Exposing Algorithmic Discrimination and Its Consequences in Modern Society: Insights from a Scoping Study
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866916093906386944 |
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| author | Dehal, Ramandeep Singh Sharma, Mehak Santos, Ronnie de Souza |
| author_facet | Dehal, Ramandeep Singh Sharma, Mehak Santos, Ronnie de Souza |
| contents | Algorithmic discrimination is a condition that arises when data-driven software unfairly treats users based on attributes like ethnicity, race, gender, sexual orientation, religion, age, disability, or other personal characteristics. Nowadays, as machine learning gains popularity, cases of algorithmic discrimination are increasingly being reported in several contexts. This study delves into various studies published over the years reporting algorithmic discrimination. We aim to support software engineering researchers and practitioners in addressing this issue by discussing key characteristics of the problem |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_04832 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Exposing Algorithmic Discrimination and Its Consequences in Modern Society: Insights from a Scoping Study Dehal, Ramandeep Singh Sharma, Mehak Santos, Ronnie de Souza Software Engineering Algorithmic discrimination is a condition that arises when data-driven software unfairly treats users based on attributes like ethnicity, race, gender, sexual orientation, religion, age, disability, or other personal characteristics. Nowadays, as machine learning gains popularity, cases of algorithmic discrimination are increasingly being reported in several contexts. This study delves into various studies published over the years reporting algorithmic discrimination. We aim to support software engineering researchers and practitioners in addressing this issue by discussing key characteristics of the problem |
| title | Exposing Algorithmic Discrimination and Its Consequences in Modern Society: Insights from a Scoping Study |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2312.04832 |