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  "text": "In this new paper, we make a strong point:\n\nHuman imitation is a misplaced goal for AI.\n\nToo much of AI development is based on human imitation, as exemplified by the Turing test: the more a machine resembles us, the more successful it is.\n\nBut there are two major problems.\n\nThe first is conceptual. Imitating human outputs does not tell us much about the capacities behind them:\n\nThe same answer can emerge from different processes. A plausible response does not tell us whether a system can reason reliably, generalize to unfamiliar situations, or recognize when it should say “I don’t know”. \n\nThe second is ethical. Why should we want AI that imitates humans?\n\nHumans are biased. Our attention is limited. Our judgment is fallible. Reproducing these limitations is hardly an ambitious vision for AI.\n\nEven worse:\n\nA system that impersonates a person can exploit human trust.\n\nAnd an industry focused on replicating humans can fall in the “Turing’s trap”: favour human replacement over augmentation. \n\nInstead, we argue that AI should aim to improve human welfare.\n\nTo this end, we propose three coordinated changes:\n\nFor developers: Build systems that strengthen human capabilities and independent judgment.\n\nFor funders: Require projects to assess benefits, costs, and who receives or bears them.\n\nFor institutions: Base procurement and renewal on demonstrated benefits.\n\nThe goal should be to help people know more, suffer less, and exercise greater control over their lives.\n\n*\n\nFull paper in the first reply.\n\nWith @GaryMarcus & @Walter4C",
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