[yummyfajitas]

Go read the description of the statistical analysis or just view their R notebook:

https://github.com/propublica/compas-analysis/blob/master/Co...

Their own analysis shows that (p ~= 0) that high and medium risk factors are predictive. They also showed that the racial bias terms (race_factorAfrican-American:score_factorHigh, etc) are probably not predictive (p > 0.05).

Your quotes are not evidence of bias, though I see how they might confuse an innumerate reader. It's interesting how good a job this article is doing confusing the innumerate - it's almost as if it was written to mislead without technically lying.

For example, black defendants being pegged as being more likely to commit crimes can be caused by one of two things: bias or perhaps black defends actually are more likely to commit crimes. According to ProPublica's own analysis (see race_factorAfrican-American), the latter is actually the case. This is true with p = 4.52e-06 - see line [36].

[daveguy]

I read through the entire analysis. It appears that you stopped reading after you saw a p-value that supported your bias. That is bias in the sense of pre-conceived notion. You then proceeded to pedantically argue that the well demonstrated bias of the algorithm (more false positives for blacks than whites about 40% vs 20%) does not exist because of a p-value that came in between 0.05 to 0.1 instead of below 0.05.

Please let me know when your reading comprehension catches up with your mediocre statistics comprehension.

Maybe you just didn't realize that the 20-20 hindsight data -- prediction vs recidivism -- is included right there in the analysis. Or maybe you did realize it later and just decided you'd dug in so much that you didn't want to admit your ignorance.

Or maybe you still haven't comprehended the difference between the meanings of the word bias.