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The irony is that I think the author may have meant granularity, not precision. You could have the highest precision model (not the AI type) of any given topic or domain and not only be totally inaccurate, but being categorically flawed, i.e., you’re not even shooting at the right target. From his statement it seems what he is really saying though is that it is the granularity of data is insufficient for an AI model to accurately or precisely evaluate a problem and then presumably solve it, assuming there is, let alone a human-acceptable solution. As I mentioned, you can have the most precisely modeled problem in the world and it won’t make a difference if it’s not accurate, especially since there is a very uncomfortable reality starting to face us, at least in the West, that all the little lies we were told and we perpetuated because we have been trained on them from birth, across generations now, are simply wrong and have polluted our minds to such a degree that many people could never accept if AI told them they’re wrong and everything they believe they know and have known all their life is wrong. On top of that, it shatters people’s narcissistic self-image of having been the good guy, because accepting what AI tells them is actually the truth means accepting that they were abusive to those who were right all along, meaning they are actually the bad guy. And if we definitely know anything as good guys, it’s that the majority is always right, because that is what we were taught is the democratic way. The majority is always right and you always have to trust the minority that are experts unless it’s a majority of experts, then you have to trust them too, especially if they are beholden to the minority ruling class! Right? Right! |