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.)