From Near Miss to Pause: Historical Warning Shots and AI Governance

Executive Summary: The U.S. government often fails to convert warning shots into effective legal and policy solutions for the security and safety of its citizens.  A core government function is to recognize indications of future catastrophe, then formulate successful government prevention and response.  Yet this governance gap persists. 

The gap is a significant risk for American society, especially in an era of AI.  The nation is accelerating into an AI future of greater cyber, bio, and loss of control risks, amidst ongoing public harms and dangers (Bengio et al., 2026). 

Our project aimed to address this gap.  First, we developed a clear definition of what a warning shot is, and their five criteria.  We then applied this warning shot analysis to 25 historical “candidate” cases in nuclear, cyber, bio, and military domains.  Next, we filtered 13 cases that fully qualified, affirming that governments struggle to translate acknowledged incidents into effective government solutions.  From this review, we identified six stages of how governments convert warning shots into improved safety and security conditions for their citizens (these stages form our proposed “Governance Convergence Framework (GCF)”).  

To address convergence shortfalls, we recommend that the U.S. Congress establish an independent agency to track emergent AI warning shots, register incidents for government attention, and facilitate their rapid conversion through the GCF for appropriate resolution.  We also recommend that Congress designate an existing committee to have lead oversight responsibility for AI warning shots and government regulation/resolution.  Lastly, we recommend that one or several civil society organizations (AI safety labs, non-profits, AI safety associations, etc.) establish an external AI warning shot reporting and advocacy initiative to hold the U.S. government accountable for resolving emerging AI risks.