This is a link post.

In March I posted a very short description of my PhD thesis, Algorithmic Bayesian Epistemology, on LessWrong. I've now written a more in-depth summary for my blog, Unexpected Values. Here's the full post:

***

In January, I defended my PhD thesis. My thesis is called Algorithmic Bayesian Epistemology, and it's about predicting the future.

In many ways, the last five years of my life have been unpredictable. I did not predict that a novel bat virus would ravage the world, causing me to leave New York for a year. I did not predict that, within months of coming back, I would leave for another year — this time of my own free will, to figure out what I wanted to do after graduating. And I did not predict that I would rush to graduate in just seven semesters so I could go work [...]

---

Outline:

(03:48) Chapter 0: Preface

(04:17) Chapter 1: Introduction

(07:39) Chapter 2: Preliminaries

(09:33) Chapter 3: Incentivizing precise forecasts

(11:00) Chapter 4: Arbitrage-free contract functions

(14:10) \* Chapter 5: Quasi-arithmetic pooling

(21:11) Chapter 6: Learning weights for logarithmic pooling

(23:01) \* Chapter 7: Robust aggregation of substitutable signals

(30:01) Chapter 8: When does agreement imply accuracy?

(36:09) \* Chapter 9: Deductive circuit estimation

(46:34) Epilogue

The original text contained 6 footnotes which were omitted from this narration.

---

First published:
May 9th, 2024

Source:
https://www.lesswrong.com/posts/j6EhfL2hRubaKL9ca/my-thesis-algorithmic-bayesian-epistemology-explained-in

---

Narrated by TYPE III AUDIO.

“My thesis (Algorithmic Bayesian Epistemology) explained in more depth” by Eric Neyman

LessWrong (30+ Karma)