search sounds and player in $ResourceDir

[micropolis] / src / notes / Beyond-Intelligent-Machines

Date: Tue, 24 Nov 92 22:25:59 -0500
From: ben@cs.UMD.EDU (Ben Shneiderman)
To: bam@cs.cmu.edu, ben@cs.umd.edu, callahan@cerc.wvu.wvnet.edu,
        hopkins@bongo.garnet.cs.cmu.edu, weiser.pa@xerox.com
Subject: Re: more pie menus!

I couldn't resist sending you all this latest essay which is
destined for IEEE Software...some readers expect it to generate
some strong responses...Ben


Beyond Intelligent Machines:
    Designing Predictable and Controllable User Interfaces
 
 
  Ben Shneiderman  November 24, 1992
 
       University of Maryland, College Park, MD 20742  
 
   Professor, Department of Computer Science,
   Head, Human-Computer Interaction Laboratory at the 
      Center for Automation Research &
   Member, Institute for Systems Research
 
 
Who's in control?

An important shift is occurring from the old vision of computers
as 'intelligent' to a new vision based on predictable and controllable
user interfaces that depend on direct manipulation of objects and actions.
Appropriate metaphors and terminology are important since they shape
the thoughts of researchers, designers, managers, congress-people, 
journalists, etc.  Most of us have learned the importance of gender 
neutral terminology and similarly I have been strongly opposed to 
suggesting that computers are 'intelligent' or 'smart' for several 
reasons:
 
1) Limits to Imagination
 
I think we should have much greater ambition than to make a computer 
behave like an intelligent butler or other human agent.  Computer 
supported cooperative work (CSCW), hypertext/hypermedia, multi-media, 
information visualization, and virtual realities are powerful 
technologies that enable human users to accomplish tasks that no human 
has ever done.  If we describe computers in human terms then we
run the risk of limiting our ambition and creativity in the design
of future computer capabilities.
 
 
2) Predictability and Control are Desirable
 
If machines are 'intelligent' or 'adaptive' then they may become less 
predictable and controllable.  Our usability studies show that users 
want feelings of mastery, 
competence, and understanding that come from a predictable and 
controllable interface.  Most users seek a sense of 
accomplishment at the end of the day, not the sense that this 
'intelligent' machine magically did their job for them. 
 
 
3) Human Responsibility
 
I am concerned that if designers are successful in convincing the users 
that computers are intelligent, then the users will have a reduced sense 
of responsibility for failures.  The tendency to blame the machine is 
already widespread and I think we will be on dangerous grounds if we 
encourage this trend.
 
 
4)  Machines are not People  AND  People are not Machines
 
I have a basic philosophical objection to the suggestion that machines 
are, or can ever be, intelligent.  I know that many of my colleagues are 
quite happy to call machines intelligent and knowledgeable, but I prefer 
to treat and think about machines in very different ways from the way I 
treat and think about people.
 

The lessons of history
 
While some productive work has been done under the banner of
`intelligent', often those who use this term reveal how little they
know about what users want or need.  The users's goal is not to
interact with an 'intelligent' machine, but to create, communicate, 
explore, plan, draw, compose, design, or learn.  Ample evidence 
exists of the misguided directions brought by 'intelligent' machines:
 
  - natural language interaction seems clumsy and slow compared to 
direct manipulation and information visualization methods that use 
rapid, high-resolution, color displays with pointing devices.  Lotus HAL 
is gone, AI INTELLECT hangs on but is not catching on.  There are some 
interesting directions for tools that support human work through 
natural language processing: aiding human translators, parsing 
texts, and generating reports from structured databases.
 
  - speech I/O in talking cars and vending machines is gone.
Voice recognition is fine for handicapped users plus special situations, 
but doesn't seem to be viable in general office, home, or school 
settings.  Our recent studies suggest that speech I/O has a greater
interference with short term and working memory than hand-eye 
coordination for mouse menu selection.  Voice store and forward,
phone-based information retrieval, and voice annotation have great 
potential but these are not the 'intelligent' applications.
 
  - adaptive interfaces are unstable and unpredictable, often leading 
users to worry about what will change next.  I see only modest chances 
for success in user modeling to recognize the level of expertise and
revise the interface accordingly - can anyone point to successful
studies or commercial products?  By contrast, user controlled 
adaptation through control panels, cruise control for cars, and 
remote controls for TV are success stories.  While algorithms to 
deal with dynamic
issues in network or disk space management are needed, the task domain 
and user interface issues of the application program
should generally be under direct user control.
 
  - Intelligent CAI (Computer Assisted Instruction) only prolonged the 
time (compared to traditional CAI) until the users felt they were the 
victims of the machine.  Newer variations such as Intelligent Tutoring 
Systems are giving way to Interactive Learning Environments where 
students are in control and actively creating or exploring.
 
  - intelligent talking robots with five-fingered hands and human facial 
features (quaint fantasy that did well in Hollywood but not in Detroit 
or elsewhere) are mostly gone in favor of flexible manufacturing systems 
that enable supervisors to specify behavior with predictable results.
 
 
It seems that some designers continue to ignore this historical pattern 
and still dream of creating 'intelligent' or 'smart' machines.  It is an 
ancient and primitive fantasy, and its seems most new technologies must 
pass through this child-like animistic phase.  Lewis Mumford identified 
this pattern (Technics and Civilization, 1934) when he wrote about the 
Obstacle of Animism: 'the most ineffective kind of machine is the 
realistic mechanical imitation of a man or another animal...for 
thousands of years animism has stood in the way of...development.'   
 
 
An alternate vision

My point in this essay is not merely to counter a popular design 
philosophy, but to offer a new vision that is more in harmony with what 
users want.  I believe that the future will be filled with powerful, but 
predictable and controllable computers that genuinely serve human needs  
(Designing the User Interface: Strategies for Effective Human-Computer
Interaction, Second Edition, Addison-Wesley Publ. Co., Reading, MA, 1992).

In this vision of predictable and controllable (PC) computing, 
the promising strategies are rapid,
visual, animated, colorful, high resolution interfaces built on
meaningful control panels, appropriate preference boxes,
user-selectable toolbars, rapid menu selection, easy to create macros,
and comprehensible shortcuts.  These enable me to specify rapidly, 
accurately, and confidently how I want my email filtered, what documents 
I want retrieved and in what order, and how my documents will be 
formatted.
 
 
Our Human-Computer Interaction Laboratory has applied these principles 
to information visualization methods that give users X-ray vision to see 
through their mountains of data.  Treemaps enable users to see (and 
hear) 2-3000 nodes of hierarchically structured information by utilizing 
every pixel on the display.  Each node is represented by a rectangle 
whose location preserves the logical tree structure and whose area is 
proportional to one of its attributes.  Color represents a second 
attribute and sound a third (B. Johnson & D. Turo,  Improving the 
Visualization of Hierarchies with Treemaps: Design Issues and 
Experimentation, Proc. IEEE Visualization '92).  Treemaps have been 
applied to Macintosh directory browsing (Figure 1), in which area could 
be set to file size, color to application type, and sound to file age 
(our TreeViz application is available from the University of Maryland's 
Office of Technology Liaison, (301) 405-4210).  When users first try 
TreeViz they usually discover duplicate or misplaced files, redundant 
and chaotic directories, and many useless files or applications.  Other 
applications include: stock market portfolio management, sales data, 
voting patterns, sports (48 statistics on 459 NBA players, in 27 teams, 
in four leagues), etc.
 
 
Dynamic queries allow rapid adjustment of query parameters and immediate 
display of updated result sets.  These animations enable users to 
develop intuitions, discover patterns, spot trends, find exceptions, and 
see anomalies.  The Dynamic HomeFinder prototype (Figure 2) allows users 
to adjust the cost, number of bedrooms, location, etc. and see points of 
light come and go on a map to indicate a matching home.  Users execute
up to 100 queries/second (rather than one query per 100 seconds)
producing a revealing animated view of where high or low priced homes
are found, and there are no syntax errors.  Clicking on a point of
light brings up a description or image (videotape available, or for 
an empirical comparison with a natural language system, see 
Williamson, C. and Shneiderman, B., The Dynamic HomeFinder: Evaluating 
dynamic queries in a real-estate information exploration system, 1992 
ACM SIGIR Proceedings).  

Dynamic queries are very effective when a visual environment such as a
map, calendar, or schematic diagram are available, but they can be
easily applied with standard text file output (Figure 3).  Dynamic 
queries exemplify the future of interaction; You don't need to
describe your goals, negotiate with an intelligent agent, and wait for
a response, you Just Do It!   Furthermore, dynamically seeing the 
results enables you to explore and rapidly reformulate your goals in 
an engaging videogame-like manner.  
 
 
Open problems in information visualization include screen organization, 
widget design, algorithms for rapid search and display, use of color
and sound, and strategies to accommodate human perceptual skills.  
We also see promise in expanding macro makers into the graphical 
environment with visual triggers based on controlled replay of 
desired actions - the 
general idea is Programming in the User Interface (PITUI) to 
Do-What-I-Did (DWID).
 
 
I want to encourage the exploration of new metaphors and visions of how 
computers can empower people by presenting information, allowing rapid 
selection, supporting personally specified automation, and providing 
relevant feedback.  Metaphors related to controlling tools or machines 
such as driving, steering, flying, directing, conducting, piloting, 
or operating seem more generative of effective and acceptable 
interfaces, than 'intelligent' machines.


A scientific approach to user interface research
 
Whether you agree with the design philosophy in this essay, and
especially if you disagree, I hope that you will add to our scientific
knowledge by conducting well-designed empirical studies of learning
time, measuring performance time for appropriate tasks, recording error
rates, evaluating human retention of interface features, and assessing
subjective satisfaction.  There's much work to be done to make
computing accessible, effective, and enjoyable.
 
 
Acknowledgements:  This essay was prompted by the discussion between 
Mark Weiser and Bill Hefley, stimulated by lively email and personal 
discussions with Paul Resnick, Tom Malone, and Christopher Fry at MIT, 
and refined by comments from Catherine Plaisant, Rick Chimera, Brian 
Johnson, David Turo, Richard Huddleston, and Richard Potter at the 
Human-Computer Interaction Lab at Univ. of Maryland.  I appreciate Bill 
Curtis's support for this vision.  Thanks to all.