mei28
December 20, 2023
160

# [Human-AI Decision Making勉強会] 意思決定 with AIは個人vsグループで変わるの？

2023/12/20 Human-AI Decision Makingの発表資料
Are Explanations Helpful? A Comparative Study of the Effects of Explanations in AI-Assisted Decision-Making
CHI2023

## mei28

December 20, 2023

## Transcript

1. ### ҙࢥܾఆ with AI͸ݸਓvsάϧʔϓͰมΘΔͷʁ ౦ژେֶ അ৔ݚڀࣨ D2 ༶໌఩ 2023/12/20 Human-AI Decision

making ษڧձ Are Two Heads Beter Than One in AI-Assisted Decision Making? Comparing the Behavior and Performance of Groups and Individuals in Human-AI Collaborative Recidivism Risk Assessment Chun-Wei Chiang, Zhuoran Lu, Zhuoyan Li and Ming Yin CHI 2023 https://dl.acm.org/doi/10.1145/3544548.3581015

7. ### ४උɿͭͷ؍఺ʹ஫໨͢Δ 8 1. Decision Accuracy 3. Decision Conﬁdence 5. Fairness

2. Reliance on AI 4. Understanding of AI 6. Accountability

9. ### ४උɿ3FMJBODFPO"* 10 ໡໨తʹAIΛ৴པ →Over reliance Algorithm appreciation[4,5] AIΛ৴པ͠ͳ͍ →Under reliance

Algorithm aversion[3] AIͷΞυόΠε͕࠷ऴ൑அʹͲΕ͘Β͍ӨڹΛड͚Δ͔ʁ

12. ### ४උɿ'BJSOFTT 13 Ӊ஦ਓ͸μϝ ਓؒ͸͍͍Α ಛఆͷଐੑʹରͯ͠ෆ౰ͳ൑அΛ͠ͳ͍Α͏ʹ͢Δ[8] P(Y ∣ A = 0)

= P(Y ∣ A = 1) Y͸༧ଌ஋ɺA͸ੑผ΍ਓछͳͲͷଐੑɻଐੑ͝ͱͷ༧ଌൺ཰͕ಉ͡Ͱ͋Δ͜ͱ͕ެฏ

14. ### ࠶ܝɿͭͷ؍఺ʹ஫໨͢Δ 15 1. Decision Accuracy 3. Decision Conﬁdence 5. Fairness

2. Reliance on AI 4. Understanding of AI 6. Accountabilidy

ຊ൪λεΫͰͷཧղ౓
24. ### ࣮ݧ݁Ռɿ%FDJTJPO.BLJOH'BJSOFTT wશମతʹ͸άϧʔϓͷํ͕ެฏͳ൑அΛ΋ͨΒ͍ͯ͠Δɻͨͩ͠༗ҙࠩ͸ͳ͠ w ʹؔͯ͠ͷΈάϧʔϓͱݸਓͰ༗ҙ͕ࠩΈΒΕͨ ΔAcc 25 ूஂެฏੑ ूஂެฏੑ ूஂެฏੑ ूஂެฏੑ

ݸผެฏੑ શͯ0ʹ͍ۙ΄Ͳެฏ

26. ### ࣮ݧ݁Ռɿఆྔ݁Ռͷ·ͱΊ 27 1. Decision Accuracy ݸਓͱάϧʔϓͰେࠩͳ͍ 2. Reliance on AI

άϧʔϓ͸AIʹґଘ͕ͪ͠ 3. Reliance on AI άϧʔϓ͸ࣗ৴Λ࣋ͬͯ AIΛڋ൱͢Δ 4. Understanding on AI ݸਓͱάϧʔϓͰେࠩͳ͍ 5. Fairness ͋Δج४Ͱ͸άϧʔϓ͸ެฏʹ 6. Accountability ࠷ऴ൑அ͕ؒҧ͏ͱ͖ ݸਓ΋άϧʔϓ΋܏޲͸ಉ͡

31. ### ࢀߟจݙ <>\$IVO8FJ\$IJBOHBOE.JOH:JO:PV`ECFUUFSTUPQ6OEFSTUBOEJOHIVNBOSFMJBODFPONBDIJOFMFBSOJOHNPEFMTVOEFSDPWBSJBUFTIJGU <>#FO(SFFOBOE:JMJOH\$IFO5IFQSJODJQMFTBOEMJNJUTPGBMHPSJUINJOUIFMPPQEFDJTJPONBLJOH <>+FOOJGFS.-PHH +VMJB".JOTPO BOE%PO".PPSF"MHPSJUINBQQSFDJBUJPO1FPQMFQSFGFSBMHPSJUINJDUPIVNBOKVEHNFOU <>#FSLFMFZ+%JFUWPSTU +PTFQI14JNNPOT BOE\$BEF.BTTFZ"MHPSJUINBWFSTJPOQFPQMFFSSPOFPVTMZBWPJEBMHPSJUINTBGUFSTFFJOHUIFNFSS <>:PDIBOBO&#JHNBOBOE,VSU(SBZ1FPQMFBSFBWFSTFUPNBDIJOFTNBLJOHNPSBMEFDJTJPOT

<>-FBI\$IPOH (VBOHMV;IBOH ,PTB(PVDIFS-BNCFSU ,FOOFUI,PUPWTLZ BOE+POBUIBO\$BHBO)VNBODPOGEFODFJOBSUJGDJBMJOUFMMJHFODF BOEJOUIFNTFMWFT5IFFWPMVUJPOBOEJNQBDUPGDPOGEFODFPOBEPQUJPOPG"*BEWJDF <>7JWJBO-BJ )BO-JV BOE\$IFOIBP5BO8IZJT`\$IJDBHP`EFDFQUJWF 5PXBSET#VJMEJOH.PEFM%SJWFO5VUPSJBMTGPS)VNBOT <>+VMJB"OHXJO +FG-BSTPO 4VSZB.BUUV BOE-BVSFO,JSDIOFS.BDIJOF#JBT1SP1VCMJDB 32