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"A 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.
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Spare, epic, plot-driven and contemporary.
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On Open Library, 5 have read it and 37 want to.
Closest on the same fourteen dimensions, from everything scored on Taste Buds. Other media included when they land close.