We published a paper on this a few years ago! Short answer: algorithms exhibit different accuracies on different races, genders, and ages.

B. F. Klare, M. J. Burge, J. C. Klontz, R. W. Vorder Bruegge and A. K. Jain, "Face Recognition Performance: Role of Demographic Information," in IEEE Transactions on Information Forensics and Security, vol. 7, no. 6, pp. 1789-1801, Dec. 2012.

http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA556941

Computers certainly can be racist when it comes to visual recognition tasks. Different races do look different, after all. For example, there have been several cases of face tracking software failing to detect black people.

In the case I think you're referencing, they were detected, just not as people.

It's a bit of a cop-out just to say, "shucks, computers do the darnedest things!" Humans coded, tested, and deployed that service. They let something fall through the cracks, the awful implications of which detract quite a bit from all the good the service might ever accomplish.

There are a bunch of different examples out there, just search for "face detection black people." In one example, Google Photos tagged a pair of unfortunate folks as gorillas. In another, HP had some webcams that tracked faces but couldn't track black people. Kinect had a similar problem. Nikon had a "did someone blink?" message that produced a lot of false positives with Asian people.

My point isn't to excuse it, and indeed I'm not even trying to address the moral dimensions of it. My point is just that if this is a Chinese product developed for use in China, it's entirely possible that it won't work well on non-Asian faces without additional work.

Sorry, you're right. I must have been aggressively misunderstanding in this case.

That's alright. I didn't know about the gorilla case until I went looking for it there, so that's something I learned.

Don't worry, anyone not looking Asian enough is automatically suspicious.

Someone has to program them.