Just kidding. Recht might be even more suspicious of these things than we are. What has statistics ever done for us, really? When was the last time YOU ran a clinical trial after all, huh? HUH? After Ben Chugg defends his life decision to do a PhD in statistics, we talk AI, cults, philosophy, Paul Meehl, and discuss Ben Recht's forthcoming book, The Irrational Decision.

Check out Ben's blog, website, and his story about machine learning.

We discuss

• Ben Recht's theory of blogging
• Why is Berkeley the epicenter of AI doom?
  
• Where the word "robot" came from
• Is Bayesian reasoning responsible for AI doom?
• Paul Meehl and his contributions to science
• Ben Recht's bureaucratic theory of statistics
• What on earth is null hypothesis testing?
• What is the point of statistics?
• "Sweet spots" and "small worlds"
• Does science proceed by Popperian means?
• Can Popper get around the Duhem-Quine problem?
  

Errata

The z-score for the Pfizer trial was 20, not 12!

References

• Argmin, Ben Recht's blog
• David Freedman, UC Berkeley
• Paul Meehl's online course
• Theoretical Risks and Tabular Asterisks: Sir Karl, Sir Ronald, and the Slow Progress of Soft Psychology, Paul Meehl's 1978 paper.
• Clinical versus statistical prediction: A theoretical analysis and a review of the evidence, by Meehl
• On the near impossibility of estimating the returns to advertising
• A Bureaucratic Theory of Statistics by Recht
• The new riddle of induction by Goodman
• Announcing the Irrational Decision
• Patterns, Predictions, and Actions, textbook by Ben Recht and Moritz Hardt

Socials

• Follow us on Twitter at @BeenWrekt, @IncrementsPod, @BennyChugg, @VadenMasrani
• Come join our discord server! DM us on twitter or send us an email to get a supersecret link
• Become a patreon subscriber here. Or give us one-time cash donations to help cover our lack of cash donations here.
• Click dem like buttons on youtube

What's Berkeley's next cult? Send your guess over to incrementspodcast@gmail.com

Special Guest: Ben Recht.

Support Increments

Follow David on Twitter (@DavidDeutschOxf) or find his website here.

We discuss

• Whether belief is a fruitful lens through which to analyze ideas
• Whether a non-quantitative form of belief can be defended
• How does belief bottom out epistemologically?
• Whether statistics and probability are useful
• Where should statistics and probability be used in practice?
• The Popper-Miller theorem
• Statements vs propositions and their relevance for truth
• Whether Popper and Deutsch disagree about truth

References

• The Popper-Miller theorem. See the original paper
• David's 2021 talk on the correspondence theory of truth
• David's talk on physics without probability.
• Hempel's paradox
• The Beginning of Infinity
• Knowledge and the Body-Mind Problem

Socials

• Follow us on Twitter at @IncrementsPod, @BennyChugg, @VadenMasrani, @DavidDeutschOxf
• Come join our discord server! DM us on twitter or send us an email to get a supersecret link
• Believe in us and get exclusive bonus content by becoming a patreon subscriber here. Or give us one-time cash donations to help cover our lack of cash donations here.
• Click dem like buttons on youtube

What's the truth about your belief on the probability of useful statistics? Tell us over at incrementspodcast@gmail.com.

Special Guest: David Deutsch.

Support Increments

You can find Nick's podcast on institutional design here, and his substack here.

We discuss:

• The lack of feedback loops in longtermism
• Whether quantifying your beliefs is helpful
• Objective versus subjective knowledge
• The difference between prediction and explanation
• The difference between Bayesian epistemology and Bayesian statistics
• Statistical modelling and when statistics is useful

Links

• Philosophy and the practice of Bayesian statistics by Andrew Gelman and Cosma Shalizi
• EA forum post showing all forecasts beyond a year out are uncalibrated.

• Vaclav smil quote where he predicts a pandemic by 2021:

  The following realities indicate the imminence of the risk. The typical frequency of influenza pan- demics was once every 50–60 years between 1700 and 1889 (the longest known gap was 52 years, between the pandemics of 1729–1733 and 1781–1782) and only once every 10–40 years since 1889. The recurrence interval, calculated simply as the mean time elapsed between the last six known pandemics, is about 28 years, with the extremes of 6 and 53 years. Adding the mean and the highest interval to 1968 gives a span between 1996 and 2021. We are, probabilistically speaking, very much inside a high-risk zone.

  - Global Catastropes and Trends, p.46

• Reference for Tetlock's superforecasters failing to predict the pandemic. "On February 20th, Tetlock’s superforecasters predicted only a 3% chance that there would be 200,000+ coronavirus cases a month later (there were)."

Contact us

• Follow us on Twitter at @IncrementsPod, @BennyChugg, @VadenMasrani
• Check us out on youtube at https://www.youtube.com/channel/UC_4wZzQyoW4s4ZuE4FY9DQQ
• Come join our discord server! DM us on twitter or send us an email to get a supersecret link

Errata

• At the beginning of the episode Vaden says he hasn't been interviewed on another podcast before. He forgot his appearence on The Declaration Podcast in 2019, which will be appearing as a bonus episode on our feed in the coming weeks.

Sick of hearing us talk about this subject? Understandable! Send topic suggestions over to incrementspodcast@gmail.com.

Photo credit: James O’Brien for Quanta Magazine

Support Increments