Daniel Kokotajlo

Daniel Kokotajlo is a researcher and forecaster recognized for his work on advanced artificial intelligence, long-term risk, and the dynamics of transformative technologies. Specializing in AI governance and strategy, Kokotajlo has developed analyses on how rapidly advancing AI systems could impact economies, institutions, and global security. His research is referenced in discussions about AI timelines, takeoff scenarios, and the strategic implications of highly capable machine learning systems.

Across research roles at organizations focused on AI and effective altruism, Kokotajlo has built quantitative models and decision frameworks to assist policymakers, philanthropists, and technical leaders in addressing high-stakes uncertainty. He has authored essays and technical memos exploring topics such as the potential speed of AI development, default alignment of powerful systems, and governance structures required to manage advanced capabilities. His work combines formal modeling with accessible explanations for a range of audiences.

Kokotajlo participates in online forums, working groups, and workshops dedicated to AI alignment and existential risk. He is known for presenting probability estimates and scenario analyses in formats understandable to non-specialist audiences, contributing to seminars, panel discussions, and policy briefings. Through his written and spoken contributions, Kokotajlo has influenced how practitioners and observers conceptualize the challenges and opportunities presented by frontier AI.

Kokotajlo has addressed the challenges of reasoning under deep uncertainty, including the potential for error in key assumptions. By revising his views in response to new evidence, he demonstrates the intellectual humility and skepticism necessary for responsible work on issues with limited data and significant consequences. This approach supports his credibility with technical experts and broader audiences interested in the future of artificial intelligence.