Research Project Overview and Description
This project develops a unified philosophical theory of AI agency by integrating philosophy, statistics, and law to analyze generative models and legal liability. It aims to define agency within distributed systems through a series of academic publications and industry-focused events addressing the ethical and legal foundations of artificial agents.
This project, titled “AI Agency: Foundations, Ethics, and Liability,” seeks to construct a unified philosophical theory of AI agency that bridges the disciplines of philosophy, statistics, and law. It specifically explores the agency of AI systems driven by generative models from both fundamental and applied perspectives. By avoiding mistaken technical assumptions about generative AI, the research tackles several pressing questions: whether the novelty of generative AI is social or technical, how to define agency within fundamentally distributed systems, and the applicability of legal fictions—such as corporate personhood—to artificial agents. The methodology combines philosophical inquiry with statistical modeling, legal analysis, and potential empirical testing involving human-AI interactions.
Research Outcome
The primary academic deliverables are five to six research papers targeted at top-tier, peer-reviewed journals in philosophy and law. Planned publications include “All Learning is Generative” for a philosophy of science journal (Q3 2025), alongside papers exploring the distributed nature of AI (Q3 2025), AI personhood and liability (Q1 2026), and issues of consciousness, hallucination, and deception (Q2–Q4 2026). To generate impact beyond academia, the team plans to pitch a management-focused article to the Harvard Business Review and potentially publish a distilled piece in Nature Machine Intelligence by Q2 2026. Furthermore, an industry event focusing on AI agency and business strategy is planned for Q3–Q4 2026.
About the researcher
Professor Boris Babic is an HKU-100 Associate Professor at the University of Hong Kong, jointly appointed in the Musketeers Foundation Institute of Data Science, the Department of Philosophy, and the Faculty of Law. He holds a JD from Harvard Law School, along with an MS in Statistics and a PhD in Philosophy from the University of Michigan. His research focuses on the ethics, law, and policy of artificial intelligence and machine learning, as well as Bayesian statistics and decision theory. Prior to joining HKU, he held faculty positions at the University of Toronto and INSEAD, and completed a postdoctoral fellowship at the California Institute of Technology.
Fund Source
Staff Seed Fund (pending)
For enquiries
please contact at atlabhku.hk