Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness
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arXiv
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| Format: | Preprint |
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2024
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| author | Deck, Luca Müller, Jan-Laurin Braun, Conradin Zipperling, Domenique Kühl, Niklas |
| author_facet | Deck, Luca Müller, Jan-Laurin Braun, Conradin Zipperling, Domenique Kühl, Niklas |
| contents | The topic of fairness in AI, as debated in the FATE (Fairness, Accountability, Transparency, and Ethics in AI) communities, has sparked meaningful discussions in the past years. However, from a legal perspective, particularly from the perspective of European Union law, many open questions remain. Whereas algorithmic fairness aims to mitigate structural inequalities at design-level, European non-discrimination law is tailored to individual cases of discrimination after an AI model has been deployed. The AI Act might present a tremendous step towards bridging these two approaches by shifting non-discrimination responsibilities into the design stage of AI models. Based on an integrative reading of the AI Act, we comment on legal as well as technical enforcement problems and propose practical implications on bias detection and bias correction in order to specify and comply with specific technical requirements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_20089 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness Deck, Luca Müller, Jan-Laurin Braun, Conradin Zipperling, Domenique Kühl, Niklas Artificial Intelligence The topic of fairness in AI, as debated in the FATE (Fairness, Accountability, Transparency, and Ethics in AI) communities, has sparked meaningful discussions in the past years. However, from a legal perspective, particularly from the perspective of European Union law, many open questions remain. Whereas algorithmic fairness aims to mitigate structural inequalities at design-level, European non-discrimination law is tailored to individual cases of discrimination after an AI model has been deployed. The AI Act might present a tremendous step towards bridging these two approaches by shifting non-discrimination responsibilities into the design stage of AI models. Based on an integrative reading of the AI Act, we comment on legal as well as technical enforcement problems and propose practical implications on bias detection and bias correction in order to specify and comply with specific technical requirements. |
| title | Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2403.20089 |