If by "algorithms" we mean ML—and that's what we mean in 2019—ML is inherently and intrinsically bound with data, and it's increasingly formally (formally, as in mathematically) clear that problem of bias thus isn't solveable. https://arxiv.org/abs/1903.03862 andhttps://arxiv.org/abs/1609.05807
-
-
And let's not get even started with fair... Different definitions of fair are often in mathematical conflict (see the Kleinberg et. al paper). (And, crucially) we're not using math the way we use them to probe laws of nature.)
-
Indeed. More than that, regardless of how you define it, bias is ineradicable. The question is how do we deal with it?https://twitter.com/ShlomoArgamon/status/1109641898560577536 …
End of conversation
New conversation -
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.