Statistical Discrimination in Ratings-Guided Markets
Fuente:
arXiv
Salvato in:
| Autori principali: | , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2020
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866913573786091520 |
|---|---|
| author | Che, Yeon-Koo Kim, Kyungmin Zhong, Weijie |
| author_facet | Che, Yeon-Koo Kim, Kyungmin Zhong, Weijie |
| contents | We study statistical discrimination of individuals based on payoff-irrelevant social identities in markets that utilize ratings and recommendations for social learning. Even though rating/recommendation algorithms can be designed to be fair and unbiased, ratings-based social learning can still lead to discriminatory outcomes. Our model demonstrates how users' attention choices can result in asymmetric data sampling across social groups, leading to discriminatory inferences and potential discrimination based on group identities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2004_11531 |
| institution | arXiv |
| publishDate | 2020 |
| record_format | arxiv |
| spellingShingle | Statistical Discrimination in Ratings-Guided Markets Che, Yeon-Koo Kim, Kyungmin Zhong, Weijie Computer Science and Game Theory Theoretical Economics We study statistical discrimination of individuals based on payoff-irrelevant social identities in markets that utilize ratings and recommendations for social learning. Even though rating/recommendation algorithms can be designed to be fair and unbiased, ratings-based social learning can still lead to discriminatory outcomes. Our model demonstrates how users' attention choices can result in asymmetric data sampling across social groups, leading to discriminatory inferences and potential discrimination based on group identities. |
| title | Statistical Discrimination in Ratings-Guided Markets |
| topic | Computer Science and Game Theory Theoretical Economics |
| url | https://arxiv.org/abs/2004.11531 |