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| Main Authors: | , |
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| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15773292 |
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Table of Contents:
- <p>This chapter examines how artificial intelligence (AI) bias can undermine legal (or legally relevant) norms and standards. It does so by introducing a conceptual distinction between <em>bias in AI</em> (arising from flawed data, programming choices, or emergent algorithmic behaviour) and <em>bias towards AI</em> (where human decision-makers either overtrust or unjustifiably dismiss AI outputs). This distinction can equip legal practitioners with a deeper, yet straightforward understanding of various AI biases and the risks they raise. To mitigate these risks, the chapter explores preventive and corrective strategies, including regulatory sandboxes, fairness-aware AI design, auditing laws, and legal oversight mechanisms. Addressing AI bias is not merely a technical challenge—it is a professional responsibility for legal practitioners who seek to properly navigate the relationship between law and AI.</p>