Social behavior curves, equilibria, and radicalism

I. Here are some hypotheticals to consider, with a common theme. Note that in each case I'm asking what you would do, rather than what you should do. In the fall, COVID cases drop to 10% of their current level. You're back to working/studying in person. You're vaccinated, as is everyone else. Mask-wearing isn't required, … Continue reading Social behavior curves, equilibria, and radicalism

Grading my 2020 predictions

In December 2019, I made 132 probabilistic predictions for 2020. As promised, I've come back to evaluate them on three criteria: calibration, personal optimism/pessimism, and performance relative to PredictIt (and an anonymous friend who sent me their predictions for some of the events). I'll get to all of those, but first, here are my predictions, … Continue reading Grading my 2020 predictions

Predictions for 2021

Just as I did last year, I have some probabilistic predictions for 2021. In January 2022 I will return to grade them, just as in a week or two I'll grade my 2020 predictions. This year the predictions fall into four categories: U.S. politics (#1-17 below), COVID (#18-39), Miscellaneous (#40-53), and Personal (#54-100). Note that … Continue reading Predictions for 2021

Alike minds think great

I. It is famously the case that almost everyone thinks they're above average. Derek Sivers writes: Ninety-four percent of professors say they are better-than-average teachers.Ninety percent of students think they are more intelligent than the average student.Ninety-three percent of drivers say they are safer-than-average drivers. Interesting. Intuitively this seems to suggest that people are prone … Continue reading Alike minds think great

An elegant proof of Laplace’s rule of succession

Suppose I give you a bag of marbles and tell you that all the marbles are either green or black. You repeatedly reach in, pick out a random marble, and then put it back. You find that out of 100 draws, 70 of the marbles you took out of the bag were green. What's the probability that the next marble you'll draw will be green? Or, to put it another way, what's your best guess (expected value) of the fraction of marbles in the bag that are green?

Your vote matters — probably more than you think

(This post is meant to persuade you to vote. If you already want to vote but don't have a concrete voting plan, check out this post.) In 10th grade civics class I learned about two moral arguments in favor of voting in elections. The first of these appeals to a notion of civic duty: as … Continue reading Your vote matters — probably more than you think

Scoring rules part 3: Incentivizing precision

[This is Part 3 of a three-part series on scoring rules. If you aren’t familiar with scoring rules, you should read Part 1 before reading this post. You don't need to read Part 2, but I think it's pretty cool.] In 9th grade I learned the difference between accuracy and precision from a classroom poster. … Continue reading Scoring rules part 3: Incentivizing precision

Scoring rules part 2: Calibration does not imply classification

[This is Part 2 of a three-part series on scoring rules. If you aren't familiar with scoring rules (and Brier's quadratic scoring rule in particular), you should read Part 1 before reading this post. If you'd like, you can skip straight to Part 3.] One of the most important skills of good probabilistic forecasting is … Continue reading Scoring rules part 2: Calibration does not imply classification

Scoring rules part 1: Eliciting truthful predictions

Yesterday I submitted for publication a paper I've been working on for a long time. The paper was on scoring rules, which I think are really interesting. In this three-part series, I'll tell you a bit about scoring rules and hopefully convey why I find them so cool. In this post I'll define scoring rules … Continue reading Scoring rules part 1: Eliciting truthful predictions