[4c2383f5c88e911]

The title is surprisingly not too clickbaity, although it's not as clear-cut: in order to reduce false positives (increase precision), they need to limit the number of positives (reduce recall). On 1000 samples containing 70 gay people, they were able to get a 10% false positive rate on their positive results, which were 10 people (meaning 12% of the total gay sample). The sample is a bit biased too because they pulled it from explicitly gay-oriented public social network pages (but I don't fault them for that, it would be quite hard to find a better sample).

It is still an impressive result, and one that might be misused badly, despite the numerous warnings used in the paper.

[BeniBoy]

This is the classic "false positive paradox"[1]. Commonly present in medical testing. Even if false positive rate is very low, if the positive value is very low too, the likelihood of being victim of false can be high.

The exemple in the wikipedia page are very good. I had to explain that to a friend which had tested positive on the HIV test and was waiting for confirmation over the weekend. Not easy to talk math when such things happens.. I found it very troubling that doctors don't even mention that to patient and present tests as 95% effective. (In fact she was fine)

[1]: https://en.wikipedia.org/wiki/False_positive_paradox