Earlier quoted context omitted.
"Ethics" does not really encompass the topic. The topic was that a net trained mostly on white people's faces upsamples a downsampled photo of a half-black man (Barack Obama) into a generic white face. LeCun's point is this is no surprise. If you trained it on leopards, it would upsample pixelated human faces into leopard faces instead. LeCun is an expert on how these nets work.
And nowhere did Timnit disagree that the cause he identified was a cause of bias in the system. Her contention is that there are others, and reducing the problem to just "get better datatsets" is a bad idea (and a way for researchers to abdicate responsibility). To use an example that comes up: do we solve the ethical qualms of a system that predicts incarceration rate based on facial structure by getting a better da…
A: Training data is a cause of this bias
B: But not the only cause
A: True
vs. A: Training data is a cause of this bias
B: I am so sick of this. You are not permitted to speak.
A: I am deleting my Twitter account.