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Join us for a special event speaker in our seminar series on Tuesday, November 18, hosted by the MIT Media Lab's Advancing Humans with AI (AHA) research program.
This hybrid event features Dr. Joseph Jay Williams, an Assistant Professor at the University of Toronto in Computer Science.
AI has the potential to help people change their beliefs and behavior so they can better achieve their goals. We incorporate AI into the interfaces billions of people use every day, so it intelligently intervenes—taking appropriate actions to help people change their beliefs and behavior. Our work spans education, mental health, physical health, and charitable donations. We design tools and methods for Intelligent Interventions by (1) designing better GenAI interfaces and teaching people to use them (e.g., improved versions of ChatGPT), and (2) using Reinforcement Learning for adaptive A/B experimentation that tests, enhances, and personalizes interventions. One example is transforming text messages into AI agents for encouraging exercise and providing education about anxiety and depression.
Our systems have accelerated (1) the generation of alternative intervention versions (e.g., text messages A vs. B vs. C) through human–GenAI co-design and crowdsourcing, and (2) the evaluation and deployment of enhanced and personalized interventions, by using Reinforcement Learning algorithms to conduct experiments that identify which message is best, and for whom. One intervention boosted student grades by 4% in 3 minutes. This framework won the $1M XPrize competition for the Future of Experimentation and a $3M NSF grant to make it available to practitioners and scientists. This will enable Intelligent Interventions that change a broad range of beliefs and behaviors to help people and society.
Joseph Jay Williams is an Assistant Professor at the University of Toronto in Computer Science, with courtesy appointments supervising PhD students in Statistical Sciences, Psychology, and the Vector Institute for Artificial Intelligence. He also has courtesy appointments in Economics, Industrial Engineering, and the Faculty of Information. He directs the Intelligent Adaptive Interventions Lab, which aims to transform any user interface into an intervention to help people change their behavior and learn by reimagining randomized A/B experiments as a tool for intelligent adaptation. His lab's work is represented in over 85 papers, 2 Best Paper Awards (including one at CHI), 4 Runner-Up/Honorable Mention awards for Best Paper (CHI, EDM, LAS), and 1st place in a $1M XPrize competition for the future of experimentation technology in education. He has received over $2M in grant funding, enabling interventions that have impacted over 500,000 people.
His PhD students span HCI (Human Computer Interaction), cognitive/social/clinical/health psychology, applied ML (reinforcement learning), applied AI (LLMs), and statistics. Joseph was previously an Assistant Professor in Information Systems & Analytics at the National University of Singapore, a Research Scientist at Harvard, a postdoc at Stanford, and completed his PhD at UC Berkeley. He is originally from Trinidad and Tobago.
An overview of his research program is at tiny.cc/williamsresearch; papers are at tiny.cc/williamspapers and tiny.cc/williamsjournalpapers; slides and recordings from past talks are at tiny.cc/williamstalk.