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Chapter 18
Future Trends for
Conversational Agents
Diana Pérez-Marín
Universidad Rey Juan Carlos, Spain
Ismael Pascual-Nieto
Universidad Autónoma de Madrid, Spain
ABSTRACT
In the last decades, there has been a great evolution in the field of Conversational Agents. Currently,
there are agents to assist the navigation in Web pages, support elder users when interacting with some
computer application to remind them which medicines they should take during the day, or to enhance
the learning process by allowing students to review with systems that adapt themselves to their previous
knowledge and rhythm of study. In this chapter, the goal is to provide a summary of the future trends
that can be envisaged for the future of the field. It is our insight that the future of Conversational Agents
are to become pervasive and natural in our daily lives.
INTRODUCTION
Fifty years ago, computers were complex machines
that occupied rooms and required a vast amount
of technical knowledge to be used. Therefore,
only a small amount of people could interact with
them. Furthermore, users could only communicate
with the computers via a very restrictive interface.
There was a list of commands with their set of
options that should be placed in the exact order
DOI: 10.4018/978-1-60960-617-6.ch018
in order to command the operation requested to
the program.
There has been a great evolution both in the
hardware and software aspects of Computer
Science since then. While the hardware is being
made smaller and more potent, the software is
being made friendlier and less dependent on the
technical knowledge of the user. Menu-based
interfaces have mostly replaced the list of commands. That way, users do not need to memorize
the commands. They choose the action to perform
by clicking on the menu.
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Future Trends for Conversational Agents
Nevertheless, the interaction based on the use
of menus can also be regarded as quite restrictive.
All in all, users are limited to request the computer
one of the enlisted actions with the options of the
panels. Moreover, if the users ignore in which
menu an option is, then they will not be able to
perform it.
Natural Language Interaction is studied in this
book as the possibility of interacting with computers in natural language. That way, users could
request the tasks to perform with their computer in
the same way than they talk to their colleagues at
work. It would not longer necessary to learn lists
of commands or where they are placed in a menu.
Conversational agents are programs that interact with the users in natural language. They can
be executed in any type of computers (including
laptops and netbooks), smartphones or PDAs.
These agents are currently being used as assistants
to make the navigation in Internet easier, to book
travels on-line, remind which medicines to take, do
the homework, or attend some customer petitions.
The advantages are many: the agents can work
24 hours per day, all the days of the year, they
do not get tired or impatient, and they could be
adapted to treat all the people in the same way, or
depending on the information previously stored
of their profiles, so that they provide exactly what
each user needs. In fact, according to Fairclough
(2009), the next generation of intelligent technology will be characterized by increased autonomy
and adaptive capability.
For the future of Conversational Agents, the
advances in Natural Language Processing will
keep being crucial. The research into new techniques and algorithms can allow the systems to
understand better the sentences provided by the
users, and to respond with more elaborated and
different constructions as humans would answer
to those petitions.
Furthermore, and according to Erwin Van Luhn
from Chatbots.org and highlighted in chapters 9
and 17 of this book, the future of conversational
agents encompasses more than just the correct
396
understanding and generation of words; it will
be about understanding emotions too. Conversational agents could become then part of the users’
everyday life. The agents would be available on
demand just by calling out their names as emphatic
characters, understanding the users’ lifes, feelings,
situation, friendships, history and anticipating like
a human would do.
Conversational agents can also have an
animated face with or without body. In that case,
they are called Embodied Conversational Agents
(ECAs). Currently, according to López-Mencía et
al. (chapter 3), we are just beginning to understand
how ECAs affect the perceptions of users, upon
which the most appropriate design of the ECA’s
behaviour ultimately depends (Gratch et al., 2006;
Edlund & Beskow, 2007). Therefore, it is necessary more research in that line, and it would also
be interesting to research the application of ECAs
for biometric applications (Krämer et al., 2009).
The chapter is organised as follows: firstly,
the future trends on more sophisticated Natural
Language Processing, humanising the agents and
their pervasiveness are summarised. Next, the
chapter is focused on the domain applications and
their potential users. Finally, the main conclusions
drawn are presented.
TRENDS
More Sophisticated Natural
Language Processing
Natural Language Processing (NLP) has been
researched since 1950s. Originally, the goals were
very broad such as automatic translation of any
text from any language to any other language.
However, the lack of resources and hardware ended
with the feeling that it was a task too difficult to
accomplish. Therefore, more realistic and specific
goals were established, such as to recognize entities in the text or to answer questions.
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