͍·ͷਓೳෳࡶͳจষͷཧղ͕ۤखͰ͋Δ 10 αϦʔΧΰΛ͍࣋ͬͯ·͢ɻΞϯശΛ͍࣋ͬͯ·͢ɻαϦʔ ϏʔۄΛ͍࣋ͬͯ·͢ɻαϦʔϏʔۄΛࣗͷΧΰʹ͍·͠ ͨɻαϦʔ֎ʹग़͔͚·ͨ͠ɻΞϯɺΧΰ͔ΒϏʔۄΛऔΓग़ ͠ɺࣗͷശʹ͍·ͨ͠ɻαϦʔ͕͖ͬͯ·ͨ͠ɻαϦʔ ϏʔۄͰ༡΅͏ͱ͍ͯ͠·͢ɻͯ͞ɺαϦʔͲ͜Λ୳͢Ͱ͠ΐ͏ ͔ɻ S. Baron-Cohen et al.: Does the Autistic Child have a “Theory of mind” ? Cognition, Vol. 21, Issue 1, 1985. ຊޠ༁ߨࢣʹΑΔɻ
7J[8J[ࢹ֮ো͕͍ऀͷ࣭ԠγεςϜ 15 -tap to take a photo. -tap to begin recording your question and again to stop.
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? Web Server - Database - Local Client Remote Services and Worker Interface 4UFQϢʔβ͕࣭Λߘ ίʔϯͷ؈ͲΕʁ 4UFQγεςϜ෦ͷਓ͕ؒճ Ұ൪ӈͷ؈Ͱ͢ J. P. Bigham et al.: VizWiz: Nearly Real-time Answers to Visual Questions. In Proceedings of the 23rd annual ACM symposium on User interface software and technology (UIST), 2010.
;FOTPSTਓؒΛͬͨࢹγεςϜ 17 G Laput et al. Zensors: Adaptive, Rapidly Deployable, Human-Intelligent Sensor Feeds. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI), 2015. How many glasses need a re fi ll? or… I can’t Tell https://www.dreamstime.com/empty-white- wine-glasses-table-restaurant-bar-setting- close-up-alcohol-image215682647 ͓͖ʹਓؒʹը૾Λૹ৴ͯ͠
ਓؒͰͳ͘ਓೳΛར༻ G. Laput et al. Zensors: Adaptive, Rapidly Deployable, Human-Intelligent Sensor Feeds. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI), 2015.
SF$"15$)"ɿॻ੶ͷจࣈೝࣝγεςϜʹਓؒΛΈࠐΉ 23 morning 4UFQ݁Ռ͕ෆҰகͷͱ͖ʹਓؒʹ͍߹ΘͤΔ moroiog morpipg 4UFQॻ੶தͷจࣈΛ̎ͭͷਓೳγεςϜʹೝࣝͤ͞Δ L. von Ahn et al.: reCAPTCHA: Human-Based Character Recognition via Web Security Measures. Science, Vol. 321, Issue 589, 2008. ਓೳʹ͍͠จࣈΛਓؒʹೝࣝͤ͞Δ
ʮਓ͔ؒϘοτ͔ͷఆʯͱʮॻ੶ͷจࣈೝࣝʯΛಉ࣌ʹߦ͏ 25 ᶃਓ͔ؒϘοτ͔ͷఆɹᶄॻ੶ͷจࣈೝࣝ SF$"15$)"ͷత Type the word Type the word reCAPTCHA ೋͭͷจࣈΛೝࣝ͢ΔΑ͏ʹࢦࣔ͢Δ ˞ͲͪΒ͕ਖ਼ղط͔͑ͳ͍ ਖ਼ղط ਖ਼ղະ L. von Ahn et al.: reCAPTCHA: Human-Based Character Recognition via Web Security Measures. Science, Vol. 321, Issue 589, 2008. ᶄʮਓؒɹʯͷ݁Ռ͚ͩΛ
࣭อূͷͨΊʹʮਓؒʯͷճ͚ͩ࠾༻͢Δ 26 overlooks morning reCAPTCHA ਖ਼ղط ਖ਼ղະ L. von Ahn et al.: reCAPTCHA: Human-Based Character Recognition via Web Security Measures. Science, Vol. 321, Issue 589, 2008. ਖ਼ղͳͷͰ
ʮϘοτʯͷճ࠾༻͠ͳ͍ 27 overfooRs morpipg reCAPTCHA ਖ਼ղط ਖ਼ղະ L. von Ahn et al.: reCAPTCHA: Human-Based Character Recognition via Web Security Measures. Science, Vol. 321, Issue 589, 2008. ෆਖ਼ղͳͷͰ
ti ਖ਼ղ YES ti = NO ti = yij βj ճ ճϞσϧʢ ʹର͢Δճऀ ͷճʣ i j αj Pr[yij ∣ ti = 1] = αyij j (1 − αj )(1−yij ) Pr[yij ∣ ti = 0] = β(1−yij ) j (1 − βj )yij ճϞσϧΛߏஙͯ͠ਖ਼ղ༧ଌʹ༻͍Δ 35 ɿճऀ ͕ਖ਼ղ͕YESͷʹYESͱ͑Δ֬ αj j ɿճऀ ͕ਖ਼ղ͕NOͷʹNOͱ͑Δ֬ βj j ճऀͷ৴པੑύϥϝʔλʢࠞಉߦྻʣ ճ YES NO ਖ਼
ղ YES NO αj βj 1 − αj 1 − βj ࠞಉߦྻ A. P. Dawid and A. M. Skene: Maximum likelihood estimation of observer error-rates using the EM algorithm. Journal of the Royal Statistical Society, Series C (Applied Statistics), 1979.
˔ ଞਓͷ͑Λ͍ղ͔ͤΔ͜ͱͰਖ਼͍͑͠ΛҾ͖ग़͢ ˙ 4PZMFOUਓؒΛͬͨจষߍਖ਼γεςϜ 'JOEͷ͋ΔՕॴͷݕग़ 'JYߍਖ਼ͷ࣮ࢪ 7FSJGZߍਖ਼͕ਖ਼͍͔֬͠ೝ ྻ߹ͤʹΑΔ࣭อূ 36 When the crowd is finished, Soylent calls out the edited sections with a purple dashed underline. If the user clicks on the error, a drop-down menu explains the problem and offers a list of alternatives. By clicking on the desired alter- native, the user replaces the incorrect text with an option of Figure 2. Crowdproof is a human-augmented proofreader. The drop-down explains the problem (blue title) and suggests fixes (gold selection). M. S. Bernstein et al.: Soylent: a Word Processor with a Crowd Inside. Communications of the ACM, Vol. 58, Issue 8, 2015. Find Fix Verify
˔ %"31"3FE#BMMPPO$IBMMFOHF͍෩ધΛ୳͢ίϯςετ ˙ શถՕॴʹ͍෩ધ🎈Λઃஔ ˙ ࠷ॳʹશͯͷ͍෩ધΛݟ͚ͭͨνʔϜʹ͕ۚࢧΘΕΔ ˙ ༏উνʔϜʮ෩ધΛݟ͚ͭͦ͏ͳਓʯΛଞऀ͔ΒͷਪનͰൃݟ ਪનʹΑΔ࣭อূ 37 contributed articles platform for viral collaboration that used recursive incentives to align the public’s interest with the goal of win- ning the Challenge. This approach was inspired by the work of Peter S. Dodds et al.5 that found that success in us- ing social networks to tackle widely distributed search problems depends on individual incentives. The work of Mason and Watts7 also informed the use of financial incentives to motivate crowdsourcing productivity. The MIT team’s winning strategy was to use the prize money as a finan- cial incentive structure rewarding not only the people who correctly located balloons but also those connecting the finder to the MIT team. Should the team win, they would allocate $4,000 in prize money to each balloon. They promised $2,000 per balloon to the Figure 1. Locations in the DARPA Red Balloon Challenge. Figure 2. Example recursive incentive-structure process for the MIT team. J. C. Tang et al.: Re fl ecting on the DARPA Red Balloon Challenge. Communications of the ACM, Vol. 54, Issue 11, 2011.