Causal Bandits Podcast 49% Less Loss with Causal ML | Stefan Feuerriegel S2E1 | CausalBanditsPodcast.com
Jan 17, 2025
Stefan Feuerriegel, Head of the Institute of AI in Management at LMU, discusses the exciting world of causal machine learning. He shares insights from successful projects that improved semiconductor yields and enhanced healthcare outcomes through causal methods. Stefan emphasizes the importance of team diversity in problem-solving and the necessity of tailoring complex ideas for broader audiences. He also offers practical advice for decision-makers and highlights the transformative potential of collaboration in leveraging AI for better decision-making.
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NZZ Website Optimization
- Stefan Feuerriegel's team helped Neue Zürcher Zeitung optimize their website's front page using causal inference.
- This empowered editors to make better decisions, like promoting articles they initially hesitated to.
ABB Hitachi Yield Improvement
- At ABB Hitachi, causal machine learning reduced yield loss in semiconductor fabrication by almost 50%.
- This resulted in significant financial gains, though the exact amount remains undisclosed.
Explaining Causality to Managers
- Explain causal machine learning with relatable analogies like crystal balls.
- Managers want two crystal balls to compare decision outcomes, not just predict the future.