An Alternative View on AI: Collaborative Learning, Incentives, Social Welfare, and Dynamics - Lecture 3

Explore an alternative perspective on artificial intelligence in this third lecture of the INFOSYS-ICTS Turing Lectures series, delivered by Michael I. Jordan from the University of California, Berkeley. Delve into the concept of collaborative learning, examining how intelligence can be distributed across entire systems rather than residing solely in individual agents. Investigate the role of incentives, social welfare, and dynamics in AI systems deployed in social contexts. Learn about the limitations of current centralized AI paradigms and discover a broader framing where agents actively participate and cooperate in learning-based systems. Gain insights into the intersection of economics, computing, and data sciences, and understand the potential for this alternative view to reshape our understanding of AI and its applications in real-world scenarios.