Last week I read an article from the MIT Technology Review that looked into what causes people to make mistakes. The approach was one I hadn’t seen before: it used data mining on a set of chess games. Their rationale was that:
- There’s a huge database to feed your model from,
- Chess is a deterministic domain where you can objectively evaluate good and bad moves,
- There are clear criteria for the skill level of the participants, even when disparate, which allows you to balance.
As spoiled by the title, complexity was the main factor whenever a player made a mistake.
The bottom line is that the difficulty of the decision is the most important factor in determining whether a player makes a mistake.
So what’s the big deal?