An Analysis of the New EU AI Act and A Proposed Standardization Framework for Machine Learning Fairness
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866914071288217600 |
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| author | Teodorescu, Mike Sun, Yongxu Bhatia, Haren N. Makridis, Christos |
| author_facet | Teodorescu, Mike Sun, Yongxu Bhatia, Haren N. Makridis, Christos |
| contents | The European Union's AI Act represents a crucial step towards regulating ethical and responsible AI systems. However, we find an absence of quantifiable fairness metrics and the ambiguity in terminology, particularly the interchangeable use of the keywords transparency, explainability, and interpretability in the new EU AI Act and no reference of transparency of ethical compliance. We argue that this ambiguity creates substantial liability risk that would deter investment. Fairness transparency is strategically important. We recommend a more tailored regulatory framework to enhance the new EU AI regulation. Further-more, we propose a public system framework to assess the fairness and transparency of AI systems. Drawing from past work, we advocate for the standardization of industry best practices as a necessary addition to broad regulations to achieve the level of details required in industry, while preventing stifling innovation and investment in the AI sector. The proposals are exemplified with the case of ASR and speech synthesizers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_01281 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Analysis of the New EU AI Act and A Proposed Standardization Framework for Machine Learning Fairness Teodorescu, Mike Sun, Yongxu Bhatia, Haren N. Makridis, Christos Computers and Society Artificial Intelligence K.4.1; K.4.2 The European Union's AI Act represents a crucial step towards regulating ethical and responsible AI systems. However, we find an absence of quantifiable fairness metrics and the ambiguity in terminology, particularly the interchangeable use of the keywords transparency, explainability, and interpretability in the new EU AI Act and no reference of transparency of ethical compliance. We argue that this ambiguity creates substantial liability risk that would deter investment. Fairness transparency is strategically important. We recommend a more tailored regulatory framework to enhance the new EU AI regulation. Further-more, we propose a public system framework to assess the fairness and transparency of AI systems. Drawing from past work, we advocate for the standardization of industry best practices as a necessary addition to broad regulations to achieve the level of details required in industry, while preventing stifling innovation and investment in the AI sector. The proposals are exemplified with the case of ASR and speech synthesizers. |
| title | An Analysis of the New EU AI Act and A Proposed Standardization Framework for Machine Learning Fairness |
| topic | Computers and Society Artificial Intelligence K.4.1; K.4.2 |
| url | https://arxiv.org/abs/2510.01281 |