Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets
Machine Learning
2024-04-23 v1 Computer Science and Game Theory
Machine Learning
Abstract
Motivated by equilibrium models of labor markets, we develop a formulation of causal strategic classification in which strategic agents can directly manipulate their outcomes. As an application, we compare employers that anticipate the strategic response of a labor force with employers that do not. We show through a combination of theory and experiment that employers with performatively optimal hiring policies improve employer reward, labor force skill level, and in some cases labor force equity. On the other hand, we demonstrate that performative employers harm labor force utility and fail to prevent discrimination in other cases.
Keywords
Cite
@article{arxiv.2404.13240,
title = {Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets},
author = {Seamus Somerstep and Yuekai Sun and Ya'acov Ritov},
journal= {arXiv preprint arXiv:2404.13240},
year = {2024}
}
Comments
22 pages, 5 figures