Turingtestet - Yta och djup i cybernetisk dialog

1. Turingtestet- Yta och djup i cybernetisk dialog Staffan Larsson Institutionen för lingvistik Humanistdagarna 2005

2. Posthumanism • Turingtestet • Artificiell intelligens • Wittgensteintestet? • Mediering och kategorisering

3. Posthumanism • N. K. Hayles: How we became Posthuman • Den "posthumana" människan - cyborgen – är en människa utvidgad av och i symbios med teknologin; våra teknologier fungerar som proteser. • Det posthumana synsättet utgör en kreativ kritik mot traditionell humanism, • som ignorerar kroppslighet och antar att människans ”själsliv” är oberoende av kroppen (liberalt rationellt icke-kroppsligt subjekt) • men också grundar sig på antagandet att den biologiska kroppen på ett okomplicerat vis utgör människans gräns • Istället är kroppen bara "den första protesen"; människan är oskiljaktigt integrerad med sina hjälpmedel, sitt språk, sina teknologier, sin omvärld och sina medmänniskor • Seminarieserie: Tes-Anitites-Protes (TAP) • www.ling.gu.se/projekt/tap

4. Alan Turing (1912-1954) • Born in London, PhD in Princeton 1938 • The world’s first computer scientist • proved the existence of uncomputable functions • invented the first formal model of computation: the Turing Machine • helped break the German Enigma code using a simple nonprogrammable computer • laid the groundwork for Artificial Intelligence (AI) • Arrested 1952 under British laws of homosexuality • forced to undergo hormone treatment • died from cyanide poisoning

5. “Computing Machinery and Intelligence” (1950) • “Can machines think?” • Turing thought this question “too meaningless to deserve discussion” • wanted to replace it with with something more concrete

6. The imitation game • 3 participants: • man (A) • woman (B) • interrogator (C) • Interrogator stays in a separate room, and communicates via a messenger or a text terminal (”teleprinter”) • C’s goal is to determine who is the man and who is the woman; he knows them as X and Y • A tries to get C to make the wrong identification • B tries to help C make the correct identification

7. The new question • ”What will happen when a machine takes the part of A in this game, the part of B being taken by a man”? • Will C decide wrongly as often as in the original game? • This question replaces ”Can machines think?” • This is an operational / behavioural definition of thinking and intelligence • Focus on verbal behaviour abstracts from incidental properties like visual appearance

9. Turing’s prediction “In about fifty years time it will be possible to programme computers with a storage capacity of about 109 to make them play the game so well that an average interrogator will not have more than 70 percent chance of making the right identification after five minutes of questioning.” “At the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted” Lobner Prize

10. Two dialogues from the Loebner Prize competition 2005 • X: Hello, my name is Alice and I am the human • Judge 1: Hi Alice, if you are indeed human, you should be able to tell me which is bigger, my big toe or a Boeing 747 • X: Hi there Judge 1. Um, I think I sometimes am.I am a real person.  As you are sitting in front of your computer screen, you may be wondering if I am a computer or a person talking. • Judge 1: Can you answer the question about the toe and the 747? • X: Please rephrase the question and try asking me again.  As you hear the sound of keys typing you may begin to feel more comfortable chatting with me. • Judge 1: Which is bigger, a 747 or my big toe.  Come on, answer it. • X: The obvious one.  Please rephrase your question, Judge 1.  The feel of the keys on the tips of your fingers may remind you of some questions you wanted to ask me about. • Judge 1: Is a 747 smaller than my big toe or your big toe or anyone's big toe? • X: Not if I can help it.  You may be seated alone in a room, or together with a group of other people using computers.  You may be judging me.

11. Y: Hello, my name is Sam and I am the human. • Judge 3: what is your profession? • Y:i am a professor. • Judge 3: do you like windsurfing? • Y: think I would.  Do you? • Judge 3: tell me what you know about it. • Y: Not much, to be honest.  Sort of sailing on a surfboard? • Judge 3: do you know more about sailing? • Y: A little more.  I'm not too big on boats. • Judge 3: ell me some sport you are big on. • Y: I like to swim. • Judge 3: which stroke is the most tiring to you? and to most people? • Y: Crawl.  Or butterfly. • Judge 3: how far can you butterfly? • Y: Not very far.  It's tiring!  As you say. • Judge 3: what makes it so tiring? • Y: I suppose that it provides less floating momentum than backstroke, for instance. • Judge 3: could you describe the motion you make when you do butterfly? • Y: Both sets of limbs work simultaneously.

12. X = ALICE, winner of the 2005 Loebner Prize • Y = A human confederate • Judge 3: i think you're real. • Y: Thanks.  I think you're real too. • Men Turingtestet har en roll i

13. “How I failed the Turing Test”http://www.blogcadre.com/blog/jason_striegel/how_i_failed_the_turing_test_2005_09_04_13_26_29 • ...the more I tried proving my "actual" intelligence, the more my "artificial" intelligence would get called into question... • jmstriegel: no, really. I'm quite human.jmstriegel: test me if you wantshymuffin32: okshymuffin32: why do you like music?jmstriegel: hmm. i've never really considered that.jmstriegel: hell, i'm not going to be able to contrive a good answer for that one. ask me something else.shymuffin32: jeesus, you're worse than eliza

14. Artificial Intelligence • Goal • simulate human/intelligent behaviour/thinking • Weak AI • Machines can be made to act as if they were intelligent, i.e., pass the Turing Test • Strong AI • Agents that act intelligently have real, conscious minds • cf. “Is passing a TT criterial for intelligence?” • It is possible to believe in strong AI but not in weak AI

15. Kritik mot AI • Utifrån Heidegger och Wittgenstein har ett antal filosofer och (före detta) AI-forskare (Winograd & Flores 1987, Weizenbaum 1976, Dreyfus 1992) formulerat en kritik mot AI (främst GOFAI) • Mänsklig ”common sense” / ”bakgrund” är grundad i kroppen (embodied) och en produkt av mänskliga förkroppsligade socialiseringsprocesser; ej klart att det finns några ”genvägar” till common sense • Denna bakgrund är central för språkförståelse och språkanvändning • Därför kommer ingen dator (av den typ vi känner idag) att kunna klara Turingtestet • I denna mening kan Turingtestet sägas utgöra en gräns mellan människa och maskin; det som bara människan klarar

16. Gränssnittet aktualiserar gränsen • Vi kan istället att välja att inrikta forskningen på framtagandet av språkteknologiska gränssnitt, i syfte att göra teknologier mer lättillgängliga • Men: språkteknologiska gränssnitt ofta får formen av ett (skenbart) subjekt; • ett dialogsystem som SJ:s tidtabellupplysning framträder som en individ, låt vara trög, enkelspårig och med stora hörselproblem. • Detta är i viss mån en identifikation vi människor inte kan låta bli att göra åtminstone i någon grad; om det pratar som en människa, så är det en människa • Språkteknologiska gränssnitt tenderar genom sin språkliga förmåga att aktualisera gränsdragningen mellan människa och maskin, vare sig vi vill eller inte

17. Hayles on the Turing test • ”Your job is to pose questions that can distinguish verbal performance from embodied reality” • Turing makes a cruicial distinction: • the enacted body, present in the flesh on one side of the computer screen • the represented body, produced by verbal and semiotic markers consituting it in an electronic environment

18. The subject is contingent and mediated by technology... • ”...that has become so entwined with the production of identity that it can no longer be meaningfully separated from the human subject” • a cyborg

19. The new question again • 3 participants: • man (A) • woman (B) • interrogator (C) • What will happen when a machine takes the part of A in this game, the role of B being taken by a man? • Will C decide wrongly as often as in the original game?

20. Not completely clear whether • A should try to pretend that A is a woman, • or that A is a human • Not completely clear whether • B should be a woman or a man • Not completely clear whether C should be told that • one of X and Y is a machine and the other a woman • or that one of X and Y is a man and the other a woman

22. Gender imitation • Why has the gender aspect of Turing’s original formulation been downplayed? Perhaps it suggests that gender, as well as thinking, is • a property projected on the subject by others • not emanating from some essence within the subject, but rather working ”from the outside in” • cf. social constructivism, feminism, queer theory • Sherry Turkle: Life on the screen – Indentity in the Age of the Internet

23. Language games and communities • Compare the Turing test to Wittgenstein’s view of language communities • Kripke (1982): Wittgenstein on Rules and Private Languages • Instead of building complex theories of meaning and understanding, see how these concepts are used • When we say that someone understands an utterance, or means something by an utterance, we are performatively including or excluding them into a community of language users • “I understand what you mean”: inclusion • “What A really means (when he says X) is Y”: exclusion • To be part of a community is to be accepted as someone able to participate in the language games specific to that community

24. Communities on several levels • All speakers of some human language • All speakers of some indoeruopean language • All speakers of some Scandinavian language • All speakers of Swedish • All speakers of Gothenburg dialect of Swedish • All speakers of some sublanguage specific to an occupation (doctor, bus driver, bartender...)

25. The Turing Test and the human language community • The Turing test is based on language use • it implies (at least) that human-level language use requires human-level intelligence • We could instead simply regard it as a test of the ability to use human language as a human does it

26. From this perspective, the force of the Turing test is not that it shows intelligence... • ... but that it is a (very strict) test to determine whether to take a computer into a community of human language users

27. When we meet someone for the first time, we automatically make a first judgement as to whether this is a person we can talk to • We may extrapolate from physical appearance • After a brief and perhaps very formulaic conversation we automatically assume that this person is a member of my language community • We do not apply the Turing test to new acquaintances... • but if someone clearly breaks a rule, we get suspicious

28. The Wittgenstein Test? • A more ecologically valid version of the Turing test would be to sneak a computer into a conversation and see if anyone notices

29. Kategorisering • Vi tilldelar hela tiden varandra kategorier efter det vi direkt kan iaktta (ytan) • man / kvinna • svensk / invandrare • läkare / spårvagnsförare / ... • (människa / maskin) • Dessa kategorier antas ofta var förknippade med någon form av essens (ett djup) • Från iakttagelser av ytan gör vi antaganden om vad som ligger därbakom • Dessa tilldelningar är i hög grad intuitiva och automatiska

30. Mediering • För länge sedan var kommunikationen inte (lika tydligt och lika ofta) medierad • Samtal ansikte mot ansikte • Ny kommunikationsteknologi har lett till att en större andel av vår kommunikation är medierad av teknologi • I medierad kommunikation är den andre närvarande bara genom sin representation • I den mån representationen är språklig (en text eller en röst) kommer det språkliga beteendet att utgöra grunden för vår kategorisering

31. Turingtestet som en prototyp för medierad kategorisering • Turingtestet klargör villkoren för den teknologiskt medierad kommunikation • Medierad kommunikation kan ses som dialog mellan cybernetiska system • (människa + kommunikationsteknologi) talar med (människa + kommunikationsteknologi) • Vad innebär denna förskjutning för våra vanemässiga sätt att kategorisera varandra?

33. Turing’s list of possible objections • The theological objection • Thinking is a function of man’s immortal soul, given by God to humans but not to machines • The “heads in the sand” objection • “The consequences of machines thinking would be too dreadful. Let us hope and belive that they cannot do so.” • The mathematical objection • based on Gödel’s incompleteness theorem & limitations of discrete-state machines • The argument from consciousness • The only way one could be sure that a machine thinks is to be that machine and to feel oneself thinking

34. Argument from disability • claims (usually unsupported) of the form ”a machine can never do X” • Lady Lovelace’s objection • computers can only do what we tell them to • The argument from Continuity in the nervous system • The human nervous system is not a discrete-state machine, and a computer can thus not mimic its behaviour • The argument from informality of behaviour

35. (Searle’s Chinese Room • argument concerns strong AI • purports to show that producing intelligent behavoiur is not a sufficient condition for being a mind) • An argument about whether a “chinese room” (i.e. a computer) can understand language • Displaying verbal behaviour is not a sufficient condition for understanding a language

36. The Turing test and cultural change(Collins) • Now suppose, for argument's sake, that the test is long enough for the Chinese language to change while the questions are being asked, or that it is repeated again and again over a long period, and that the interrogators do not conspire to keep their questions within the bounds of the linguistic cross-section encapsulated in the original look-up tables. • If the stock of look-up tables, etc., remains the same, The Room will become outdated-it will begin to fail to answer questions convincingly. • Suppose instead, that the look-up tables are continually updated by attendants. • Some of the attendants will have to be in day-to-day contact with changing fashions in Chinese-they will have to share Chinese culture. • Thus, somewhere in the mechanism there have to be people who do understand Chinese sufficiently well to know the difference between the Chinese equivalents of "to be or not to be" and "what will it be, my droogies" at the time that The Room is in operation. • Note that the two types of room-synchronic and diachronic-are distinguishable given the right protocol. • It is true that the person using the look-up tables in the diachronic room still does not understand Chinese, but among the attendants there must be some who do.

37. Under the extended protocol, any Chinese Room that passed the test would have to contain type 4 knowledge [EXPLAIN] and I have argued that it is to be found in those who update the look-up tables. • It is these people who link the diachronic room into society-who make it a social entity. • Under the extended protocol, the Turing Test becomes a test of membership of social groups. It does this by comparing the abilities of experimental object and control in miniature social interactions with the interrogator. Under this protocol, passing the test signifies social intelligence or the possession of encultured knowledge.

38. A simplified Turing Test (Collins) • Once one sees this point, it is possible to simplify the Turing Test greatly while still using it to check for embeddedness in society. • The new test requires a determined judge, an intelligent and literate control who shares the broad cultural background of the judge, and the machine with which the control is to be compared. • The judge provides both "Control" and "Machine" with copies of a few typed paragraphs (in a clear, machine-readable font), of somewhat mis-spelled and otherwise mucked-about English, which neither has seen before. • It is important that the paragraphs are previously unseen for it is easy to devise a program to transliterate an example once it has been thought through. • Once presented, Control and Machine have, say, an hour to transliterate the passages into normal English. • Machine will have the text presented to its scanner and its output will be a second text. • Control will type his/her transliteration into a word processor to be printed out by the same printer as is used by Machine. • The judge will then be given the printed texts and will have to work out which has been transliterated by Control and which by Machine.

39. Here is a specimen of the sort of paragraph the judge would present. • mary: The next thing I want you to do is spell a word that means a religious ceremony. • john: You mean rite. Do you want me to spell it out loud? • mary: No, I want you to write it. • john: I'm tired. All you ever want me to do is write, write, write. • mary: That's unfair, I just want you to write, write, write. • john: OK, I'll write, write. • mary: Write.

40. mary: The next thing I want you to do is spell a word that means a religious ceremony. • john: You mean “rite”. Do you want me to spell it out loud? • mary: No, I want you to write it. • john: I'm tired. All you ever want me to do is write, write, write. • mary: That's unfair, I just want you to write “rite” right. • john: OK, I'll write “rite”. • mary: Right.

41. The point of this simplifed test • the hard thing for a machine to do in a Turing Test is to demonstrate the skill of repairing typed English conversation • the interactional stuff is mostly icing on the cake. • The simplifed test is designed to draw on all the culture-bound common-sense needed to navigate the domain of error correction in printed English. • This is the only kind of skill that can be tested through the medium of the typed word but it is quite sufficient, if the test is carefully designed, to enable us to tell the socialized from the unsocialized. • It seems to me that if a machine could pass a carefully designed version of this little test all the significant problems of artificial intelligence would have been solved-the rest would be research and development.

43. Hayles again If my nightmare is a culture inhabited by posthumans who regard their bodies as fashion accessories rather than the ground of being, my dream is a version of the posthuman that embraces the possibilities of information technologies without being seduced by fantasies of unlimited power and disembodied immortality, that recognizes and celebrates finitude as a condition of human being, and that understands human life is embedded in a material world of great complexity, one on which we depend for our continued survival.