Terence Tao

Yeah.

So we're going to have a paper with 50 authors and a big appendix of who contributed what.

The beauty of these lean projects is that automatically you get all this data.

So like everything's uploaded to this GitHub and GitHub tracks who contributed what.

So you could generate statistics at any later point in time.

You could say, oh, this person contributed this many lines of code or whatever.

I mean, these are very crude metrics.

I would definitely not want this to become part of your 10-year review or something.

But I mean, I think already in enterprise computing, people do use some of these metrics frequently.

as part of the assessment of performance of an employee.

Again, this is a direction which is a bit scary for academics to go down.

We don't like metrics so much.

Yeah, I think it's interesting to study.

I mean, I think you can do studies of whether these are better predictors.

There's this problem called Goodhart's law.

If a statistic is actually used to incentivize performance, it becomes gamed, and then it is no longer a useful measure.

Oh, humans, always gamed.

Yeah, I know.

I mean, it's rational.

So what we've done for this project is self-report.