To figure out how to make progress on problems that require cognitive effort, it seems useful to think of times in the past when you’ve made lots of cognitive progress. For me, high school math camp was the most cognitively productive time.

It seems plausible that the main reason I was productive at math camp was because of the competitive atmosphere. In light of this, I want to experiment with systems that harness people’s competitiveness to drive learning and insight, since maybe this can increase productivity substantially. “Insight Hunt” is a way this could be done. 

I suspect the below idea is somewhat far from the ideal and that it could change a fair bit in response to user feedback. If anyone tries an Insight Hunt, please leave your feedback and results (including the name of the winner if you want increased motivation) in the comments! Also, feel free to suggest alternative games/systems which leverage competitiveness for cognitive productivity.

Lastly, I suspect that Insight Hunt works best when the stuff the players want to learn is more “shallow” i.e. knowledge/facts that require few inferential steps from what most people know to understand. This is because if one person wants to learn linear algebra (not shallow), and another person knows linear algebra, the game will devolve into a lecture (I suspect). Examples of shallow knowledge include alignment theory (given some pre-requisites, like basic ML; this is the primary use-case I'm excited about) and psych study results. Non-examples include theoretical physics and math.
 

Insight Hunt

• There are three players; one player is the “judge” and two are the “seekers”
• Who plays as the judge rotates such that everyone is the judge equally often
• Every round:
  • The seekers spend 8 minutes trying to find “insights” (i.e. true and useful sentences) that score highly according to the judge, who scores the insights based on how useful and interesting they found the sentence
    • Before the round, it’s in the judge’s interest (who wants to learn) to tell the seekers what kind of stuff they want to know, or e.g. what papers/posts/ideas they want summarized to them
      • Examples include “what is deep double descent?” or “what are the main reasons sleeping 8 hours might be important?” or “what’s John Wentworth’s main problem with ELK?”
    • Finding insights might look like quickly digesting a paper, DMing someone for a quick insight, or using an on-demand tutor service
  • The seekers each get 1 minute to explain each insight; after 1 minute is up, the judge awards anywhere from 1 to 10 points
    • Optional: scores are displayed on a scoreboard
    • Optional: a prize (e.g. $1000 or being announced as the winner publicly) is given to the person with the highest score in the end