A Case for AI Safety via Law
Not on the map. Why?
Abstract (arXiv)
How to make artificial intelligence (AI) systems safe and aligned with human values is an open research question. Proposed solutions tend toward relying on human intervention in uncertain situations, learning human values and intentions through training or observation, providing off-switches, implementing isolation or simulation environments, or extrapolating what people would want if they had more knowledge and more time to think. Law-based approaches--such as inspired by Isaac Asimov--have not been well regarded. This paper makes a case that effective legal systems are the best way to address AI safety. Law is defined as any rules that codify prohibitions and prescriptions applicable to particular agents in specified domains/contexts and includes processes for enacting, managing, enforcing, and litigating such rules.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 81 references that are in the map. First posted on arXiv 31 Jul 2023.
Builds on
12 of 81 references.
References · 12
- 2017Deep reinforcement learning from human preferencescited by 3,846
- 2022Constitutional AI: Harmlessness from AI Feedbackcited by 2,950
- 2016Concrete Problems in AI Safetycited by 1,582
- 2023Are Emergent Abilities of Large Language Models a Mirage?cited by 515
- 2018AI safety via debatecited by 384
- 2018The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigationcited by 159
- 2019Optimal Policies Tend to Seek Powercited by 115
- 2016Research Priorities for Robust and Beneficial Artificial Intelligencecited by 74
- 2017A Voting-Based System for Ethical Decision Makingcited by 55
- 2022Law Informs Code: A Legal Informatics Approach to Aligning Artificial Intelligence with Humanscited by 23
- 2021Learning Altruistic Behaviours in Reinforcement Learning without External Rewardscited by 8
- 2023The Construction of Reality in an AI: A Reviewcited by 1
Built on by
Not cited yet.