Here’s the link:

Learning from mistakes

Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University

We learn so much from mistakes! How can we structure our workflow so that we can learn from mistakes more effectively? I will discuss a bunch of examples where I have learned from mistakes, including data problems, coding mishaps, errors in mathematics, and conceptual errors in theory and applications. I will also discuss situations where researchers have avoided good learning opportunities. We can then try to use all these cases to develop some general understanding of how and when we learn from errors in the context of the fractal nature of scientific revolutions.

The video is here.

It’s sooooo frustrating when people get things wrong, the mistake is explained to them, and they still don’t make the correction or take the opportunity to learn from their mistakes.

To put it another way . . . when you find out you made a mistake, you learn three things:

1. Now: Your original statement was wrong.

2. Implications for the future: Beliefs and actions that flow from that original statement may be wrong. You should investigate your reasoning going forward and adjust to account for your error.

3. Implications for the past: Something in your existing workflow led to your error. You should trace your workflow, see how that happened, and alter your workflow accordingly.

In poker, they say to evaluate the strategy, not the play. In quality control, they say to evaluate the process, not the individual outcome. Similarly with workflow.

As we’ve discussed many many times in this space (for example, here), it makes me want to screeeeeeeeeeam when people forego this opportunity to learn. Why do people, sometimes very accomplished people, give up this opportunity? I’m speaking here of people who are trying their best, not hacks and self-promoters.

The simple answer for why even honest people will avoid admitting clear mistakes is that it’s embarrassing for them to admit error, they don’t want to lose face.

The longer answer, I’m afraid, is that at some level they recognize issues 1, 2, and 3 above, and they go to some effort to avoid confronting item 1 because they really really don’t want to face item 2 (their beliefs and actions might be affected, and they don’t want to hear that!) and item 3 (they might be going about everything all wrong, and they don’t want to hear that either!).

So, paradoxically, the very benefits of learning from error are scary enough to some people that they’ll deny or bury their own mistakes. Again, I’m speaking here of otherwise-sincere people, not of people who are willing to lie to protect their investment or make some political point or whatever.

In my talk, I’ll focus on my own mistakes, not those of others. My goal is for you in the audience to learn how to improve your own workflow so you can catch errors faster and learn more from them, in all three senses listed above.

P.S. Planning a talk can be good for my research workflow. I’ll get invited to speak somewhere, then I’ll write a title and abstract that seems like it should work for that audience, then the existence of this structure gives me a chance to think about what to say. For example, I’d never quite thought of the three ways of learning from error until writing this post, which in turn was motivated by the talk coming up. I like this framework. I’m not claiming it’s new—I guess it’s in Pólya somewhere—, just that it will help my workflow. Here’s another recent example of how the act of preparing an abstract helped me think about a topic of continuing interest to me.