博弈论研究：AI 供应链中的安全投资激励机制
Market Incentives for AI Safety Investment
一篇把 AI 安全和经济学模型结合的论文，结论挺反直觉：下游竞争反而让安全投入更多，上游供应商才是不愿意掏钱的那个，监管该盯谁一目了然。
arXiv 论文 2610.21607 用博弈论模型分析上游 LLM 供应商与多家竞争性下游企业组成的 AI 供应链中，利润最大化如何影响安全投资水平。研究发现，下游竞争促使下游企业的安全投资高于行业利润最优水平，而上游供应商因无法完全获得安全投资带来的剩余而倾向于投资不足。论文还比较了市场驱动投资水平与社会福利最大化水平的差异，并分析了不同监管干预措施对各参与方激励、利润和模型安全水平的影响。
Market Incentives for AI Safety Investment
Despite their practical significance, modern AI systems pose significant societal risks, including toxicity, malicious use, and misinformation. Their mitigation depends not only on technical feasibility but also on the incentives of firms that develop and deploy these systems. We show how profit maximization shapes safety investment in an AI supply chain with an upstream LLM provider and several competing downstream firms. In our game-theoretic model, we derive the market-driven level of safety investment and compare it with the levels that maximize market welfare and industry profit. We find that downstream competition generally induces downstream firms to invest more in safety than the industry-profit-optimal level. By contrast, the upstream provider may underinvest relative to these benchmarks because it is not fully compensated for the surplus from safety investments. Finally, we analyze how different regulatory interventions affect the participants' incentives and profits, and the resulting levels of model safety.
