Using AI Alignment Theory to understand the potential pitfalls of regulatory frameworks
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Abstract (arXiv)
This paper leverages insights from Alignment Theory (AT) research, which primarily focuses on the potential pitfalls of technical alignment in Artificial Intelligence, to critically examine the European Union's Artificial Intelligence Act (EU AI Act). In the context of AT research, several key failure modes - such as proxy gaming, goal drift, reward hacking or specification gaming - have been identified. These can arise when AI systems are not properly aligned with their intended objectives. The central logic of this report is: what can we learn if we treat regulatory efforts in the same way as we treat advanced AI systems? As we systematically apply these concepts to the EU AI Act, we uncover potential vulnerabilities and areas for improvement in the regulation.
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References · 10
- 2020Artificial Intelligence, Values and Alignmentcited by 443
- 2023AI Alignment: A Comprehensive Surveycited by 256
- 2023An Overview of Catastrophic AI Riskscited by 214
- 2021Trustworthy AI: A Computational Perspectivecited by 93
- 2023Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitmentcited by 32
- 2018FactSheets: Increasing Trust in AI Services through Supplier's Declarations of Conformitycited by 31
- 2022D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Biascited by 18
- 2023Generalized Disparate Impact for Configurable Fairness Solutions in MLcited by 7
- 2023Monitoring Algorithmic Fairness under Partial Observationscited by 7
- 2023Fairness in AI and Its Long-Term Implications on Societycited by 2
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