Re:AI researcher Timnit Gebru resigns from Google
by ska on Thursday December 03, 2020 @06:16PM
(#25296766)
At least in theory, something like:
Fair academic criticism: We shouldn't publish this paper because it has flaws X,Y,Z. (usually followed by an opportunity for the researchers to address X,Y,Z).
Unfair and/or non-academic criticisms: We shouldn't publish this paper because: I don't like the author/authors institution. I don't like this approach, approach X is better. I don't like the conclusions.
The last is potentially relevant here. And yes, clearly the quality and value of research is reduced by filtering based on results you want to promote. Which well may be in a companies best interest, but there are sometimes difficult lines to draw - when exactly do you move from "promoting the companies interests" to "propaganda intended to mislead the public"?
Re:AI researcher Timnit Gebru resigns from Google
by titanomachy on Thursday December 03, 2020 @06:41PM
(#25297040)
That makes sense, but I don't think of corporate approval committees as being designed to render "fair academic criticism". For example, they might say "the core thesis of this paper reveals our valuable trade secrets and therefore you are forbidden from publishing it externally." That's not fair academic criticism, but it could be a reasonable decision for the committee to make.
Re:AI researcher Timnit Gebru resigns from Google
by ska on Thursday December 03, 2020 @06:51PM
(#25297149)
Right, as I was trying to convey in the last - there are other corporate interests than research value, and I think all would agree there are situations where they reasonably trump the researchers or public's interest. And vice-versa; "This research shows we have been poisoning the public for 40 years" for most people probably really isn't the same as "This research exposes valuable trade secrets". The lines aren't always obvious.
If a company publishes only papers that clearly advance its interests, but the research is sound and independently reproducible, does that bias really lessen the perceived value and quality of the research?