How to Find Us: We are meeting at the old location again this week, in the upstairs wine bar at Westside Pavillion.

Discussion: The phrase "bias bias" could mean many things. Perhaps one might employ the term to point to the tendency to accuse others of bias before oneself. Perhaps, as in this paper, it could refer to the tendency of statisticians to be overly concerned with eliminating statistical bias and under-concerned about variance. What I want to discuss is the risk that, if we are observing other decision-makers from the outside with less knowledge about the situation than them, we will almost always find predictable irregularities in their decision-making which we cannot explain via our understanding of the situation. This will, I think, tend to be true whether they're "biased" in a significant sense or not. In other words: we're very likely to have less knowledge about the situation than the people making the decisions, and this is very likely to mislead us into thinking they're making biased decisions which are harming them, if we approach the question without sufficient awareness. This doesn't mean we can't assess bias, but it does sound a note of caution in doing so. Even in cases where the reasoning from our perspective seems very clear, the decision-maker may have other considerations to take into account.

Recommended Reading: I don't know of anything written specifically on this, but the recent breaking Chesterton’s fence in the presence of bull seems relevant here.

No prior exposure to Less Wrong is required; all are welcome.