{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:13:46Z","timestamp":1750220026314,"version":"3.41.0"},"reference-count":17,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2022,7,1]],"date-time":"2022-07-01T00:00:00Z","timestamp":1656633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGecom Exch."],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>\n            Many policies allocate harms or benefits that are\n            <jats:italic>uncertain<\/jats:italic>\n            in nature: they produce distributions over the population in which individuals have different probabilities of incurring harm or benefit. Comparing different policies thus involves a comparison of their corresponding probability distributions, and we observe that in many instances the policies selected in practice are hard to explain by preferences based only on the expected value of the total harm or benefit they produce. In cases where the expected value analysis is not a sufficient explanatory framework, what would be a reasonable model for societal preferences over these distributions? Here we investigate explanations based on the framework of\n            <jats:italic>probability weighting<\/jats:italic>\n            from the behavioral sciences, which over several decades has identified systematic biases in how people perceive probabilities. We show that probability weighting can be used to make predictions about preferences over probabilistic distributions of harm and benefit that function quite differently from expected-value analysis, and in a number of cases provide potential explanations for policy preferences that appear hard to motivate by other means. In particular, we identify optimal policies for minimizing perceived total harm and maximizing perceived total benefit that take the distorting effects of probability weighting into account, and we discuss a number of real-world policies that resemble such allocational strategies. Our analysis does not provide specific recommendations for policy choices, but is instead interpretive in nature, seeking to describe observed phenomena in policy choices.\n          <\/jats:p>","DOI":"10.1145\/3572885.3572889","type":"journal-article","created":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T17:05:57Z","timestamp":1669655157000},"page":"47-54","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["On modeling human perceptions of allocation policies with uncertain outcomes"],"prefix":"10.1145","volume":"20","author":[{"given":"Hoda","family":"Heidari","sequence":"first","affiliation":[{"name":"Carnegie Mellon University"}]},{"given":"Solon","family":"Barocas","sequence":"additional","affiliation":[{"name":"Microsoft Research &amp; Cornell University"}]},{"given":"Jon","family":"Kleinberg","sequence":"additional","affiliation":[{"name":"Cornell University"}]},{"given":"Karen","family":"Levy","sequence":"additional","affiliation":[{"name":"Cornell University"}]}],"member":"320","published-online":{"date-parts":[[2022,11,28]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Calabresi G. and Bobbitt P. 1978. Tragic choices. Norton.  Calabresi G. and Bobbitt P. 1978. Tragic choices. Norton."},{"key":"e_1_2_1_2_1","volume-title":"The effects of higher speed limits on traffic fatalities in the United States","author":"Farmer C. M.","year":"1993","unstructured":"Farmer , C. M. 2019. The effects of higher speed limits on traffic fatalities in the United States , 1993 --2017. Farmer, C. M. 2019. The effects of higher speed limits on traffic fatalities in the United States, 1993--2017."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007740225484"},{"volume-title":"fast and slow","author":"Kahneman D.","key":"e_1_2_1_4_1","unstructured":"Kahneman , D. 2011. Thinking , fast and slow . Macmillan . Kahneman, D. 2011. Thinking, fast and slow. Macmillan."},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Kahneman D. and Tversky A. 2013. Prospect theory: An analysis of decision under risk. In Handbook of the fundamentals of financial decision making: Part I. World Scientific 99--127.  Kahneman D. and Tversky A. 2013. Prospect theory: An analysis of decision under risk. In Handbook of the fundamentals of financial decision making: Part I. World Scientific 99--127.","DOI":"10.1142\/9789814417358_0006"},{"volume-title":"et al","year":"2019","key":"e_1_2_1_6_1","unstructured":"LEE, M. K. et al . 2019 . Webuildai : Participatory framework for algorithmic governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW , 1--35. LEE, M. K. et al. 2019. Webuildai: Participatory framework for algorithmic governance. Proceedings of the ACM on Human-Computer Interaction 3, CSCW, 1--35."},{"key":"e_1_2_1_7_1","first-page":"376","article-title":"Imagined risks and cost-benefit analysis","volume":"88","author":"Pollak R. A.","year":"1998","unstructured":"Pollak , R. A. 1998 . Imagined risks and cost-benefit analysis . The American Economic Review 88 , 2, 376 -- 380 . Pollak, R. A. 1998. Imagined risks and cost-benefit analysis. The American Economic Review 88, 2, 376--380.","journal-title":"The American Economic Review"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.2307\/3325137"},{"key":"e_1_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Prelec D. 1998. The probability weighting function. Econometrica 497--527.  Prelec D. 1998. The probability weighting function. Econometrica 497--527.","DOI":"10.2307\/2998573"},{"key":"e_1_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Quiggin J. 1991. On the optimal design of lotteries. Economica 1--16.  Quiggin J. 1991. On the optimal design of lotteries. Economica 1--16.","DOI":"10.2307\/2554972"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-68164-9_5"},{"key":"e_1_2_1_12_1","unstructured":"Selective Service System. 2020. Changes from Vietnam to now. https:\/\/www.sss.gov\/history-and-records\/changes-from-vietnam-to-now\/. Accessed: 2020-10-06.  Selective Service System. 2020. Changes from Vietnam to now. https:\/\/www.sss.gov\/history-and-records\/changes-from-vietnam-to-now\/. Accessed: 2020-10-06."},{"volume-title":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2459--2468","author":"Srivastava M.","key":"e_1_2_1_13_1","unstructured":"Srivastava , M. , Heidari , H. , and Krause , A . 2019. Mathematical notions vs. human perception of fairness: A descriptive approach to fairness for machine learning . In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2459--2468 . Srivastava, M., Heidari, H., and Krause, A. 2019. Mathematical notions vs. human perception of fairness: A descriptive approach to fairness for machine learning. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2459--2468."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.2307\/1600596"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.5840\/monist197659224"},{"volume-title":"Pricing lives: Guideposts for a safer society","author":"Viscusi W. K.","key":"e_1_2_1_16_1","unstructured":"Viscusi , W. K. 2018. Pricing lives: Guideposts for a safer society . Princeton University Press . Viscusi, W. K. 2018. Pricing lives: Guideposts for a safer society. Princeton University Press."},{"volume-title":"Proceedings of the ACM on Human-Computer Interaction 2, CSCW, 194","author":"Zhu H.","key":"e_1_2_1_17_1","unstructured":"Zhu , H. , Yu , B. , Halfaker , A. , and Terveen , L . 2018. Value-sensitive algorithm design: Method, case study, and lessons . Proceedings of the ACM on Human-Computer Interaction 2, CSCW, 194 . Zhu, H., Yu, B., Halfaker, A., and Terveen, L. 2018. Value-sensitive algorithm design: Method, case study, and lessons. Proceedings of the ACM on Human-Computer Interaction 2, CSCW, 194."}],"container-title":["ACM SIGecom Exchanges"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3572885.3572889","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3572885.3572889","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:38Z","timestamp":1750182698000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3572885.3572889"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":17,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["10.1145\/3572885.3572889"],"URL":"https:\/\/doi.org\/10.1145\/3572885.3572889","relation":{},"ISSN":["1551-9031"],"issn-type":[{"type":"electronic","value":"1551-9031"}],"subject":[],"published":{"date-parts":[[2022,7]]},"assertion":[{"value":"2022-11-28","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}