Enough of this false equivalence. You can call what I do "introducing my own biases". I am "biasing" NLP algorithms toward treating people equally whenever pos

Enough of this false equivalence. You can call what I do "introducing my own biases". I am "biasing" NLP algorithms toward treating people equally whenever possible, toward not discriminating based on their name or how they describe themselves. The default biases are really bad, and whatever my biases are, they're not as bad. I don't even know what you say I'm "cheating" at. That is a very weird accusation. You always make a choice of what algorithms and heuristics to deploy. Deploying a system like pre-trained word2vec or GloVe that believes everything it reads on the Web is a harmful choice. Not even waiting forever for strong AI will fix it. You wouldn't even let a child believe everything that they read, and a child has real intelligence. When you deploy harmful AI, you can't blame its effects on the code or the data, because the code and data have no moral agency. You wrote the code and it's your responsibility.