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Arthur Cecil Pigou · 1920
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Kenneth J. Arrow and Gerard Debreu · 1954
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Collective Choice and Social Welfare
Amartya Sen · 1970
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Per-Olov Johansson · 1991
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Amartya Sen · 1999
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Statistical modeling: The two cultures (with comments and a rejoinder by the author)
Leo Breiman · 2001
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The foundations of cost-sensitive learning
Charles Elkan · 2001
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Learning to rank: from pairwise approach to listwise approach
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, and Hang Li · 2007
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Static prediction games for adversarial learning problems
Michael Brückner, Christian Kanzow, and Tobias Scheffer · 2012
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Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel · 2012
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The Price of Inequality: How Today’s Divided Society Endangers Our Future
Joseph E. Stiglitz · 2012
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Phishing for phools: The economics of manipulation and deception
George A Akerlof and Robert J Shiller · 2015
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Prediction policy problems
Jon Kleinberg, Jens Ludwig, Sendhil Mullainathan, and Ziad Obermeyer · 2015
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Top-k multiclass svm
Maksim Lapin, Matthias Hein, and Bernt Schiele · 2015
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Strategic classification
Moritz Hardt, Nimrod Megiddo, Christos Papadimitriou, and Mary Wootters · 2016
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Fairness behind a veil of ignorance: A welfare analysis for automated decision making
Hoda Heidari, Claudio Ferrari, Krishna Gummadi, and Andreas Krause · 2018
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Delayed impact of fair machine learning
Lydia T Liu, Sarah Dean, Esther Rolf, Max Simchowitz, and Moritz Hardt · 2018
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Estimation and inference of heterogeneous treatment effects using random forests
Stefan Wager and Susan Athey · 2018
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Measuring social welfare: An introduction
Matthew D Adler · 2019
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Differentiable convex optimization layers
Akshay Agrawal, Brandon Amos, Shane Barratt, Stephen Boyd, Steven Diamond, and J Zico Kolter · 2019
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Deep equilibrium models
Shaojie Bai, J Zico Kolter, and Vladlen Koltun · 2019
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Regression equilibrium
Omer Ben-Porat and Moshe Tennenholtz · 2019
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Information design: A unified perspective
Dirk Bergemann and Stephen Morris · 2019
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The social cost of strategic classification
Smitha Milli, John Miller, Anca D Dragan, and Moritz Hardt · 2019
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Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Cynthia Rudin · 2019
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Content provider dynamics and coordination in recommendation ecosystems
Omer Ben-Porat, Itay Rosenberg, and Moshe Tennenholtz · 2020
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Learning with differentiable pertubed optimizers
Quentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, and Francis Bach · 2020
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Differentiable top-k classification learning
Felix Petersen, Hilde Kuehne, Christian Borgelt, and Oliver Deussen · 2022
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Prediction-powered inference
Anastasios N Angelopoulos, Stephen Bates, Clara Fannjiang, Michael I Jordan, and Tijana Zrnic · 2023
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Stochastic optimization with decision-dependent distributions
Dmitriy Drusvyatskiy and Lin Xiao · 2023
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Recommending to strategic users
Andreas Haupt, Dylan Hadfield-Menell, and Chara Podimata · 2023
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Causal strategic classification: A tale of two shifts
Guy Horowitz and Nir Rosenfeld · 2023
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2023
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Daniel Björkegren, Joshua E Blumenstock, and Samsun Knight · 2020
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Invariance, causality and robustness
Peter Bühlmann · 2020
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Distributionally robust learning
Ruidi Chen, Ioannis Ch Paschalidis, et al · 2020
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Fair classification and social welfare
Lily Hu and Yiling Chen · 2020
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How do classifiers induce agents to invest effort strategically?
Jon Kleinberg and Manish Raghavan · 2020
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Predictive multiplicity in classification
Charles Marx, Flavio Calmon, and Berk Ustun · 2020
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Strategic classification is causal modeling in disguise
John Miller, Smitha Milli, and Moritz Hardt · 2020
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Delegated classification
Eden Saig, Inbal Talgam-Cohen, and Nir Rosenfeld · 2023
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How bad is top- k k recommendation under competing content creators?
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, and Haifeng Xu · 2023
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Position: Social choice should guide AI alignment in dealing with diverse human feedback
Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H Holliday, Bob M Jacobs, Nathan Lambert, Milan Mossé, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, et al · 2024
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Incentive-aware recommender systems in two-sided markets
Xiaowu Dai, Wenlu Xu, Yuan Qi, and Michael Jordan · 2024
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Modular pluralism: Pluralistic alignment via multi-LLM collaboration
Shangbin Feng, Taylor Sorensen, Yuhan Liu, Jillian Fisher, Chan Young Park, Yejin Choi, and Yulia Tsvetkov · 2024
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Generative social choice
Sara Fish, Paul Gölz, David C. Parkes, Ariel D. Procaccia, Gili Rusak, Itai Shapira, and Manuel Wüthrich · 2024
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Axioms for AI alignment from human feedback
Luise Ge, Daniel Halpern, Evi Micha, Ariel D. Procaccia, Itai Shapira, Yevgeniy Vorobeychik, and Junlin Wu · 2024
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Classification under strategic self-selection
Guy Horowitz, Yonatan Sommer, Moran Koren, and Nir Rosenfeld · 2024
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Decision-focused learning: Foundations, state of the art, benchmark and future opportunities
Jayanta Mandi, James Kotary, Senne Berden, Maxime Mulamba, Victor Bucarey, Tias Guns, and Ferdinando Fioretto · 2024
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An engine not a camera: Measuring performative power of online search
Celestine Mendler-Dünner, Gabriele Carovano, and Moritz Hardt · 2024
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Decongestion by representation: Learning to improve economic welfare in marketplaces
Omer Nahum, Gali Noti, David C. Parkes, and Nir Rosenfeld · 2024
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Learning social welfare functions
Kanad Shrikar Pardeshi, Itai Shapira, Ariel D Procaccia, and Aarti Singh · 2024
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The relative value of prediction in algorithmic decision making
Juan Carlos Perdomo · 2024
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Allocation requires prediction only if inequality is low
Ali Shirali, Rediet* Abebe, and Moritz* Hardt · 2024
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On counterfactual metrics for social welfare: Incentives, ranking, and information asymmetry
Serena Wang, Stephen Bates, P Aronow, and Michael Jordan · 2024
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User welfare optimization in recommender systems with competing content creators
Fan Yao, Yiming Liao, Mingzhe Wu, Chuanhao Li, Yan Zhu, James Yang, Jingzhou Liu, Qifan Wang, Haifeng Xu, and Hongning Wang · 2024
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Differentiable economics: Strategic behavior, mechanisms, and machine learning
Martin Bichler and David C Parkes · 2025
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A market for accuracy: Classification under competition
Ohad Einav and Nir Rosenfeld · 2025
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Strategic classification with externalities
Safwan Hossain, Evi Micha, Yiling Chen, and Ariel D. Procaccia · 2025
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Learning classifiers that induce markets
Yonatan Sommer, Ivri Hikri, Lotan Amit, and Nir Rosenfeld · 2025
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A collectivist, economic perspective on ai
Michael I. Jordan · 2026
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Strategic content creation with genai: To share or not to share?
Gur Keinan and Omer Ben-Porat · 2026
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LLM alignment should go beyond harmlessness–helpfulness and incorporate human agency
Usman Naseem, Tanmoy Chakraborty, Kai-Wei Chang, Mark Dras, Preslav Nakov, Nanyun Peng, and Soujanya Poria · 2026
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Market games for generative models: Equilibria, welfare, and strategic entry
Xiukun Wei, Min Shi, and Xueru Zhang · 2026
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