An Alternative View on AI: Collaborative Learning, Incentives, and Social Welfare - Lecture 2

Explore the second lecture in a three-part series on an alternative perspective of artificial intelligence, delivered by Michael I. Jordan from the University of California, Berkeley. Delve into topics such as collaborative learning, incentives, social welfare, and dynamics in AI systems. Examine how this approach challenges the traditional paradigm of intelligence residing in a single, autonomous agent and instead proposes a framework where intelligence is distributed across a system of active, cooperative agents. Gain insights into the integration of economics with computing and data sciences, and understand the potential impact of this broader conceptual foundation on real-world AI systems. Learn from a distinguished speaker who has been recognized as one of the most influential computer scientists worldwide and has received numerous prestigious awards for his contributions to the field.