1. Alan Turing & AI LCC 2700: Intro to Computational Media

2. Alan Turing 1912 - 1954 Mathematician, Cryptographer Worked at Bletchley Park, Britain’s codebreaking hq, where he designd ciphers to break the code for the German Enigma Machine 1952, convicted of “gross acts of indecency” for having a homosexual relationship. Turing was forced to take estrogen treatments and committed suicide in 1954

3. Turing From thinking machines to credible machines “Can machines think?” is a meaningless and loaded question The foundation of the field that came to be known as Artificial Intelligence The “Turing Test” — a human engages in natural conversation with a human and a machine. If the human cannot tell the difference, the machine passes — based on the Imitation Game (a party game in which players try to guess the gender of a A specific, discrete state machine : context

4. Alan Turing, Can Machines Think? (1950) Q. If machines could think, how would we know it? A.Indistinguishability using the “imitation game”: The new form of the problem can be described in terms of a game which we call the "imitation game." It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart from the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman. He knows them by labels X and Y, and at the end of the game he says either "X is A and Y is B" or "X is B and Y is A." The interrogator is allowed to put questions to A and B.

5. Some notable Objections to the Turing Test (as covered by Turing) Theological - thinking is a function of an immortal soul; machines can’t think –Turing: God could grant a computer a soul if he wished Mathematical - There are limits to what logic can answer –Turing: Humans are pleased with the fallibility of machines Consciousness - Only composition from emotions could = brain –Turing: We have no way of knowing if non-human things experience emotion Lady Lovelace - Computers are incapable of originality –Turing: computers can show things that are not immediately recognizable

6. Turing Machine An abstract machine that represents computation Model: –A person executes ordered operations on the contents of an unlimited number of paper sheets. The sheets contain a finite number of symbols. The person stores one of a finite number of states. Example –Change the state of the current page to 1 and move one symbol to the right –If your current state is 4, move to page 456 A Turing Machine that simulates any other Turing machine is said to be a universal Turing machine

7. Turing Completeness A system equivalent to a universal Turing machine Unlimited storage can be assumed or ascribed to qualify a system as Turing complete –Babbage’s Analytical Engine –Programming languages (C, Java, Lisp, etc.) –Formal grammars

8. From Thinking Machines to Credible Machines Move from thinking to believability (Turing) The responsibility of computation (Weizenbaum) –Computation as a representational system Computation as literary expression (Murray’s adoption of W.)

9. Experiencing Characters in Traditional Media Drama embodied actors reciting speeches and exchanging dialog, gesturing, using props in unisequential story we interpret their inner life based on what they say and do while we are observing them directly Film embodied actors seen in moving images, with dialog, voice-over narration; shorter scenes, fewer words; smaller gestures; unisequential or multi-sequential we interpret their inner life based on what the camera shows us of them and of their world

10. Experiencing Computational Characters Computational characters come alive when they execute behaviors in response to our participation in their world Inscription in both directions bits/clicks Circular transmission display – input - output Interpretation in both directions images, words – pointing, typed words We interpret their inner life based on how they respond to what we do

11. Traditional vs Computational Character Making All characters are imagined by creators and readers/audience as having inner, continuous reality, and a range of possible behaviors beyond what is represented in the text Writers imagine the character’s deeper self – the psyche, soul, feelings, consciousness, personalities out of which all the behavior we see arises In computational media, we can create a character by inscribing and representing the deeper self, and a range of possible actions, and letting the computer dynamically create the behavior : e.g. the Sims

12. Traditional vs Computational Character Making In computational media, we can create a character by inscribing parameters and/or rules, and then watching the computer dynamically generate the behavior inscribing parameters and then operating the character inscribing parameters and then interacting with the character

13. Parameterized Characters

14. The Sims : Parameters realized in behaviors

15. Characters in Computational Media Characters can be created procedurally by new behavior (rules) by parameters for existing behavior Characters are made real by participation by scripting the interactor to form expectations by giving the interactor props and actions to shape their behaviors Exchanges between character and interactor should be coherent readable

16. Genre expectations shape interaction Dramatic genres: mysteries, thrillers, romances, situation comedies, etc. –Create expectations of possible sequences and outcomes –Include familiar roles (detective, villain, Mr. Right, insensitive husband, etc. ) –Include familiar events and actions (interrogation, fight, kiss, insult, etc.) –Include props that carry scripts and expectations (blackmail note, gun, bouquet of flowers, sixpack of beer)

17. ELIZA Joseph Weizenbaum, 1966 Simulation of a Rogerian therapist Named after Eliza Doolittle, the character in Pygmalion who learns to speak with an upper-class accent instead of her Cockney one ELIZA Works by parsing and substituting key words/phrases with canned responses The result evokes a therapist

18. E.M. Forster: Flat vs Round Characters Flat characters do not change Flat characters always respond in the same way to the same situation Flat characters make good comic characters –Predictable, creating anticipation –Inappropriate, because repeat same response in new situation

19. Classic Flat Character Jack Benny, the stingy man Thief: Your money or your life! (long pause) Thief: Your money or your life!! Jack Benny: I’m thinking….

20. Interactive flat character Less satisfying to play because too predictable More satisfying to interact with because you can anticipate and evoke the behavior

21. Interactive round character Hard! “Selectively” round characters

22. Conversations with Characters: Loebner Prize established 1990 –Hard to do it with knowledge base The real world is too hard to represent Fact-based conversation is hard to fudge –Yet same character (Julia) failed Loebner but passed the test in a social MUD Human beings are often unresponsive Comic characters are often unresponsive Human beings often converse in formulaic patterns Dating / flirting insult conversation is very formulaic (http://openseduction.org/signals/

23. Loebner Prize 2003 ?

24. Humans outperformed all the chatterbots

26. Rollo Carpenter, Jabberwock Loebner Prize Winner 2003 http://www.abenteuermedien.de/jabberwock/

27. Conversations with Characters: Free text input creates high expectations –FaçadeFaçade –www.interactivestory.netwww.interactivestory.net

28. Dramatic Agency Procedural + Participatory + Dramatic compression Character’s conditions and parameters are suited to the dramatic world Interactor’s actions are well suited to the dramatic world Character’s behaviors are evoked smoothly by Interactor’s actions and satisfy dramatic expectations of the situation Interactor is able to do things that effect the character in significant, dramatizable ways

29. Janet Murray on Chatterbots “The most successful characters have been those who are self- absorbed, evasive, or obsessive in familiar ways. Politicians in a press conference Defaults and conversions for a genre of insolent characters What about other characters? Trouble with “an authoring environment that does not require programming”

31. Then why did Eliza work? Clear scripting of the interactor by dramatic situation Clever key word/response pairs Very clever DEFAULTS Character’s lack of responsiveness is dramatically motivated Character is barely a character; a simple subject to simulate

32. ELIZA as Parody Weizenbaum worried about reactions to Eliza that suggested that it should be used as a “real” therapist This concern had much to do with how willing users were to anthropomorphize the program –Story of the secretary Weizenbaum: the responsibility of the artist/scientist for the work they create

33. The Danger of Science “What aspects of life are formalizable” becomes “of what technological genius is man a species” –Critique of the drive to discover and invent as an end Science as an “addictive drug” –The seduction of rationality: all things human can be understood, modeled, and predicted Instead, Weizenbaum suggests that science is all argument, persuasion –“Scientific statements can never be certain; they can be only more or less credible” –Compare to Turing on AI, and contemporary simulation vs. expression.

34. Computation as Expression Creating and consuming computational artifacts There is a science in computational representation, but computational representation is not a science

35. Designing Character Behavior Abstraction Flat characters can be interesting when they are the primary subject of a computational artifact Parody is useful and valid Design character behaviors from your own perspective –Disaffected http://www.persuasivegames.com/games/game.aspx?game=di saffected http://www.persuasivegames.com/games/game.aspx?game=di saffected Steal others’ perspectives for commentary, critique, or caricature –Signals & Flirtation http://openseduction.org/signals/discussion/