Do We Possess the Intelligence to Design Artificial Intelligence
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This presentation was given by Christopher Konrad at the Interaction19 Redux event in San Diego. It is an examination of the aspects of human behavior that can impact or influence the Artificial Intelligence (AI) systems that we are designing.
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Do We Possess the Intelligence to Design Artificial Intelligence
- 7. FAST SLOW SYSTEM1 SYSTEM2 Operates automatically / quickly with little effort. No sense of voluntary control. Example: Detect that one object that is more distant than another Controlled and allocates attention to the effortful mental activities that demand it, including complex computations. Example: Compare two washing machines for overall value TWO-SYSTEMSMODELOFTHEMIND
- 9. 17 X 24 = 408 COMPLETETHECOMPUTATION
- 10. A MACHINE FOR JUMPING TO CONCLUSIONS Neglect of Ambiguity & Suppression of Doubt ANN APPROACHED THE BANK
- 11. CONFIDENTIAL
- 12. Group1 Group2 How happy are you these days? How many dates did you have last month? How many dates did you have last month? How happy are you these days? Any correlation with the number of dates and being happier? No Any correlation with the number of dates and being happier? Yes ANSWERING AN EASIER QUESTION The Mood Heuristic for happiness
- 13. ANSWERING AN EASIER QUESTION Substitution of 3-D for 2-D size occurred automatically As shown on the screen, is the figure on the right larger than the figure on the left?
- 14. TargetQuestion EasierQuestion How much would you contribute to save an endangered species? How much emotion do I feel when I think of dying polar bears? How happy are you with your life these days? What is my mood right now? How should financial advisers who prey on the elderly be punished? How much anger do I feel when I think of financial predators? ANSWERING AN EASIER QUESTION Substituting Questions
- 15. CONFIDENTIAL ANSWERING AN EASIER QUESTION Substituting Questions
- 16. REMEMBERTHIS… ASKYOURSELFTHIS… System 1 generates impressions, feelings, and inclinations; when endorsed by system 2 these become beliefs, attitudes and intentions. Should AI have fast and slow complimentary systems with similar characteristics as the human mind? System 1 is a machine for jumping to conclusions. When do you want AI to trust its gut and jump to conclusions based on feelings and inclinations? We are rarely stumped because system 1 will just answer an easier question that uses available information. Do you want AI to substitute hard questions for easier questions? It’s a very human quality. DOWEPOSSESSTHEINTELLIGENCE TODESIGNARTIFICIALINTELLIGENCE?
- 18. ASTUDYOFTHEINCIDENCEOFKIDNEYCANCERINTHE3,141 COUNTIESOFTHEUNITEDSTATESREVEALSAREMARKABLEPATTERN.
- 22. System 1 is adept at causal connections but they can be wrong. We fall into a trap that “What you see is all there is.” It is a difficult relationship between our mind and statistics. THE LAW OF SMALL NUMBERS Small samples yield extreme results more often than large samples do.
- 24. PLAYER 1 2 3 4 1 66 78 70 69 2 77 67 69 71 ROUND REGRESSION TO THE MEAN Success = Talent + Luck Regression effects are ubiquitous, and so are misguided causal stories to explain them.
- 25. STORE 2017 2018 1 $11,000,000 2 $12,000,000 3 $18,000,000 4 $29,000,000 Total $61,000,000 $67,100,000 REGRESSION TO THE MEAN Regressive forecasts are more predictive. Low performers likely to do better than 10% while high performers likely do worse than 10%.
- 26. REMEMBERTHIS… ASKYOURSELFTHIS… System 1 is adept at causal connections on the basis of scraps of evidence. We fall into a trap that “What you see is all there is.” Are ML models trained on data that are too limited and biased? Does the dataset accurately represent the diversity of the customer base? Sustaining doubt is harder work than sliding into certainty. How can AI systems help us make better causal judgements? Causal explanations will be falsely used when regression is the inevitable explanation. Do we need to be concerned with our attempt to humanize AI systems and pass along bogus or biased causal explanations? DOWEPOSSESSTHEINTELLIGENCE TODESIGNARTIFICIALINTELLIGENCE?
- 29. Willing to sell for less than $1 million Buyer said that was too high Lucky? What else didn’t happen? CONFIDENTIAL EXAGGERATE SKILL & UNDERESTIMATE LUCK Narrative Fallacy
- 30. CEOwhencompanyisthriving… SameCEOwhencompanyisfailing… Flexible Confused Methodical Rigid Decisive Authoritarian CONFIDENTIAL WE CAN GET THE CAUSAL RELATIONSHIP BACKWARDS Halo Effect
- 31. REMEMBERTHIS… ASKYOURSELFTHIS… We exaggerate the role of skill and underestimate the part that luck played in the outcome. Will we say, “that robot was lucky?” We get the causal relationship backwards because of the halo effect. When is an algorithm better than human judgement? DOWEPOSSESSTHEINTELLIGENCE TODESIGNARTIFICIALINTELLIGENCE?
- 32. PART4 CHOICES
- 33. Youareofferedagambleonthetossofacoin. Ifthecoinshowstails,youlose$100 Ifthecoinshowsheads,youwin$150 Isthisgambleattractive?Wouldyouacceptit? LOSS AVERSION The rejection is an act of system 2 but the emotional responses are generated by system 1.
- 34. LOSS AVERSION Diminishing sensitivity for both gains and losses. Losses loom larger than gains.
- 35. People become risk seeking when all their options are bad. PROBLEM1:WHICHDOYOUCHOOSE? GET$900FORSUREOR90%CHANCETOGET$1,000 PROBLEM2:WHICHDOYOUCHOOSE? LOSE$900FORSUREOR90%CHANCETOLOSE$1,000 RISK SEEKING
- 43. REMEMBERTHIS… ASKYOURSELFTHIS… Losses loom larger than gains which make us loss averse. Will AI choices factor the psychological benefits of gains and cost of losses of the choice? We become risk seeking when all the options are bad. Will our personal AI assistants inherit our individual morality and make choices accordingly? DOWEPOSSESSTHEINTELLIGENCE TODESIGNARTIFICIALINTELLIGENCE?
- 45. THANKYOU.