Dr. Ang Li, an Assistant Professor in the Computer Science Department, and his research lab have recently published their work in the prestigious Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24). AAAI is recognized as one of the top conferences in the field of artificial intelligence. Their research paper, titled “Probabilities of Causation with Nonbinary Treatment and Effect,” co-authored with Judea Pearl, a Turing Award recipient and Dr. Li’s Ph.D. advisor, marks a significant contribution.

The paper advances the theoretical fundamentals of counterfactual analysis, focusing on the bounding of probabilities of causation such as the probability of necessity and sufficiency (PNS), the probability of sufficiency (PS), and the probability of necessity (PN), all of which find applications in health science, business, and personalized decision-making. Theoretical advancements in this area had not been updated since the early 2000s, focusing only on the simpler binary cases of PNS, PS, and PN, without further developments for about 20 years. Dr. Li was able to define all probabilities of causation without any restrictions and bounded them using consistent rules in counterfactual analysis and Fréchet inequalities. This work not only enables counterfactual analysis in real-world applications but also paves the way for further theoretical discoveries.

The paper was presented at the AAAI 2024 conference in Vancouver, Canada, in February and is set to be published by the AAAI Press in the conference proceedings.