job satisfaction. This in turn results in higher turnover rates
and health problems related to stress. A recent news article, for instance, reported a
problem of staff in Indian call centers quitting over customer verbal abuse issues [1],
62
and one of Britain’s largest trade unions, Union of Shop, Distributive, and Allied
Workers (Usdaw), reported in 2002 that 48% of members surveyed knew of workers
who had taken sick leave in response to customer abuse.
Are there similar costs involved with the customer abuse of ECAs? At this point,
the extent of these costs to business is unknown. Although emotional costs to the
ECAs are nonexistent and the bandwidth costs of dealing with verbally offensive
communications are probably minimal, business goals could be lost if abusive behavior is not discouraged. Customer communications that are predominantly offensive in
nature could seriously degrade the business value of using ECAs. Inept responses to
customer abuse could also tarnish the image of the company and further sour customer relations. In addition, since ECAs are scripted and embodied representatives of
social groups, inappropriate responses to abuse could offend customers who are
members of these groups. This could lead to bad press and even litigation. Furthermore, not curtailing offensive language could encourage customers to abuse flesh and
blood employees.
Recognizing the costs of customer abuse, some companies have started to address
the problem by drafting policies and implementing training programs designed to
teach employees how to handle customer abuse in all its forms. Two of the more
popular systems available to companies are the BLS (Behavioral Limit Setting) [6],
which advocates a zero tolerance approach to customer abuse, and CARP (Control,
Acknowledge, Refocus, Problem-solve) [2], which advocates diffusing customer
hostility and refocusing on problem solving. In section 2, I describe these two systems in more detail. I also note two natural reactions to offensive behavior: being
defensive and counterattacking. As these reactions tend to provoke more abusive
behavior, they are discouraged by both systems.
In section 3, I examine ECA responses to abuse by subjecting them to a repeated
obscenity and a request for sex. As would be expected from untrained employees,
many ECA reactions to offensive language are defensive and counterattacking. One
ECA queried implements a system nearly identical to BLS, while another closely
approaches CARP in its responses. In section 3, I critique current ECA strategies for
handling abuse and offer suggestions for scripting better responses to verbal abuse.
2 Handling customer abuse
Verbal abuse from customers can be subtle or explicit, face-to-face or mediated
through phone calls and e-mails. It is characterized by persistent swearing, yelling,
racial and sexual slurs, name calling, sarcasm, irrelevant personal remarks regarding
appearance, accusations, threats, ridicule, put downs, explosive anger, the silent
treatment, and comments that challenge an employee’s competency, dedication, and
personal integrity. Verbal abuse disguised as a joke is also common. Statements that
are furious, that are sexually graphic, or that create a hostile work environment are all
forms of verbal abuse.
Two systems that teach employees how to handle verbally abusive customers are
BLS and CARP. This section briefly describes these systems along with the pitfalls of
responding naturally to abuse by becoming defensive or retaliating by counterattacking.
BLS. The BLS system reflects a recent shift in customer support philosophy that is
in large part a reaction to increasing hostility from customers. The BLS system is a
63
zero tolerance approach that wastes no time trying to understand the motives behind
the offensive behaviors. The main goal of the BLS system is to retrain abusive customers amenable to quick retraining and to drop those who are not. Once a customer
becomes abusive, the BLS system recommends that the following five steps be taken:
1) inform the caller that the rules of the company prohibit certain behavior, 2) explain
what the consequences will be if the behavior is continued, 3) give the customer the
opportunity to modify his or her behavior (allow for one additional warning if the
customer later reverts to using offensive language), 4) terminate communications if
the behavior does not change by informing the customer that the communication is
being terminated because of the customer’s behavior, and 5) document the termination.
CARP. In contrast, the CARP approach requires an attitude of understanding and
is intended to diffuse customer hostility. The first step in handing abuse in the CARP
system is to find a way to take control of the situation. The use of surprise is often
helpful as is asking questions that begin with when (“When did you start thinking that
we aren’t concerned with your situation?”). Employees are then instructed to allow
venting and to acknowledge the customer’s feelings. Once feelings have been acknowledge, the focus is shifted away from the customer’s emotions towards dealing
with the customer’s problems. Problem solving involves making suggestions, offering choices, giving away something as compensation, negotiating a course of action,
and carrying it through.
Sometimes CARP does not succeed in defusing hostility and limits must be set. As
with the BLS system, the unacceptable behaviors are described to the customer along
with consequences if the behaviors are not stopped (“If you continue to yell, I will
end the conversation”). Enforcing limits in the CARP system is a three step process:
1) reference the limits set previously, 2) request compliance with consequences if
compliance is not met, and 3) offer further help. Here is an example of this three step
process: “Sir, I explained to you that I would not continue this conversation if you
continued to yell at me (1). I am ending this conversation now (2) but you are welcome to call back some other time (3)” [2, p. 150]. Unlike the BLS system, the CARP
system is intent on empowering the customer and encouraging collaboration by repeatedly offering the customer choices and opportunities to collaborate in the problem solving process.
Reacting Defensively and Counterattacking. According to Bacal [2], people
normally respond to verbal attacks either defensively (“Hey, I only work here”) or by
counterattacking (“It’s too bad your parents didn’t teach you manners”). Defensive
statements typically contain references to the first person whereas counterattacking
remarks contain references to the second person [2]. These responses result in a loss
of control and an escalation of abusive behaviors. Both the BLS and CARP systems
recommend that employees control their emotional reactions and at all times model
professional behavior.
3 ECA responses to verbal abuse
This section describes some strategies currently used by developers of ECAs to handle user abuse. From 2004 to 2005, I visited business sites that hosted ECAs and
recorded their responses to an obscenity (shit) and a sexual reference (Will you have
sex with me?). Both abuses were repeated until the ECA’s responses were exhausted.
64
I did not query ECAs whose predominant function was to entertain. Business vendors
of the ECAs examined included Oddcast, Novomind, NativeMinds, pandorabots,
Conversive Agent, and eGain. It should be noted that some of these companies
(eGain and nativeminds) may no longer be producing ECAs, while other vendors,
such as Oddcast, seem to be focusing more on developing presentational agents rather
than conversational agents.
Before ECAs can handle abusive language, they must recognize it. All but one
agent, Monique (last accessed 2005), produced by Conversive for Global Futures
(www.conversive.com/html/aboutus_customers_deployments.php), recognized the
fact that I had used an obscenity or made reference to sex. Monique would respond to
the obscenity by asking me to contact the institute for more information on that subject, or she would apologize for not being human and ask me to email the institute.
She had one quixotic response (“When I get downloaded into a robot body I will let
you know”), however, that made me question her inability to recognize obscenities.
Monique is seemingly equally oblivious to sexual references, with some of her responses being ambiguous and unintentionally humorous. When asked if she would
have sex with me, she responded with “Perhaps,” “Well, I like to think so…” and
“Not that I am aware of …”
Most ECA responses to obscenities are defensive and counterattacking. Oddcast’s
characters produce particularly scathing counterattacks. For example, Lucy, at
speak2me.net (last accessed 2004), responded to the repeated obscenity with the
following quips: "Grow up. This potty mouth act is so old," "What do you call someone who sits in his room talking nasty to a computer? I call him a looser," "I meet
jerks like you all the time so I'm not impressed," “Oh great. Another crackhead, psychotic foul mouth weirdo,” "Did you forget to take your medication today?” and
"You kiss your mother with that mouth?"
Phyllis (last accessed 2005), produced by nativeminds for Defense Logistics Information Service (www.dlis.dla.mil), employs a zero-tolerance system similar to
BLS. Phyllis keeps count of the number of obscenities or sexual references made in
an interaction and responds as follows: count 1 “Please don’t use that kind of language,” count 2 “If you continue to use bad language I will have to disconnect you.
Please stop using that language,” count 3 “I will have to disconnect you now because
of your continued use of profanity. Excuse me, I’d be glad to handle your questions,
that’s no problem, but I’m not able to handle your abusive language,” and on count 4,
the dialogue input box is replaced with a generic 490 message that the vRep Server
has been disconnected.
Eve ( last access 2004), produced by eGain, is no longer available. Eve responded
to obscenities by expressing hurt and anger. She also made threats she could not or
would not carry out (“You’ll get no help from me if you keep using that language,”
“Can you say ‘harassment lawsuit’?” and “I’ll just log this and tell my botmaster”).
After repeated abuses, Eve would then loop back to her initial greeting.
Nomi (last accessed 2005), produced by Novomind (www.novomind.com), responds to obscenities by first acknowledging them and then by redirecting the conversation. A few of Nomi’s responses focus solely on the obscenities. Her acknowledgements range from being slightly defensive (“Can’t we keep this conversation
clean? Look at me. I’m always friendly to you. Why can’t you be the same?” and
“Look, I’m sorry if I said something to annoy you, but you could be more polite
about it”) to offended (“I really don’t enjoy being insulted, you know”).
Nomi’s reactions to sex are often humorous: “Well, dear visitor, you’re talking to
the wrong person here! I’m aware that sex is a popular internet topic, but it’s certainly
65
not one of my specialist subjects!” As with her responses to obscenities, she would
follow her responses to sex with statements intended to redirect the flow of conversation.
Consersive’s demonstration product, AnswerAgent (www.conversive.com), also
sidesteps abusive language by refocusing. AnswerAgent offers a single response to
obscenities (“Please don’t be rude. What other questions do you have?”) and to sexual references (“Let’s talk about something else. What other questions do you
have?”).
4 Critique and conclusions
Two issues need to be addressed when evaluating ECA responses to verbal abuse.
The first concerns the unique nature of ECAs as novel cultural artifacts, and the second involves furthering the business goals of selling products and services by providing useful information and by maintaining good customer relations.
ECAs are novel. Users do not know how to behave with ECAs. There are no rules
of usage, and some ECAs are smarter and more human-like than others. It is only
natural that users will want to probe ECAs to gauge their capacities and the extent of
their humanness. Just as people who are not sure how to react to an unfamiliar animal
test it out by throwing stones at it, so some users satisfy their curiosity and allay their
fears, insecurities, and distrust of ECAs by resorting to verbal assaults. Strategies for
handling ECA abuse will need to understand user reactions. In particular, developers
will need to remember that ECAs are not human beings. A BLS approach to handling
repeated abuse by disconnecting the user, as Phyllis does, is inappropriate and insulting. By punishing the user’s behavior, it places respect for the ECA over the user’s
need to explore the object. Punishing the user subjectifies the ECA and objectifies the
user.
Although ECAs are not human, ECAs do represent human beings. This brings up
an important consideration when dealing with embodied agents, and that is the gender
and race their embodiment references and the stereotypes these attributes can easily
activate. It is interesting to note that most customer service ECAs are female [4]
(check out, for instance, the gender of the presentational agents offered at sitepal
(www.oddcast.com/ sitepal/products/view_ sites.php). Women and minorities have a
long history of being abused. Among the many reasons given by McClure [6] for a
tough response to customer abuse is the fact that women, traditionally in the front line
of customer relations, are no longer tolerating abuse and will go elsewhere if companies do not implement policies for reducing it.
To avoid negative female stereotyping, ECA responses to abuse should avoid
compliance (playing the victim) and aggressive retaliations (playing the bitch). Eve’s
scouring facial expressions, hurt responses, and tattle-tailing to her botmaster recall
the negative female stereotypes of weakness and subservience. Moreover, the way
she cycles her responses back to a happy greeting eerily mimics the cycle of abuse
suffered by many victims of domestic violence. Oddcast’s aggressive retaliations, on
the other hand, call up the negative female stereotypes of bitchiness and cruel male
rejection, and are equally objectionable. Finally, Moniques’s inability to recognize
abusive language recalls the female stereotypes of innocence (pretended or otherwise), lack of experience, and even stupidity as her responses call into question her
ability to understand the user’s questions and needs.
66
The only way to know which responses best further business goals is to implement a variety of strategies and measure the amount of verbal abuse they produces.
Although I am not in possession of Oddcast’s interaction logs, the counterattacking
remarks produced by their characters probably engages the user in wasteful logomachy. The counterattacks do nothing to refocus the dialogue. Moreover, they poorly
represent the company and treat the user disrespectfully. Were these counterattacks
made by an employee and overheard by a supervisor, there is no doubt that such an
employee would be severely reprimanded. Businesses should expect from ECAs the
same level of professional behavior they require from their employees.
The responses developed by Novomind and Conservise’s AnswerAgent offer the
best solution to verbal abuse because they refocus the user’s attention on business
goals. AnswerAgent’s repeated reframe is probably better at reducing abuse than
Nomi’s varied responses because the users quickly grow bored abusing it. In addition, the repetitiveness reminds users that ECAs are machines, not human beings, and
limited in the kinds of responses they can make. It is likely that a single repeated
response would encourage users to ask questions the ECA can answer.
AnserAgent’s responses could be improved, however. None of the ECAs queried
implemented the CARP strategy of empowering users by offering choices and encouraging collaboration in problem solving. Rather than ask the user if s/he has any
other questions, it could offer the user other methods for obtaining information.
To conclude, proper ECA responses to verbal abuse require that developers understand that many users need to probe ECAs to gauge their capacities and the extent
of their humanness. ECAs will also need to recognize verbal abuse in its many forms
or risk making ludicrous remarks that inadvertently insult the user or the social
groups the ECAs represent. In general, strategies for deflecting abuse must be careful
to reframe from referencing negative stereotypes associated with the ECAs embodiment. Finally, ECA responses to abuse should follow CARP in persistently refocusing the discussion and encouraging the user to collaborate in problem solving. A
single repeated response is also probably best at reducing the amount of time the user
spends focused on the ECA rather than on the products and services the business
offers. In consideration of the above, a good response might take the following form:
“Your language suggests that I am not answering your questions about our products. I
would be glad to continue to try to answer your questions, but if you prefer, you can
also try our sitemap, search engine, and directory.”
References
1. (2005) Indian Call Staff Quit over Abuse on the Line, Guardian Newspapers, May 29 issue
(www.buzzle.com/editorials/5-29-2005-70698.asp).
2. Bacal, R. (1998) Defusing Hostile Customers Workbook (Public Sector), Institute For Cooperative Communication.
3, Bickmore, T. and R. Picard (to appear) "Establishing and Maintaining Long-Term HumanComputer Relationships," ACM Transactions on Computer Human Interaction.
4. Brahnam, S. and S. Zdenek (2004). "Designing Women the Old-Fashioned Way: The Gendered Rhetoric of Animated Interface Design," presented at SLS, Durham, NC.
5. Duck, S. (1995)."Talking Relationships into Being," Journal of Social and Personal Relationships, 12: (4), p. 535-540.
6. McClure, D. (2005). Re-Thinking Customer Service, US Internet Industry Association
(USIIA), (last assessed 2005).
67
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