Empirically measuring the legal alignment of AI agents and the impact of AI on the rule of law
About the project
- Developing a domain-specific benchmark to evaluate whether AI agents comply with a particular area of law.
- Collecting real-world data to measure legal alignment "in the wild", especially to assess the legal compliance of commercial AI systems in deployment.
- Developing novel methods to empirically measure the impact of AI on the rule of law.
Relevant literature:
- Legal Alignment for Safe and Ethical AI (TMLR 2026) https://arxiv.org/abs/2601.04175
- Superintelligence and Law (Harvard Journal of Law & Technology) https://arxiv.org/abs/2603.28669
Theory of change
Rigorously evaluating the legal alignment of AI agents is critical to:
- identify law-violating AI agents that pose large-scale risks, either individually or through gradual disempowerment
- inform and incentivize technical work on developing law-abiding AI agents
- prompt policymakers to demand that AI agents demonstrate a satisfactory level of legal compliance prior to deployment. Empirically measuring the impact of AI on the rule of law is essential for understanding, protecting, and steering one of society's most vital institutions.
Your role
- Leading the development of a legal alignment benchmark and/or empirical study of AI's impact on the rule of law
- Researching and writing a paper for submission to a top CS conference and/or legal journal.
Prerequisites
Publication track record of at least one first-authored paper in a top CS conference (e.g., NeurIPS, AAAI, FAccT), peer-reviewed scientific journal, or U.S. law review.
About the mentor
Noam Kolt is an Assistant Professor at the Hebrew University Faculty of Law and School of Computer Science and Engineering, where he leads the Governance of AI Lab (GOAL). The lab’s mission is to support safe and ethical AI through cross-disciplinary research that integrates methods from law, computer science, and the social sciences. Areas of focus include the governance of AI agents, empirical evaluations of legal alignment, and institutional design for advanced AI. Noam’s scholarship has been published in law reviews (Washington University Law Review, Notre Dame Law Review, Harvard Journal of Law & Technology, Berkeley Technology Law Journal, Yale Law & Policy Review), computer science venues (NeurIPS, ICML, TMLR, ACM FAccT, AIES), and general-interest journals (Patterns, Science).