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11 August 2023 Global | US

Ep. 176: Michael Schrage on How Recommendation Engines Create Value

Bilal Hafeez

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

Make sure to subscribe to the show on Apple, Spotify, YouTube, or wherever you go for your podcasts. You can follow us on Twitter and LinkedIn.

(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.)

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