Machine learning and the challenge of human values
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Machine learning and the challenge of human values
Brian Christian examines the gap between what people want machine-learning systems to do and what those systems actually do. The book frames that gap as the alignment problem, connecting the growing use of data-trained systems to make decisions and interpret the world with ethical and potentially existential risks. Its subject sits at the intersection of machine learning, human expectations, and the consequences of delegating decisions to automated systems.
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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 potentially existential risks emerge. Researchers call this the alignment problem.
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