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Seven: Prof Tetlock on why accurate forecasting matters for everything, and how you can do it better

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Manage episode 290955897 series 2917741
Contenido proporcionado por Rob Wiblin, Keiran Harris and 80,000 Hours and The 80000 Hours team. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Rob Wiblin, Keiran Harris and 80,000 Hours and The 80000 Hours team o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

Have you ever been infuriated by a doctor's unwillingness to give you an honest, probabilistic estimate about what to expect? Or a lawyer who won't tell you the chances you'll win your case?

Their behaviour is so frustrating because accurately predicting the future is central to every action we take. If we can't assess the likelihood of different outcomes we're in a complete bind, whether the decision concerns war and peace, work and study, or Black Mirror and RuPaul's Drag Race.

Which is why the research of Professor Philip Tetlock is relevant for all of us each and every day.

In this conversation from 2019, we discuss how his work can be applied to your personal life to answer high-stakes questions, like how likely you are to thrive in a given career path, or whether your business idea will be a billion-dollar unicorn — or fall apart catastrophically.

Full transcript, related links, and summary of this interview

This episode first broadcast on the regular 80,000 Hours Podcast feed on June 28, 2019. Some related episodes include:

• #7 – Julia Galef on making humanity more rational, what EA does wrong, and why Twitter isn’t all bad
• #11 – Dr Spencer Greenberg on speeding up social science 10-fold & why plenty of startups cause harm.
• #15 – Prof Tetlock on how chimps beat Berkeley undergrads and when it’s wise to defer to the wise
• #30 – Dr Eva Vivalt on how little social science findings generalize from one study to another
• #40 – Katja Grace on forecasting future technology & how much we should trust expert predictions.
• #48 – Brian Christian on better living through the wisdom of computer science
• #78 – Danny Hernandez on forecasting and measuring some of the most important drivers of AI progress

Series produced by Keiran Harris.

  continue reading

12 episodios

Artwork
iconCompartir
 
Manage episode 290955897 series 2917741
Contenido proporcionado por Rob Wiblin, Keiran Harris and 80,000 Hours and The 80000 Hours team. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Rob Wiblin, Keiran Harris and 80,000 Hours and The 80000 Hours team o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

Have you ever been infuriated by a doctor's unwillingness to give you an honest, probabilistic estimate about what to expect? Or a lawyer who won't tell you the chances you'll win your case?

Their behaviour is so frustrating because accurately predicting the future is central to every action we take. If we can't assess the likelihood of different outcomes we're in a complete bind, whether the decision concerns war and peace, work and study, or Black Mirror and RuPaul's Drag Race.

Which is why the research of Professor Philip Tetlock is relevant for all of us each and every day.

In this conversation from 2019, we discuss how his work can be applied to your personal life to answer high-stakes questions, like how likely you are to thrive in a given career path, or whether your business idea will be a billion-dollar unicorn — or fall apart catastrophically.

Full transcript, related links, and summary of this interview

This episode first broadcast on the regular 80,000 Hours Podcast feed on June 28, 2019. Some related episodes include:

• #7 – Julia Galef on making humanity more rational, what EA does wrong, and why Twitter isn’t all bad
• #11 – Dr Spencer Greenberg on speeding up social science 10-fold & why plenty of startups cause harm.
• #15 – Prof Tetlock on how chimps beat Berkeley undergrads and when it’s wise to defer to the wise
• #30 – Dr Eva Vivalt on how little social science findings generalize from one study to another
• #40 – Katja Grace on forecasting future technology & how much we should trust expert predictions.
• #48 – Brian Christian on better living through the wisdom of computer science
• #78 – Danny Hernandez on forecasting and measuring some of the most important drivers of AI progress

Series produced by Keiran Harris.

  continue reading

12 episodios

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