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The example the parent poster described is "doctors are 66% male", which could very well be true.

My point is that neither "insects are unpleasant" nor "plants are pleasant" nor "doctors are 66% male" are immutable features of the universe. They are merely snapshots of the human view of world conditions, as the world is now. "True now", but not "true forever and always".

The paper seems to advocate for designing ML systems that learn that what is "true now" may not be "true forever and always". It seems to be quite the opposite of "there are certain truths that ML systems should not learn."

If your standard for truth is "immutable feature of the universe" then you might as well give up now because we don't know about any of those, or indeed if any exist at all.

Setting such a standard for a machine is ridiculous if all you want is a new tool to get some work done.

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