Revisiting the Predictability of Performative, Social Events
Juan Carlos Perdomo
摘要
Social predictions do not passively describe the future; they actively shape it. They inform actions and change individual expectations in ways that influence the likelihood of the predicted outcome. Given these dynamics, to what extent can social events be predicted? This question was discussed throughout the 20th century by authors like Merton, Morgenstern, Simon, and others who considered it a central issue in social science methodology. In this work, we provide a modern answer to this old problem. Using recent ideas from performative prediction and outcome indistinguishability, we establish that one can always efficiently predict social events accurately, regardless of how predictions influence data. While achievable, we also show that these predictions are often undesirable, highlighting the limitations of previous desiderata. We end with a discussion of various avenues forward.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它它引用的顶会 Paper6
- Stochastic Optimization for Performative PredictionCelestine Mendler-Dünner, Juan C. Perdomo, Tijana Zrnic, Moritz HardtNeurIPS 2020 · 被引用 161 次
- Outside the Echo Chamber: Optimizing the Performative RiskJohn Miller, Juan C. Perdomo, Tijana ZrnicICML 2021 · 被引用 128 次
- Near-Optimal Algorithms for OmnipredictionPrincewill Okoroafor, Robert Kleinberg, Michael P. KimFOCS 2025 · 被引用 37 次
- Outcome indistinguishabilityCynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum 等STOC 2021 · 被引用 24 次
- Tight Lower Bounds and Improved Convergence in Performative PredictionPedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien 等NeurIPS 2025 · 被引用 6 次
相关 Paper
- The Relative Value of Prediction in Algorithmic Decision MakingJuan Carlos PerdomoICML 2024 · 被引用 14 次
- Anticipating Performativity by Predicting from PredictionsCelestine Mendler-Dünner, Frances Ding, Yixin WangNeurIPS 2022 · 被引用 52 次
- Conditional Forecasts and Proper Scoring Rules for Reliable and Accurate Performative PredictionsPhilip A. Boeken, Onno Zoeter, Joris M. MooijNeurIPS 2025 · 被引用 1 次
- On Measuring Influence in Avoiding Undesired FutureLue Tao, Tian-Zuo Wang, Yuan Jiang, Zhi-Hua ZhouICLR 2026
- Performative Risk Control: Calibrating Models for Reliable Deployment under PerformativityVictor Li, Baiting Chen, Yuzhen Mao, Qi Lei 等NeurIPS 2025 · 被引用 2 次
