I think you're right that this algorithm doesn't do a good job of reconstructing high res faces from pixelated ones, simply because it can't—there simply isn't

I think you're right that this algorithm doesn't do a good job of reconstructing high res faces from pixelated ones, simply because it can't—there simply isn't enough information in the input, and there is a huge set of real people (from many races) that could map to a given pixelated image. But I do think that when someone who is white (or another race) says "here's a cool thing, check it out" and someone who is black (or another race, different from the first) tries it and realizes it doesn't work for them because of their race, there is a bit of inadvertent racism there. There is an inadvertent exclusion of that second person. I think this happens a lot and in some cases is unavoidable (e.g. language is intertwined with race, and there is a vast amount of information—literature, news, art—that will be inaccessible to you depending on which language(s) you speak), but it is a problem, and it deserves fixing when possible. The implications in this case are currently small—it's a demo. But there is a risk that these biases could make it into real systems and have real impact on people's lives, and to combat that we need more awareness of this effect in the ML community and more research into possible solutions.