[pc86]

The data analysis you link to is by Jeff Larson, while the primary author of the article is Julia Angwin.

Larson is still the second author so it is certainly a big question how he can present data showing no statistical correlation between race and score then have his name on an article saying the exact opposite that is clearly pushing an agenda. And as noted, one where the owners of the publication are also involved in a competing risk assessment product.

[yummyfajitas]

It's not quite right that he shows no correlation between race and score. There is a strong correlation between race and score. This correlation is caused by the fact that blacks have a high recidivism rate (p = 4.52e-6).

What the analysis shows is that once you know the predicted score of the algorithm, using race doesn't give you extra information. If the scores were biased then you could correct them by using racial information to undo the bias.

For more detail on that last bit, read the "What if measurements are biased?" section of my blog post: https://www.chrisstucchio.com/blog/2016/alien_intelligences_...

(The details differ a bit - I describe linear regression rather than cox models. But the basic idea is the same.)