Regardless, my point still stands, they completely ignore (willingly or ignorantly) that human labeled data is not intrinsic to ML or even the algorithms themselves and in all likelihood is a small minority of datasets used by modern ML applications. To then apply that critique generally to ML shows ignorance and a misunderstanding of the ecosystem.
Gebru presented her doctoral research at the 2017 LDV Capital Vision Summit competition, where computer vision scientists present their work to members of industry and venture capitalists. Gebru won the competition, starting a series of collaborations with other entrepreneurs and investors.[11][12]
And to the fact that she got her PhD in computer vision, i.e. the main area of AI research that the article seems to be criticising.
Her PhD research is in computer vision and she and her co-authors are writing mainly about computer vision, but you spoke of "a lack of basic understanding and competence on the authors part". That is clearly incorrect and I don't understand what saying the same thing many times will change about that.