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Ваша оценкаA jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them.
Today’s "machine-learning" systems, trained by data, are so effective that we’ve invited them to see and hear for us?and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potenti...
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