# Using AI Alignment Theory to understand the potential pitfalls of regulatory frameworks

arXiv: https://arxiv.org/abs/2410.19749 · HTML: https://mlsanity.com/paper/2410.19749/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 33 references that are in the map.
- First posted on arXiv 10 Oct 2024.

## Builds on (most cited first, 10 of 10)

- [Artificial Intelligence, Values and Alignment](https://mlsanity.com/paper/2001.09768/) (2020)
- [AI Alignment: A Comprehensive Survey](https://mlsanity.com/paper/2310.19852/) (2023)
- [An Overview of Catastrophic AI Risks](https://mlsanity.com/paper/2306.12001/) (2023)
- [Trustworthy AI: A Computational Perspective](https://mlsanity.com/paper/2107.06641/) (2021)
- [Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment](https://mlsanity.com/paper/2302.10908/) (2023)
- [FactSheets: Increasing Trust in AI Services through Supplier's Declarations of Conformity](https://mlsanity.com/paper/1808.07261/) (2018)
- [D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Bias](https://mlsanity.com/paper/2208.05126/) (2022)
- [Generalized Disparate Impact for Configurable Fairness Solutions in ML](https://mlsanity.com/paper/2305.18504/) (2023)
- [Monitoring Algorithmic Fairness under Partial Observations](https://mlsanity.com/paper/2308.00341/) (2023)
- [Fairness in AI and Its Long-Term Implications on Society](https://mlsanity.com/paper/2304.09826/) (2023)

## 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.