Ep. 176: Michael Schrage on How Recommendation Engines Create Value
- By Bilal Hafeez
- 1 min read
Michael is a research fellow with the MIT Sloan School of Management’s Initiative on the Digital Economy. His research focuses on the behavioural economics of models, prototypes, and metrics as for managing innovation risk and opportunity. He is author of the award-winning book The Innovator’s Hypothesis and most recently Recommendation Engines. In this podcast we discuss:
- Interaction of tech and capital
- The architecture choice
- Time on board of Match.com
- Recommendations and how you see yourself
- Self-indulgence vs self-improvement in choices
- How to assess recommendations
- History of recommendation engines
- Impact of LLMs and ChatGPT
- Choice not optimisation
- Netflix, Amazon and Spotify
- Search for truth/search for value
- Importance of experimenting
- Books mentioned: Thinking, Fast and Slow (Kahnemann), read sci-fi!
You can find Michael’s latest book here
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(The commentary contained in the above article does not constitute an offer or a solicitation, or a recommendation to implement or liquidate an investment or to carry out any other transaction. It should not be used as a basis for any investment decision or other decision. Any investment decision should be based on appropriate professional advice specific to your needs.)