Bulletin, February/March 2006
Plenary Session II
Just-in Time-Information: Is It in Your Future?
by Irene Travis
Irene Travis is the
editor of the Bulletin of the American
Society for Information Science and Technology. She can be reached at
is “proactively offering information to a user that is highly relevant to what
s/he is currently focused on.” Pattie Maes of the MIT Media Laboratory’s
Ambient Intelligence Group offered this definition of her work in an address to
the second plenary session at the ASIS&T Annual Meeting in
desktop environment Maes has explored how we can give users information
pertinent to whatever they are doing in an application. Similarly, for people on
the move she asks: How might we give people relevant information about others
they are meeting for the first time? How could we give tourists
location-specific information about things of interest around them, such as
restaurants, shops or points of interest? In short, the purpose of just-in-time
information is to promote “insight, inspiration and interpersonal
connections” without interrupting the user’s activities. The goal is
something less disruptive, Maes explained, than “Please excuse me a moment
while I Google you.”
How to Offer Just-in-time
information systems, Maes noted, must model user interests/preferences, sense
the current context of the user, compute information relevant to the context and
user profile (recommendation algorithm) and present information in subtle,
non-intrusive ways. The early systems for the desktop had functions such as
recommending, remembering, mentoring and match-making, while in later systems
information is triggered by such factors as location or objects with embedded
electronic identification that are being handled or looked at.
example, the ReachMedia Project, carried out by Assaf Feldman, Sajid Sadi in
2005, explores on-the-move interaction with augmented objects. The user wears a
wristband that contains a wireless radio frequency identification (RFID reader)
such as those used to track packages. The wristband reads RF tags in objects the
user holds. Touching an object results in a menu of services and information
being displayed on the screen of a smart phone. For example, picking up a tagged
book on a friend’s coffee table connects your smart phone to a server and lets
the server know that you picked up that book. The server can then proactively
look for and transmit potentially useful and personalized information, such as
reviews, to you. With a hands-free option, the system can offer information in
auditory form, so you can listen to information and review services about the
book while you are holding it. Under the system you could also navigate through
opportunities by using gestures processed by accelerometers on the wristband,
including navigating menus with gestures.
included many other examples in her talk of both desktop and on-the-move
applications. Brief descriptions of them are available at http://interact.media.mit.edu.
next reviewed the many technical challenges of just-in-time information
provision. It will work, she said, if the information is likely to be relevant
to the user, but the challenges are user profiling, detecting user context and
recommendation algorithms. Likewise, it will work if it is offered
unobtrusively, which requires subtle interfaces. Finally it must also provide
minimum user effort to access, which requires natural “on-the-move”
at these challenges individually, user modeling may be done by having the user
give the information to the system explicitly, by the system gathering it
implicitly by data mining the users’ observed behavior or their personal
texts, such as homepages – or by some combination of methods.
context – the who, what, where and when of the user’s situation – is approached differently on the
desktop and the physical environment. On the desktop the program can sense
actions in different applications, but in the physical world, offline, the
system must rely on sensors in the environment or on the user. It may also
require background knowledge and inferencing to differentiate, for example, the
information that would be useful when you shake the hand of a new acquaintance
for the first time (creating connections, breaking the ice) as opposed to when
you shake hands with someone you know well (circumstances and subjects of your
systems can be created using a range of approaches including those based on
case/prototypes, features of the content (patterns in content), collaborative
filtering patterns among users).
subtle, natural interfaces require either secondary input/output modalities for
the user, such as peripheral vision or audio, or they require seamless
integration in an existing interface, such as cell phones, in a minimal way. The
goals are always to avoid the user having to change focus or be interrupted, to
have the recommendations be proactive but easily ignorable, to avoid additional
gear/devices/windows and to support “on-the-move” access to details.
In addition such interfaces should offer “ramping” – presenting
minimal “hints” that a user can ignore while also allowing users to control
access to more detail.
user interface lessons learned, Maes concluded, include that transparency is key
since it leads to trust, that systems must avoid making people dependent on them
or producing ”tunnel vision” and all systems must protect the user’s
privacy despite being based on user profiles.
In summary, Maes stated, the goal of her
research group is to rethink user-information interaction by proactively
offering just-in-time information, highly relevant to unique users and their
current focus of attention in a non-disruptive, easily accessible way.
members raised several questions. Regarding the potential to teach students
about the ethical implications of their work, Maes noted that though there are
no classes devoted to the topic, ethics is part of the conversation about
her projects and the technology. Responding to a question about security, Maes
noted that decentralized information is essential.
system dependence, she stressed helping people to find information – as
opposed to finding it for them – and integrating recommendations into systems
that the user already uses. For example, her group tried to build a personalized
newspaper – but it creates a huge tunnel vision problem. Instead one would
want a newspaper that is augmented. The
paper is the same for everyone, but includes an individualized highlighter for
response to a final question on scalability, Maes observed that they didn’t
think much about it in a university laboratory environment, but she did comment
on how surprising it is what can be done with the equipment people already have,
particularly cell phones.
Pattie Maes may be reached at pattie<at>media.mit.edu.
Articles in this Issue
Just-in-Time Information: Is it in Your Future?