Arnold Kling summarizes Robin’s argument:
If you have a cause, then other people probably disagree with you (if nothing else, they don’t think your cause is as important as you do). When other people disagree with you, they are usually more right than you think they are. So you could be wrong. Before you go and attach yourself to this cause, shouldn’t you try to reduce the chances that you are wrong? Ergo, shouldn’t you work on trying to overcome bias? Therefore, shouldn’t overcoming bias be your number one cause?
Here is Robin’s very similar statement. I believe these views are tautologically true and they simply boil down to saying that any complaint can be expressed as a concern about error of some kind or another. I cannot disagree with this view, for if I do, I am accusing Robin of being too biased toward eliminating bias, thus reaffirming that bias is in fact the real problem.
I find it more useful to draw an analogy with statistics. Biased estimators are one problem but not the only problem. There is also insufficient data, lazy researchers, inefficient estimators, and so on. Then I don’t see why we should be justified in holding a strong preference for overcoming bias, relative to other ends.
When I think of a blog that tries to eliminate or reduce bias, say by considering a wide variety of views and methods, I think of Dan Drezner or Matt Yglesias. I view Robin’s blog as exemplifying bias, and indeed showing that bias can be very useful, especially if embedded in a broader discovery process with checks and balances. (I would describe Robin’s blog as one of the dozen "must reads" out there.) Robin’s blog is one very select group of very smart people, pushing one unpopular, specialized, but very interesting and analytically powerful research method as far as it can go.
If I were allowed to retitle Robin’s blog (and I am not), I would call it "Reaping the Fruits of Bias."