In December 2020, I made 100 probabilistic predictions for 2021. As promised, I’ve come back to evaluate them on two criteria: calibration and personal optimism/pessimism. I also challenged readers to compete with me. More on this later, but first, here are my predictions, color-coded black if they happened and red if they didn't. I. US … Continue reading Grading my 2021 predictions
Many in the rationalist sphere look down on tribalism and group identity. Paul Graham writes that identity interferes with people's ability to have a productive discussion. Julia Galef seconds this view (though with exceptions), devoting a chapter of Scout Mindset to the ways that identity interferes with clear thinking. Eliezer Yudkowsky makes a similar point … Continue reading Can group identity be a force for good?
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
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
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
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
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?
(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
This is a map of Nassau Street, the northern edge of Princeton University. It's a very standard sort of street; I imagine one quite like it exists in most college towns. It has lots of great places to eat, shown on the map in orange. During my senior year, because of Princeton's absurdly expensive meal … Continue reading An exploration of exploitation bias
[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