PowerPoint Presentation Lecture

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human-computer interaction fdm 20c
introduction to digital media lecture
20.04.2004
warren sack / film digital media department /
university of california, santa cruz
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mini-project 2

• if you you have only added the professor and your
  ta to your social network (and not added any
  others in the class), then draw a social network
  that does include the professor and the ta.
• otherwise, draw a social network that does not
  include the professor and the ta.

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last time

• noah wardrip-fruin
• the new media reader
• first person
• artificial intelligence
• exchange between jill walker and warren sack
• turings article is the founding document of the
  field of artificial intelligence

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last time

• artificial intelligence the founding document
• who was turing? what is he famous for?
• a reading of turings article computing
  machinery and intelligence in which the
  following is highlighted
• gender the role of the woman in the imitation
  game
• the aesthetics of the game the aesthetics of the
  uncanny
• the prescient insights of turing on gender and
  the body, that would turn out -- now -- to be
  most useful for trying to understanding online
  role-playing games and also some of the central
  weaknesses of decades of ai research (especially
  oversights made about the role of the body in
  models of thinking)

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artificial intelligence a definition

• ... artificial intelligence AI is the science
  of making machines do things that would require
  intelligence if done by humans
• Marvin Minsky, 1963

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artificial intelligence research areas

• Knowledge Representation
• Programming Languages
• Natural Language (e.g., Story) Understanding
• Speech Understanding
• Vision
• Robotics
• Machine Learning
• Expert Systems
• Qualitative Simulation
• Planning

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planning as a technical problem

• GPS is what is known in AI as a planner.
• Newell, Alan, Shaw, J. C., and Simon, Herbert A.
  GPS, A Program That Simulates Human Thought. In
  Computers and Thought, ed. Edward A. Feigenbaum
  and Julian Feldman. pp. 279-293. New York, 1963
• To work, GPS required that a full and accurate
  model of the state of the world (i.e., insofar
  as one can even talk of a world of logic or
  cryptoarthimetic, two of the domains in which GPS
  solved problems) be encoded and then updated
  after any action was taken (e.g., after a step
  was added to the proof of a theorem).

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a problem with ai planning

• the frame problem This assumption that
  perception was always accurate and that all of
  the significant details of the world could be
  modeled and followed was incorporated into most
  AI programs for decades and resulted in what
  became known to the AI community as the frame
  problem i.e., the problem of deciding what
  parts of the internal model to update when a
  change is made to the model or the external
  world.
• Cf., Martins, J. Belief Revision. In
  Encyclopedia of Artificial Intelligence, Second
  Edition. Stuart C. Shapiro (editor-in-chief), pp.
  110-116. New York, 1992

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story understanding as a plan recognition problem

• G. DeJong (1979) FRUMP Fast Reading
  Understanding and Memory Program
• demonstration script
• The demonstrators arrive at the demonstration
  location.
• The demonstrators march.
• Police arrive on the scene.
• The demonstrators communicate with the target of
  the demonstration.
• The demonstrators attack the target of the
  demonstration.
• The demonstrators attack the police.
• (From DeJong, 1979 pp. 19-20)

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story generation as planning

• James Meehan, "The Metanovel Writing Stories by
  Computer", Ph.D. diss., Yale University, 1976.
• demo micro-talespin
• see http//web.media.mit.edu/wsack/micro-talespin
  .txt
• a demo of micro-talespin

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problems with story generation missing common
sense

• Examples of Talespins missing common sense(from
  Meehan, 1976)
• Answers to questions can take more than one form.
• Dont always take answers literally.
• You can notice things without being told about
  them.
• Gravity is not a living creature.
• Stories arent really stories if they dont have
  a central problem.
• Sometimes enough is enough.
• Schizophrenia can be disfunctional.

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outline for the rest of today

• key point that has implications for the
  aesthetic, ethics and evaluation of
  human-computer interaction
• history of hci from a tools perspective
• conversational models of the interface the
  intersection of ai and hci
• question for today what problem does
  weizenbaums eliza system address or solve?
• the answer of ai
• the answer of ethnomethodology

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key point

• People often interact with media technologies as
  though the technologies were people.
• related ideas
• clifford and nash, the media equation
• freud, transference
• see also sherry turkle on computers as second
  selves and as evocative objects
• surrealists, automatic writing (recall tristan
  tzaras recipe)
• mannheim/schutz/garfinkel, the documentary
  method

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related points ethics

• questions of ethics and others
• should we treat technologies as people or people
  as technologies?
• should we only treat others who are like us with
  care and respect? or, should we also extend our
  care and respect to others who are radically
  different?
• what makes believe someone or something is alive,
  thinking, or simply the same as us?

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related points aesthetics teleology

• questions of aesthetics, goals and intentions
• do objects, technologies and natural phenomena
  have goals and intentions?
• or, do they just look like they have goals and
  intentions?
• cf., the philosopher immanuel kants theories of
  aesthetics detailed in his book critique of
  judgment

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related points design

• If we view objects, technologies and natural
  phenomemon as if they do, in fact, have goals and
  intentions, then we will design like an
  artificial intelligence researcher.
• On the other hand, if we view objects,
  technologies and natural phenomenon as if the
  just look like they have goals and intentions,
  then we will design like a tool builder for human
  users or operators of our tools.

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history of hci (from a tool-building perspective)

• video of alan kay that can be found on the cd in
  the new media reader

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history of hci as tools people

• people
• Vannevar Bush memex
• J.C.R. Licklider computer networking, agents
• Ivan Sutherland sketchpad
• Doug Engelbart mouse, GUI, word processing etc.
• Ted Nelson hypertext
• Alan Kay object-oriented programming, laptops,
  ...

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history of hci as tools systems

• systems
• Memex 1945 (concept)
• Sketchpad 1963
• NLS (oNLine System) - 1963-68
• Xerox Alto 1972, Xerox Star 1981
• Apple Lisa 1983, Mac 1984, NeXT 1988
• Macintosh Powerbook 1991
• WWW 1994

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history of hci as tools funding

• funding
• Military Navy, Air Force, ARPA, DARPA
• Universities MIT, Stanford, CMU, UC
• Government National Science Foundation 1950-now
  
• Companies Xerox PARC 1970-now, Apple - NeXT

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where does hci meet ai?

• basic design question should the computer act
  like a person?
• agents versus direct manipulation
• e.g., ben schneiderman versus pattie maes
  (sigchi, 1997)
• even direct-manipulation interfaces are based
  on a conversation metaphor the computer
  responds immediately to each action or command
  from the user
• but, there are (at least) two models of
  conversation
• information/intention transmission
• inspirations for ai e.g., paul grice, pragmatics
• co-construction of meaning
• ethnomethodology e.g., harvey sacks,
  conversation analysis

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question for today

• what problem does weizenbaums eliza system
  address or solve?
• the artificial intelligence answer it does (or
  does not) behave like a human and is therefore
  successful (or not successful)
• the ethnomethodology answer it is taken to be a
  like a person in a conversation and thus simply
  works like most other technologies in a social
  situation

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johnstones story guessing game
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johnstones algorithm

• I say to an actress, Make up a story.
• She looks desperate, and says, I cant think of
  one.Any story, I say. Make up a silly one.
  I cant, she despairs.
• Suppose I think of one and you guess what it
  is.
• At once she relaxes, and its obvious how very
  tense she was.
• Ive thought of one, I say, but Ill only
  answer Yes, No, or Maybe.
• She likes this idea and agrees, having no idea
  that Im planning to say Yes to any question
  that ends in a vowel, No to any question that
  ends in a consonant, and Maybe to any question
  that ends with the letter Y.
• For example, should she ask me Is it about a
  horse? Ill answer Yes since horse ends in
  an E.
• Does the horse have a bad leg?
• No.
• Does it run away?
• Maybe
• She can now invent a story easily, but she
  doesnt feel obliged to be creative, or
  sensitive or whatever, because she believes the
  story is my invention. She no longer feels wary,
  and open to hostile criticism, as of course we
  all are in this culture whenever we do anything
  spontaneously.
• Keith Johnstone, Impro Improvisation and the
  Theatre (Methuen, 1989)

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johnstones algorithm

• If the last two answers were No, then answer
  Yes.
• Else, if more than 30 total answers, then answer
  Yes.
• Else, if the question ends in vowel, then answer
  No.
• Else, if question ends in Y, then answer
  Maybe.
• Else, answer Yes.

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ethnomethodology a definition

• Ethnomethodology simply means the study of the
  ways in which people make sense of their social
  world.
• Ethnomethodology is a fairly recent sociological
  perspective, founded by the American sociologist
  Harold Garfinkel in the early 1960s. The main
  ideas behind it are set out in his book "Studies
  in Ethnomethodology" (1967).
• (Simon Poore, http//www.hewett.norfolk.sch.uk/cu
  rric/soc/ethno/intro.htm)

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ethnomethodology

• Ethnomethodology differs from other sociological
  perspectives in one very important respect
• Ethnomethodologists assume that social order is
  illusory. They believe that social life merely
  appears to be orderly in reality it is
  potentially chaotic. For them social order is
  constructed in the minds of social actors as
  society confronts the individual as a series of
  sense impressions and experiences which she or he
  must somehow organise into a coherent pattern.
• Simon Poore, http//www.hewett.norfolk.sch.uk/curr
  ic/soc/ethno/intro.htm

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ethnomethodology

• Q How do people make sense of the world?
• A They/we use the documentary method
• Karl Mannheim, the documentary method
• Garfinkel on Mannheim The method consists of
  treating an actual appearance as the document
  of, as pointing to, as standing on behalf of
  a presupposed underlying pattern. The method is
  recognizable for the everyday necessities of
  recognizing what a person is talking about
  given that he does not say exactly what he means,
  or in recognizing such common occurrences and
  objects as mailmen, friendly gestures, and
  promises.

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lucy suchman

• Ph.D. in Social/Cultural Anthropology from the
  University of California at Berkeley
• Researcher at Xeroxs Palo Alto Research Center
  (PARC)
• Founded and Directed of the Work Practice
  Technology research group at PARC
• Currently Professor in the Centre for Science
  Studies and Sociology Department at Lancaster
  University in England

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lucy suchman

• is an ethnomethodologist and an anthropologist of
  science (cf., bruno latour in next weeks
  lectures)
• her work radically challenged work in hci and ai
• she is one of the primary people working in the
  fields of participatory design (pd) and
  computer-supported cooperative work (cscw)

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next time

• cscw computer-supported cooperative work