Statistics provides tools for answering questions that are central to building trustworthy AI: What works? What fails? How certain are we? In this talk, I will discuss my path from studying statistics to conducting research as a data scientist and now working full time in AI safety. I will share examples of how statistical thinking can support this work, including deciding what to measure, uncovering failure modes, quantifying uncertainty, and connecting evidence to real decisions. I hope to show that many paths lead into this field and that statisticians and data scientists have important skills to bring to the challenge of building trustworthy AI.
Emily Hadley is a Quantitative Threat Forecasting Analyst at OpenAI, where she works to identify, understand, and forecast risks related to AI. Previously, she was a Security Researcher on the Microsoft AI Red Team and a Senior Research Data Scientist at RTI International. Emily holds... Read More →
