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İçerik Economic Innovation Group tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan Economic Innovation Group veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.
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Hoop dreams of electric sheep

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Manage episode 393430300 series 2968992
İçerik Economic Innovation Group tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan Economic Innovation Group veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

Seth Stephens-Davidowitz has unusually written an unusual book.


The data analysis included in "Who Makes the NBA?: Data-Driven Answers to Basketball's Biggest Questions" normally would have taken Seth, a trained economist, multiple years of writing and running code. But because of new artificial intelligence tools, he finished the book in just thirty days. And he used AI tools not just for the coding, but also for the artwork, copy editing, and even to write the appendix.


He discusses with Cardiff the lessons he learned about using AI, and what such accelerated productivity might mean for the future of the labor market.


Then they discuss the actual findings in the book, an investigation into the backgrounds of the basketball players who make it to the NBA and succeed when they get there. How much of success is genetic? What accounts for the NBA's market failures—the traits of players who get paid too much and too little relative to their contributions? Why do some foreign countries have such astonishing success at sending players to the NBA? Does the choice of college really matter for future success?


The answers to these questions are surprisingly revealing about the experiences of non-basketball players, and about the relationships between luck, skill, parenting, undiscovered talent, the economy, and other familiar variables.


Related links:


Hosted on Acast. See acast.com/privacy for more information.

  continue reading

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Artwork

Hoop dreams of electric sheep

The New Bazaar

191 subscribers

published

iconPaylaş
 
Manage episode 393430300 series 2968992
İçerik Economic Innovation Group tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan Economic Innovation Group veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

Seth Stephens-Davidowitz has unusually written an unusual book.


The data analysis included in "Who Makes the NBA?: Data-Driven Answers to Basketball's Biggest Questions" normally would have taken Seth, a trained economist, multiple years of writing and running code. But because of new artificial intelligence tools, he finished the book in just thirty days. And he used AI tools not just for the coding, but also for the artwork, copy editing, and even to write the appendix.


He discusses with Cardiff the lessons he learned about using AI, and what such accelerated productivity might mean for the future of the labor market.


Then they discuss the actual findings in the book, an investigation into the backgrounds of the basketball players who make it to the NBA and succeed when they get there. How much of success is genetic? What accounts for the NBA's market failures—the traits of players who get paid too much and too little relative to their contributions? Why do some foreign countries have such astonishing success at sending players to the NBA? Does the choice of college really matter for future success?


The answers to these questions are surprisingly revealing about the experiences of non-basketball players, and about the relationships between luck, skill, parenting, undiscovered talent, the economy, and other familiar variables.


Related links:


Hosted on Acast. See acast.com/privacy for more information.

  continue reading

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