AI is becoming increasingly adept at identifying security vulnerabilities, capabilities that can be used for both attack and defense. Thickstun believes that if attackers and defenders have equally powerful AI, network systems will become safer because AI is cheaper and more scalable than human analysts.
However, the offense-defense balance presupposes that everyone has access to powerful AI. When responding to OpenAI's hack, HuggingFace used AI to analyze security logs but could not use OpenAI's model or other U.S. frontier models like Claude, because their public versions have guardrails limiting their use for cybersecurity analysis to prevent malicious actors from using them for hacking. HuggingFace had to rely on China's open-source model GLM 5.2 for security analysis.
Thickstun expresses concern about this and notes that the U.S. AI industry is adopting a centralized, authoritarian approach to AI governance, while China leads in open-source AI development. He questions: Do we want a regulatory environment where only OpenAI, the U.S. government, and trusted partners can use powerful AI? Is AI too dangerous to be widely distributed? How do we balance the risks of broad AI access against the risks of power concentration and centralized control?