Everyone always goes for the discrimination angle, but what frightens me is that like other modern automated tech of this decade the facial recognition used here probably has a horrendous false positive rate which most institutions will none the less treat as the final truth. Unrelated this is also why I fear most of this new AI stuff so much despite working in the field; the accuracy rates on these things in product…
The false positive rate on quality facial recognition is actually very low. I'm not weighing in whether or not it is proper to always use it, just as someone that's deeply experienced in commercial applications of facial recognition.
It depends on the purpose. For identity verification purposes, when you already have independent reason to suspect that someone is specifically Person X, then a "very low" false positive rate is likely sufficient.
For filtering, however, "very low" isn't enough. Suppose your facial recognition system has a 0.001% false positive rate (one per 100k), but you have a list of 1000 banned faces and your venue sees 10,000 visitors per night. You're making ten million comparisons, and that "very low" false positive rate will still result in 100 false matches.
That could still be okay, if a match just involves (here) pulling the patron aside for an ID verification. Asking 100 people for ID is much more benign than turning 100 people away at the turnstile. MSG here did appear to follow the match with a secondary verification (per the article), but I shudder to think of all the venues that will hear "very low false positive rate" and not really think through the consequences.