Social Interface Agents

Lynne Hall

Overview

What are Social Interface AgentsWhy evolution is neededThe agent community and GUISocial Interface Agent CharacteristicsSocial Interface Agents - from inception

to releaseSome thoughts for the future

Social Interface Agents

Software agents are software entities that do something on behalf of someone else in or through a computational environment

Interface agents are software agents that are tangible and visible at the interface level

Social Interface agents are interface agents that interact with the user in a social manner

Direct Manipulation / GUI Use Characteristics

Professional UserComputer literateWell structured task domainWell organised information domainDisplay lends itself to visualising all of the

different dimensionsComprehensible, predictable and

controllable interactions

Microsoft Powerpoint

New Use Characteristics

Untrained end usersLow levels of computer literacyNovel tasks with poor organisationIll-structured, dynamic information

domainDifficult to visualise information using

traditional GUI

Why is there a need for change?

Real limits for potential of information visualisation and direct manipulation

Computing environment becoming more complex

Users no longer trainedImmediacyNeed for assistance to be given to users

in a tangible, relevant, timely manner

A little history...

Origins within AI crossed with DAI extended by HCI, eagerly awaited by the net, altered by commerce and technological capability

Three principle interest groups: Agent community (AI led) Interaction designers Web Requirements

Agent Visibility

User Interface level users want to be in control need for predictability

Sub- User Interface level high utility of filtering agents adaptivity positive unless it interferes with user’s

interactionMost successful agents are the invisible ones

(currently)

Improving GUI...

Increase in automation Work - amplifies productivity of users Home - increase in disposable time

Increase user capabilities in task performancePreserve user’s sense of controlEnsure user’s sense of responsibilityIncrease the satisfaction of the user

experience

Design Issues

Extending Shniederman’s principles Principle of virtuality

representation of reality that can be manipulated by an actor selected by the user or by the user themselves

Principle of transparencyuser is able to apply intellect directly to the task, the

actor [tool] itself seems to disappear

Feeling of involvement directly with a world of actors and objects

Characteristics

Personalised - tailored to each individualProactive - can take initiative as it knows

what the user wantsPersistent - continue to run even when

user not presentAdaptive - change as user changesActs on your behalf whilst you are doing

other things

Characteristics 2

Not necessarily anthropomorphisedNot necessarily intelligent

Major Design Issues

Understanding does the user understand the potential and

limitations of the agent does the agent understand what task it should be

doing on behalf of the userControl

does the user trust the agent sufficiently to allow it to perform a task on the user’s behalf

does the agent have sufficient autonomy to perform the task successfully

Agent Researcher

Looks for net-based information can be preset by user may deduce user interests based on interactions

Proactively informs user of new informationExamples:Letizia (Lieberman), Firefly

(www.firefly.com) Added Value ?

Can introduce you to other users with similar interests Frees the user up from repetitive information searchesTailored information provision service

Agent Worker

Performs tasks that users do not wish to do because of time, desire, etc.

Enables user to be more efficient by removing mundane, time-consuming tasks

Examples: Kasbah Added Value

buying / selling finding best price / best match to specification

Agent Administrator

Administrator performs admin tasks, similar to a Personal

Assistant or the use of a Time Manager aids the user in organising their lives

considerable potential application

Remembrance Agent, Yenta

Agent Educator

Old concept (Intelligent Tutoring Systems)New “face”Can take on multiple possible roles

tutor peer

More tangible and visible, particularly if physically embodied (Bass’s Steve, for example)

Designing agents

Context…Primary goalsKey competenceBelievabilityTrustworthinessSuitability to roleCommunication aspects - vital for

success...

Take a scenario...

National Health Service Helpline context… agent characteristics agent interactions what does it look like? what does it do? is the image right?

Design and implement it

Technology issues bandwidth latency graphics

Implementation issues architecture fat / thin client / server languages

And how do you check it works?

Does HCI practice what it preaches?Evaluation…

some desperation and “making do” invisible / unavailable tests no industry / research benchmarks intuition, inspiration, innovation

Different to GUI?

Not really - why not?Same tests relevant?

Heuristic evaluation User testing Questionnaires

Shouldn’t there be something more? Psychological studies - trust, believability, nvc Media studies - believability, appearance Linguistics - communication

Symbiotic Relationship

AgentUserDirect Manipulation applications

Web Local applications Remote applications

Communication ProtocolsStandard Hardware / Software

Supporting symbiosis

Need to have agents that can be trusted and that really do what the user wants them to

Well designed information visualisation interfaces with appropriate direct manipulation can exist in parallel with agents

Agents do not necessarily “dumb-down” the interface, rather they increase usability

Varying levels of user control, agents are partially autonomous

Future

Need for comparisons of GUI direct manipulation and agent based interfaces

Focus needs to be on productivity enhancement as well as satisfaction and ease of use

Too much focus on the agent and not enough on the interface?

Summary

Social Interface Agents have enormous potential

Currently, technology, technique, functional fixedness and lack of inspiration hold us back

Similar in some respects to any other interfaceSome examples exist, but either not too good

or research basedLots of work still - is it the new paradigm?

Reading List

Stacks of stuff on the web (Maes’s group at MIT, Salford, CVE conferences, etc.)

Shneiderman, B., Maes, P., “Direct Manipulation vs. Interface Agents,” interactions (vol iv.6), November & December, 1997, pp. 42 - 61

Lanier, J., “A Conversation with Jaron Lanier,” interactions (vol ii.3), July, 1995, pp. 46 - 65