Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets
Fuente:
arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866911846246645760 |
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| author | Somerstep, Seamus Sun, Yuekai Ritov, Ya'acov |
| author_facet | Somerstep, Seamus Sun, Yuekai Ritov, Ya'acov |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_13240 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets Somerstep, Seamus Sun, Yuekai Ritov, Ya'acov Machine Learning Computer Science and Game Theory 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. |
| title | Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets |
| topic | Machine Learning Computer Science and Game Theory |
| url | https://arxiv.org/abs/2404.13240 |