Scoring Rules for Performative Binary Prediction

Alan Chan

Scoring Rules for Performative Binary Prediction

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arxiv 2207.02847 v1 pith:BI7VA6EB submitted 2022-07-05 cs.LG cs.AI

Alan Chan This is my paper · ORCID

classification cs.LGcs.AI

keywords rulesscoringconstructmodelpredictionpredictionsworldavoids

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We construct a model of expert prediction where predictions can influence the state of the world. Under this model, we show through theoretical and numerical results that proper scoring rules can incentivize experts to manipulate the world with their predictions. We also construct a simple class of scoring rules that avoids this problem.

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Joint Scoring Rules: Zero-Sum Competition Avoids Performative Prediction
cs.LG 2024-12 conditional novelty 7.0 of 10

Joint zero-sum scoring of multiple conditional predictors lets a principal deterministically take their most preferred action without performative manipulation.

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