For us, technologists, yes, the distinction between "AI bias", and the bias in the data is clear. The point however, is when it comes to the general public, "AI" is the whole thing, and actually the public has absolutely no saying (perhaps even no knowledge) about the data; nevertheless, technocrats will argue that "data doesn't lie".
Edit: the auto correct had written "data doesn't like"
It's not just biased data, though, it's an objective function optimising a biased metric.
We've picked a metric, recidivism rate, that is believed to be inherently biased because cops arrest a lot of protected minorities. The model has correctly predicted that cops will arrest a lot of protected minorities. The general public has then turned around and shot the messenger rather than hold cops accountable for all that arresting they're doing.
Technologists shouldn’t try to dumb things down for the general public; we should try to state as clearly as possible where the problem lies and how it might be mitigated. In this case, we need to make it clear that what’s called “AI” is just a new kind of statistical tool, and like all statistical tools it’s only as good as the data it’s provided and the human interpreters of its outputs.
Ironically, I think “conservative” is both an excellent descriptor of function approximators—they tend to conserve whatever bias they’re provided with—and a terrible word to use for popular writing, since it’s so easily confused with political conservatism (even though e.g. no politically conservative “AI” would autosuggest “on my face” as a completion of “can you sit”).
Edit: the auto correct had written "data doesn't like"