The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) What are the Implications of Algorithmic Thinking? with Michael I. Jordan - #407
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Sep 7, 2020 In a fascinating discussion, Michael I. Jordan, a Distinguished Professor at UC Berkeley and a leader in AI and machine learning, shares insights from his diverse academic journey. He delves into how philosophy and cognitive sciences shaped his understanding of uncertainty in tech. The conversation touches on the valuation of data, empowering young artists through AI, and creating meaningful economic markets. Michael also emphasizes the need for equitable representation in AI development and the risks of unregulated algorithmic systems.
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Algorithmic Thinking and Economics
- Algorithmic thinking has created a new infrastructure connecting people, but economic value is missing.
- Integrating economic principles into these connections could transform industries and empower individuals.
United Masters Example
- United Masters helps musicians manage their careers by leveraging data and connecting them directly with fans.
- This model empowers artists and creates a healthier music market, demonstrating the potential of data-driven marketplaces.
Markets as a Force
- Markets are a fundamental force like gravity, not inherently good or bad.
- They introduce constraints and trade-offs, which can be leveraged to create more balanced and socially beneficial systems.