Expert Survey: AI Reliability & Security Research Priorities

Expert consensus identifies urgent gaps in AI safety research: The survey of 53 specialists across 105 research areas reveals that experts view reliability and security research as critical for safely developing AI systems with human-level capabilities, suggesting current safeguards may be insufficient as AI capabilities advance.

Data-driven priorities can guide investment decisions: This is the first study to quantitatively rank AI safety research areas by expert consensus on impact potential, providing companies and funders with evidence-based guidance on where to allocate resources for maximum safety benefit rather than relying on intuition alone.

Broad research landscape requires strategic focus: The identification of 105 distinct AI reliability and security research areas indicates the challenge is multifaceted—spanning technical, operational, and governance domains—meaning no single solution exists and coordinated investment across multiple research directions is necessary.

Prevention of severe harms is a key motivation: The survey explicitly frames reliability and security research as essential not just for improving AI performance, but specifically for "preventing severe harms," indicating expert concern about potential risks if these research areas are neglected during AI development.