Strengthening legal protection against discrimination by algorithms and artificial intelligence
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909823236308992 |
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| author | Borgesius, Frederik J. Zuiderveen |
| author_facet | Borgesius, Frederik J. Zuiderveen |
| contents | Algorithmic decision-making and other types of artificial intelligence (AI) can be used to predict who will commit crime, who will be a good employee, who will default on a loan, etc. However, algorithmic decision-making can also threaten human rights, such as the right to non-discrimination. The paper evaluates current legal protection in Europe against discriminatory algorithmic decisions. The paper shows that non-discrimination law, in particular through the concept of indirect discrimination, prohibits many types of algorithmic discrimination. Data protection law could also help to defend people against discrimination. Proper enforcement of non-discrimination law and data protection law could help to protect people. However, the paper shows that both legal instruments have severe weaknesses when applied to artificial intelligence. The paper suggests how enforcement of current rules can be improved. The paper also explores whether additional rules are needed. The paper argues for sector-specific - rather than general - rules, and outlines an approach to regulate algorithmic decision-making. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_02859 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Strengthening legal protection against discrimination by algorithms and artificial intelligence Borgesius, Frederik J. Zuiderveen Computers and Society Algorithmic decision-making and other types of artificial intelligence (AI) can be used to predict who will commit crime, who will be a good employee, who will default on a loan, etc. However, algorithmic decision-making can also threaten human rights, such as the right to non-discrimination. The paper evaluates current legal protection in Europe against discriminatory algorithmic decisions. The paper shows that non-discrimination law, in particular through the concept of indirect discrimination, prohibits many types of algorithmic discrimination. Data protection law could also help to defend people against discrimination. Proper enforcement of non-discrimination law and data protection law could help to protect people. However, the paper shows that both legal instruments have severe weaknesses when applied to artificial intelligence. The paper suggests how enforcement of current rules can be improved. The paper also explores whether additional rules are needed. The paper argues for sector-specific - rather than general - rules, and outlines an approach to regulate algorithmic decision-making. |
| title | Strengthening legal protection against discrimination by algorithms and artificial intelligence |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2510.02859 |