>This is the belief that A.I. codes are recipes for automating ethics itself; and that once a broad consensus around such codes has been achieved, the problem of determining an ethically positive future direction for computer code will have begun to be solved. I can think of literally nobody who believes this. I don't think anyone working in ethical AI would pretend that ethics can be "solved."
Not sure what the author meant there but we do have a problem of offloading the ethical burden of our systems onto the algorithms themselves and it should be taken more seriously. Like when Google shipped an AI for moderating hate speech which turned out to be biased against minorities [1]. Google would have been sued if that bias had been coded in procedurally, but because they used "AI" their response was basically…
> The results show evidence of systematic racial bias in all datasets, as classifiers trained on them tend to predict that tweets written in African-American English are abusive at substantially higher rates.
Wouldn't we need to know the true rate of abusive tweets by race in order to conclude this? Is this addressed at all, e.g. with human labelled data, or am I mistaken in thinking this is necessary?