A Case for AI Safety via Law
This work proposes a foundational shift in AI safety strategies, potentially impacting all stakeholders in AI development and regulation by advocating for law-based solutions over technical or human-centric methods.
The paper argues that legal systems, defined as codified rules with enforcement mechanisms, are the most effective approach to ensuring AI safety and alignment with human values, addressing the open research question of how to make AI systems safe.
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.