A Cooperative Path to Artificial Intelligence
Our efforts to make machines smart are very different from how we go about helping make people smart. It’s time to embrace a cooperative approach to building intelligent systems in which machines learn from their environments guided by the people who are trying to help them. By leveraging human knowledge, machines can solve problems that would be mathematically intractable otherwise, leading to practical systems that are responsive to the needs and preferences of the people they are working to help.
Michael L. Littman is a Computer Science Professor at Brown University, studying machine learning and decision making under uncertainty. He is co-director of Brown’s Humanity Centered Robotics Initiative, a Fellow of the Association for the Advancement of Artificial Intelligence, and has earned multiple awards for his teaching and research. An enthusiastic performer, Michael has had roles in numerous community theater productions and a TV commercial.