{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T18:46:11Z","timestamp":1782758771551,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":102,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T00:00:00Z","timestamp":1782345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Austrian Science Fund","award":["10.55776\/COE12"],"award-info":[{"award-number":["10.55776\/COE12"]}]},{"name":"Austrian Research Promotion Agency","award":["FO999904624"],"award-info":[{"award-number":["FO999904624"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,6,25]]},"DOI":"10.1145\/3805689.3806808","type":"proceedings-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T17:52:08Z","timestamp":1782755528000},"page":"4610-4629","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["AI of the People, by the People, for the People: A Social Choice Approach to Collective Control of Artificial Intelligence"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5600-8876","authenticated-orcid":false,"given":"Paul Anton","family":"Bachmann","sequence":"first","affiliation":[{"name":"Institute of Logic and Computation, TU Wien, Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5102-449X","authenticated-orcid":false,"given":"Niclas","family":"Boehmer","sequence":"additional","affiliation":[{"name":"Hasso Plattner Institute, University of Potsdam, Potsdam, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3650-9733","authenticated-orcid":false,"given":"Lukas Daniel","family":"Klausner","sequence":"additional","affiliation":[{"name":"Center for Artificial Intelligence, University of Applied Sciences St. P\u00f6lten, St. P\u00f6lten, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2170-0770","authenticated-orcid":false,"given":"Martin","family":"Lackner","sequence":"additional","affiliation":[{"name":"Center for Artificial Intelligence, University of Applied Sciences St. P\u00f6lten, St. P\u00f6lten, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,6,25]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3690653"},{"key":"e_1_3_2_1_2_1","volume-title":"Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (Eindhoven) (UAI 2022\/Proceedings of Machine Learning Research 180)","author":"Allouche Tahar","year":"2022","unstructured":"Tahar Allouche, J\u00e9r\u00f4me Lang, and Florian Yger. 2022. Multi-Winner Approval Voting Goes Epistemic. In Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (Eindhoven) (UAI 2022\/Proceedings of Machine Learning Research 180). JMLR and Microtome Publishing, Cambridge, MA, 75\u201384. https:\/\/proceedings.mlr.press\/v180\/allouche22a.html"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE-SEIP.2019.00042"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1609\/AIMAG.v28i4.2065"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.PATTER.2024.101027"},{"key":"e_1_3_2_1_6_1","volume-title":"Advances in Neural Information Processing Systems 34 (Virtual Only) (NeurIPS","author":"Anil Cem","year":"2021","unstructured":"Cem Anil and Xuchan Bao. 2021. Learning to Elect. In Advances in Neural Information Processing Systems 34 (Virtual Only) (NeurIPS 2021). Curran Associates, Red Hook, NY, 8006\u20138017. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2021\/hash\/42d6c7d61481d1c21bd1635f59edae05-Abstract.html"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1609\/AIMAG.v36i1.2564"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1609\/AAAI.v28i2.19016"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1086\/729938"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/S43681-025-00734-4"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","unstructured":"Yuntao Bai Saurav Kadavath Sandipan Kundu Amanda Askell Jackson Kernion Andy Jones Anna Chen Anna Goldie Azalia Mirhoseini Cameron McKinnon Carol Chen Catherine Olsson Christopher Olah Danny Hernandez Dawn Drain Deep Ganguli Dustin Li Eli Tran-Johnson Ethan Perez Jamie Kerr Jared Mueller Jeffrey Ladish Joshua Landau Kamal Ndousse Kamile Lukosuite Liane Lovitt Michael Sellitto Nelson Elhage Nicholas Schiefer Noemi Mercado Nova DasSarma Robert Lasenby Robin Larson Sam Ringer Scott Johnston Shauna Kravec Sheer El Showk Stanislav Fort Tamera Lanham Timothy Telleen-Lawton Tom Conerly Tom Henighan Tristan Hume Samuel R. Bowman Zac Hatfield-Dodds Ben Mann Dario Amodei Nicholas Joseph Sam McCandlish Tom Brown and Jared Kaplan. 2022. Constitutional AI: Harmlessness from AI Feedback. doi:10.48550\/arXiv.2212.08073","DOI":"10.48550\/arXiv.2212.08073"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TTS.2024.3403681"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.65109\/ZKSF4462"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3630106.3658541"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.JET.2004.05.005"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Felix Brandt Vincent Conitzer Ulle Endriss J\u00e9r\u00f4me Lang and Ariel Procaccia (Eds.). 2016. Handbook of Computational Social Choice. Cambridge University Press Cambridge.","DOI":"10.1017\/CBO9781107446984.002"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467411"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1609\/AAAI.v32i1.11457"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.EJOR.2021.10.005"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/SAUPEC\/RobMech\/PRASA48453.2020.9041099"},{"key":"e_1_3_2_1_21_1","unstructured":"Stephen Casper Xander Davies Claudia Shi Thomas Krendl Gilbert J\u00e9r\u00e9my Scheurer Javier Rando Rachel Freedman Tomasz Korbak David Lindner Pedro Freire Tony Wang Samuel Marks Charbel-Rapha\u00ebl S\u00e9gerie Micah Carroll Andi Peng Phillip Christoffersen Mehul Damani Stewart Slocum Usman Anwar Anand Siththaranjan Max Nadeau Eric J. Michaud Jacob Pfau Dmitrii Krasheninnikov Xin Chen Lauro Langosco Peter Hase Erdem Biyik Anca Dragan David Krueger Dorsa Sadigh and Dylan Hadfield-Menell. 2023. Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. Trans. Mach. Learn. Res. (2023). https:\/\/openreview.net\/forum?id=bx24KpJ4Eb"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2412.17114"},{"key":"e_1_3_2_1_23_1","unstructured":"Collective Intelligence Project. 2023. The Collective Intelligence Project. 8 pages. https:\/\/www.cip.org\/whitepaper"},{"key":"e_1_3_2_1_24_1","volume-title":"Proceedings of the 41st International Conference on Machine Learning","author":"Conitzer Vincent","year":"2024","unstructured":"Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Mosse, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, and William S. Zwicker. 2024. Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback. In Proceedings of the 41st International Conference on Machine Learning (Vienna) (ICML 2024\/Proceedings of Machine Learning Research 235). JMLR and Microtome Publishing, Cambridge, MA, 9346\u20139360. https:\/\/proceedings.mlr.press\/v235\/conitzer24a.html"},{"key":"e_1_3_2_1_25_1","first-page":"1","article-title":"The Measure and Mismeasure of Fairness","volume":"24","author":"Corbett-Davies Sam","year":"2023","unstructured":"Sam Corbett-Davies, Johann D. Gaebler, Hamed Nilforoshan, Ravi Shroff, and Sharad Goel. 2023. The Measure and Mismeasure of Fairness. J. Mach. Learn. Res. 24, 312 (2023), 1\u2013117. http:\/\/jmlr.org\/papers\/v24\/22-1511.html","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533213"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","unstructured":"Santiago del Rey Lu\u00eds Cruz Xavier Franch and Silverio Mart\u00ednez-Fern\u00e1ndez. 2025. Estimating Deep Learning Energy Consumption Based on Model Architecture and Training Environment. doi:10.48550\/arXiv.2307.05520","DOI":"10.48550\/arXiv.2307.05520"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2025\/424"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i13.33509"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i20.30273"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.3233\/FAIA230324"},{"key":"e_1_3_2_1_32_1","first-page":"27","article-title":"Multiwinner Voting: A New Challenge for Social Choice Theory. In Trends in Computational Social Choice, Ulle Endriss (Ed.). AI Access Foundation, El Segundo, CA","volume":"2","author":"Faliszewski Piotr","year":"2017","unstructured":"Piotr Faliszewski, Piotr Skowron, Arkadii Slinko, and Nimrod Talmon. 2017. Multiwinner Voting: A New Challenge for Social Choice Theory. In Trends in Computational Social Choice, Ulle Endriss (Ed.). AI Access Foundation, El Segundo, CA, Chapter 2, 27\u201347. https:\/\/archive.illc.uva.nl\/COST-IC1205\/BookDocs\/Chapters\/TrendsCOMSOC-02.pdf","journal-title":"Chapter"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.JET.2021.105234"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/639"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1137\/090756740"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1002\/9781394238651.ch26"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/S11023-020-09539-2"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.52202\/079017-2557"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-03107-6"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","unstructured":"Samuel J. Gershman. 2025. Subjective Functions. doi:10.48550\/arXiv.2512.15948","DOI":"10.48550\/arXiv.2512.15948"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.18653\/V1\/2023.EMNLP-MAIN.539"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3593013.3594067"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1007\/S43681-021-00122-8"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i5.25702"},{"key":"e_1_3_2_1_45_1","unstructured":"High-Level Expert Group on Artificial Intelligence. 2019. Ethics Guidelines for Trustworthy AI. 39 pages. https:\/\/digital-strategy.ec.europa.eu\/en\/library\/ethics-guidelines-trustworthy-ai"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1613\/JAIR.1.18890"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3630106.3658979"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.JSS.2025.112373"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3770749"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3715275.3732069"},{"key":"e_1_3_2_1_51_1","volume-title":"No. 16948","author":"Kasy Maximilian","unstructured":"Maximilian Kasy. 2024. The Political Economy of AI: Towards Democratic Control of the Means of Prediction. IZA Discussion Papers, No. 16948. Institute of Labor Economics (IZA), Bonn. https:\/\/hdl.handle.net\/10419\/295971"},{"key":"e_1_3_2_1_52_1","volume-title":"The Means of Prediction: How AI Really Works (and Who Benefits)","author":"Kasy Maximilian","unstructured":"Maximilian Kasy. 2025. The Means of Prediction: How AI Really Works (and Who Benefits). University of Chicago Press, Hoboken, NJ."},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1609\/AAAI.v34i02.5584"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i5.25710"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-09016-5"},{"key":"e_1_3_2_1_56_1","volume-title":"What Categories Reveal about the Mind","author":"Lakoff George","unstructured":"George Lakoff. 1987. Women, Fire, and Dangerous Things: What Categories Reveal about the Mind. University of Chicago Press, Chicago, IL."},{"key":"e_1_3_2_1_57_1","volume-title":"Stanford Encyclopedia of Philosophy, Edward N","author":"List Christian","year":"2022","unstructured":"Christian List.2022. Social Choice Theory. In Stanford Encyclopedia of Philosophy, Edward N.Zalta and Uri Nodelman (Eds.).Metaphysics Research Lab, Stanford University, Stanford, CA. https:\/\/plato.stanford.edu\/archives\/win2022\/entries\/social-choice\/"},{"key":"e_1_3_2_1_58_1","volume-title":"Proceedings of the 2nd Workshop on Models of Human Feedback for AI Alignment at the 42nd International Conference on Machine Learning","author":"Lowe Ryan","year":"2025","unstructured":"Ryan Lowe, Joe Edelman, Tan Zhi-Xuan, Oliver Klingefjord, Ellie Hain, Vincent Wang, Atrisha Sarkar, Michiel A. Bakker, Fazl Barez, Matija Franklin, Andreas Haupt, Jobst Heitzig, Wesley H. Holliday, Julian Jara-Ettinger, Atoosa Kasirzadeh, Ryan Othniel Kearns, James Ravi Kirkpatrick, Andrew Koh, Joel Lehman, Sydney Levine, Manon Revel, and Ivan Vendrov. 2025. Full-Stack Alignment: Co-Aligning AI and Institutions with Thicker Models of Value. In Proceedings of the 2nd Workshop on Models of Human Feedback for AI Alignment at the 42nd International Conference on Machine Learning (Vancouver) (MoFA 2025). JMLR and Microtome Publishing, Cambridge, MA."},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2876857"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.ARTINT.2019.103203"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.3390\/FORECAST5030030"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","unstructured":"Saptarshi Mandal Xiaojun Lin and Rayadurgam Srikant. 2024. A Theoretical Analysis of Soft-Label vs Hard-Label Training in Neural Networks. doi:10.48550\/arXiv.2412.09579","DOI":"10.48550\/arXiv.2412.09579"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","unstructured":"Leonardo Matone Ben Abramowitz Ben Armstrong Avinash Balakrishnan and Nicholas Mattei. 2024. DeepVoting: Learning and Fine-Tuning Voting Rules with Canonical Embeddings. doi:10.48550\/arXiv.2408.13630","DOI":"10.48550\/arXiv.2408.13630"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1038\/S41746-023-00873-0"},{"key":"e_1_3_2_1_65_1","unstructured":"Metagov. 2025. Collective Governance for AI: Points of Intervention. 8 pages. https:\/\/metagov.org\/cg-ai\/"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.IS.2025.102549"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1613\/JAIR.1.13734"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00128122"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.2307\/2297154"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1017\/CCOL0521360552"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1016\/0022-0531(88)90253-0"},{"key":"e_1_3_2_1_72_1","doi-asserted-by":"publisher","DOI":"10.1609\/AAAI.v32i1.11512"},{"key":"e_1_3_2_1_73_1","volume-title":"Proceedings of the 42nd International Conference on Machine Learning","author":"Ovadya Aviv","year":"2025","unstructured":"Aviv Ovadya, Kyle Redman, Luke Thorburn, Quan Ze Chen, Oliver Smith, Flynn Devine, Andrew Konya, Smitha Milli, Manon Revel, Kevin Feng, Amy X. Zhang, Bilva Chandra, Michiel A. Bakker, and Atoosa Kasirzadeh. 2025. Position: Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work. In Proceedings of the 42nd International Conference on Machine Learning (Vancouver) (ICML 2025\/Proceedings of Machine Learning Research 267). JMLR and Microtome Publishing, Cambridge, MA, 81930\u201381961. https:\/\/proceedings.mlr.press\/v267\/ovadya25a.html"},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1609\/AAAI.v27i1.8570"},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.PATTER.2021.100336"},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00971"},{"key":"e_1_3_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1007\/S00355-011-0619-1"},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.18653\/V1\/2022.EMNLP-MAIN.731"},{"key":"e_1_3_2_1_79_1","doi-asserted-by":"publisher","unstructured":"Emmanouil Antonios Platanios Maruan Al-Shedivat Eric Xing and Tom Mitchell. 2020. Learning from Imperfect Annotations. doi:10.48550\/arXiv.2004.03473","DOI":"10.48550\/arXiv.2004.03473"},{"key":"e_1_3_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-84748-6_7"},{"key":"e_1_3_2_1_81_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.ARTINT.2009.03.003"},{"key":"e_1_3_2_1_82_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372873"},{"key":"e_1_3_2_1_83_1","volume-title":"Introduction to Machine Learning Systems","author":"Reddi Vijay Janapa","unstructured":"Vijay Janapa Reddi. 2026. Introduction to Machine Learning Systems. MIT Press, Cambridge, MA. https:\/\/mlsysbook.ai\/"},{"key":"e_1_3_2_1_84_1","volume-title":"Statistical Inference, and Applications","author":"Regenwetter Michel","unstructured":"Michel Regenwetter, Bernard Grofman, A. A. J. Marley, and Ilia Tsetlin. 2006. Behavioral Social Choice: Probabilistic Models, Statistical Inference, and Applications. Cambridge University Press, Cambridge."},{"key":"e_1_3_2_1_85_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-032-11108-1_8"},{"key":"e_1_3_2_1_86_1","doi-asserted-by":"publisher","DOI":"10.1111\/JAPP.12363"},{"key":"e_1_3_2_1_87_1","doi-asserted-by":"publisher","DOI":"10.1145\/3600211.3604693"},{"key":"e_1_3_2_1_88_1","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287598"},{"key":"e_1_3_2_1_89_1","doi-asserted-by":"publisher","DOI":"10.1001\/JAMA.2023.14217"},{"key":"e_1_3_2_1_90_1","doi-asserted-by":"publisher","DOI":"10.1145\/3551624.3555285"},{"key":"e_1_3_2_1_91_1","volume-title":"Proceedings of the 41st International Conference on Machine Learning","author":"Sorensen Taylor","year":"2024","unstructured":"Taylor Sorensen, Jared Moore, Jillian Fisher, Mitchell Gordon, Niloofar Mireshghallah, Christopher Michael Rytting, Andre Ye, Liwei Jiang, Ximing Lu, Nouha Dziri, Tim Althoff, and Yejin Choi. 2024. Position: A Roadmap to Pluralistic Alignment. In Proceedings of the 41st International Conference on Machine Learning (Vienna) (ICML 2024\/Proceedings of Machine Learning Research 235). JMLR and Microtome Publishing, Cambridge, MA, 46280\u201346302. https:\/\/proceedings.mlr.press\/v235\/sorensen24a.html"},{"key":"e_1_3_2_1_92_1","article-title":"Physiognomic Artificial Intelligence","volume":"32","author":"Stark Luke","year":"2022","unstructured":"Luke Stark and Jevan Hutson. 2022. Physiognomic Artificial Intelligence. Fordham Intellect. Prop. Media Entertain. Law J. 32, 4, Article 2 (2022), 922-978 pages. https:\/\/ir.lawnet.fordham.edu\/iplj\/vol32\/iss4\/2","journal-title":"Fordham Intellect. Prop. Media Entertain. Law J."},{"key":"e_1_3_2_1_93_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1355"},{"key":"e_1_3_2_1_94_1","doi-asserted-by":"publisher","DOI":"10.1145\/3630106.3658992"},{"key":"e_1_3_2_1_95_1","doi-asserted-by":"publisher","DOI":"10.1609\/hcomp.v8i1.7478"},{"key":"e_1_3_2_1_96_1","doi-asserted-by":"publisher","DOI":"10.1613\/JAIR.1.12752"},{"key":"e_1_3_2_1_97_1","unstructured":"Working Group on Artificial Intelligence and its Implications for the Information and Communication Space. 2024. AI as a Public Good: Ensuring Democratic Control of AI in the Information Space. 141 pages. https:\/\/informationdemocracy.org\/wp-content\/uploads\/2024\/03\/ID-AI-as-a-Public-Good-Feb-2024.pdf"},{"key":"e_1_3_2_1_98_1","doi-asserted-by":"publisher","DOI":"10.5555\/2484920.2484995"},{"key":"e_1_3_2_1_99_1","doi-asserted-by":"publisher","DOI":"10.1111\/BJET.13370"},{"key":"e_1_3_2_1_100_1","doi-asserted-by":"publisher","DOI":"10.24963\/IJCAI.2017\/184"},{"key":"e_1_3_2_1_101_1","doi-asserted-by":"publisher","DOI":"10.1007\/S11098-024-02249-W"},{"key":"e_1_3_2_1_102_1","volume-title":"Advances in Neural Information Processing Systems 38 (San Diego, CA) (NeurIPS","author":"Zimmermann Annette","year":"2025","unstructured":"Annette Zimmermann, Andrew Zeppa, Srijan Pandey, and Kenneth Diao. 2025. Don't Give Up on Democratizing AI for the Wrong Reasons. In Advances in Neural Information Processing Systems 38 (San Diego, CA) (NeurIPS 2025). Curran Associates, Red Hook, NY."}],"event":{"name":"FAccT '26: The 2026 ACM Conference on Fairness, Accountability, and Transparency","location":"Montreal QC Canada","acronym":"FAccT '26","sponsor":["ACM\/SIG"]},"container-title":["Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3805689.3806808","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T18:23:25Z","timestamp":1782757405000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3805689.3806808"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,25]]},"references-count":102,"alternative-id":["10.1145\/3805689.3806808","10.1145\/3805689"],"URL":"https:\/\/doi.org\/10.1145\/3805689.3806808","relation":{},"subject":[],"published":{"date-parts":[[2026,6,25]]},"assertion":[{"value":"2026-06-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}