We make a guest appearance on Nick Anyos' podcast to talk about effective altruism, longtermism, and probability. Nick (very politely) pushes back on our anti-Bayesian credo, and we get deep into the weeds of probability and epistemology.
- 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
- 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)."
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- 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.
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