Import AI 440: Red queen AI; AI regulating AI; o-ring automation
The 'automatability trigger' concept offers a novel regulatory design pattern — conditioning AI rules on the existence of automated compliance tools — that could inform Australian AI governance design.
Key points
- Sakana AI research shows LLM-based agents evolving adversarially outperform static approaches - with cybersecurity implications.
- Researchers propose 'automatability triggers': regulations that only activate once automated AI compliance tools exist.
- Both items are research-stage; no immediate APS action required, but the regulatory design concept is worth tracking.
Summary
This edition of Import AI covers two substantive AI research threads. First, Sakana AI's Digital Red Queen experiment demonstrates that LLM-based agents evolved adversarially against one another rapidly outperform human-designed competitors in a competitive programming environment, with implications for cybersecurity and AI-on-AI dynamics. Second, researchers from the Institute for Law and AI propose that AI regulations could be written with 'automatability triggers' - conditions that defer a regulation's entry into force until an automated compliance system capable of applying it exists. This concept, which the newsletter terms 'If Then Policy', could reduce compliance costs and make AI regulation more practically enforceable as capabilities improve.
Implications for Australian agencies
- Monitor Policy teams working on AI regulatory design may want to monitor the 'automatability trigger' concept as a potential approach to phased, capability-contingent AI compliance frameworks.
- Monitor Agencies with cybersecurity or national security AI responsibilities may want to watch adversarial AI evolution research for emerging threat modelling insights.
Implications are AI-generated. Starting points, not advice.
"Import AI 440: Red queen AI; AI regulating AI; o-ring automation" Source: Import AI – Substack (Jack Clark) Published: 12 January 2026 URL: https://importai.substack.com/p/import-ai-440-red-queen-ai-ai-regulating This edition of Import AI covers two substantive AI research threads. First, Sakana AI's Digital Red Queen experiment demonstrates that LLM-based agents evolved adversarially against one another rapidly outperform human-designed competitors in a competitive programming environment, with implications for cybersecurity and AI-on-AI dynamics. Second, researchers from the Institute for Law and AI propose that AI regulations could be written with 'automatability triggers' - conditions that defer a regulation's entry into force until an automated compliance system capable of applying it exists. This concept, which the newsletter terms 'If Then Policy', could reduce compliance costs and make AI regulation more practically enforceable as capabilities improve. Implications for Australian agencies: - [Monitor] Policy teams working on AI regulatory design may want to monitor the 'automatability trigger' concept as a potential approach to phased, capability-contingent AI compliance frameworks. - [Monitor] Agencies with cybersecurity or national security AI responsibilities may want to watch adversarial AI evolution research for emerging threat modelling insights. Retrieved from SIMS, 18 May 2026.