Do you have a source for this? This sounds like fine-tuning a model, which doesn’t prevent data from the original training set from influencing the output. The method you described would only work if the AI is trained from scratch on only images of iron man and cowboy hats. And I don’t think that’s how any of these models work.
Other than citing the entire training data set, how would this be possible?
Why do you need so much info on Mike? Can’t you just evaluate his statements/work on its own merit? The whole point of open source, federated platforms is that you don’t have to trust him. If he decides to enshittify it, you can just go with a fork or another instance. A nomadic identity isn’t a centralized alternative to the fediverse, it’s just a way of bringing some of the features of a centralized identity to a decentralized one (at least, that’s the way I interpreted the article).
Quotas are not the only way to combat discrimination, nor are they a good one. Name-blind hiring would resolve name discrimination without making additional presumptions about the applicant pool. A quota presumes that the applicant pool has a particular racial mix, and that a person’s qualifications and willingness to apply are independent of race. And even if those happen to be true, it can’t take into account the possibility that the random distribution of applicants just happens to sway one way or another in a particular instance.
Absolutely none of this law was ever about privacy or mental health. No one ever claimed it was. The law is banning tiktok because it is based in China. That is the reason given by the law itself. The possibility that meta or Google or some other American company will buy or replace tiktok and operate the same way is not an unintended outcome. It is literally the whole point of the law to get bytedance to sell tiktok to an American company.