
埃里克·J. 拉森 (Erik J. Larson) 揭示了人工智能的实际科学基础与外界对其的夸张宣称之间有巨大差距。他指出,将人工智能(artificial intelligence)与人类智能(human intelligence)等同起来极其错误。AI 基于归纳推理,依靠处理数据集来预测结果。它缺乏演绎推理 (deductive)(从一般原则或前提中得出具体结论)和溯因推理 (abductive)(为一组观察结果形成最可能的解释)的能力,而这些推理能力对人类思维至关重要。人类不是通过关联数据集来思考,我们通过情景和经验做出推测,这种直觉式的推理目前我们根本不知道如何编程实现。拉森担忧我们正在同时犯下两个错误:一方面降低了对什么是人类智能的定义标准,另一方面高估了人工智能可能达到的能力。
Erik J. Larson exposes the vast gap between the actual science underlying AI and the dramatic claims being made for it. It is a profound mistake to equate artificial intelligence with human intelligence. AI works on inductive reasoning, crunching data sets to predict outcomes. It lacks the deductive (deriving specific conclusions from general principles or premises) and abductive (forming the most likely explanation for a set of observations) reasoning capabilities that are crucial for human thought. Humans don’t correlate data sets. We make conjectures, informed by context and experience. And we haven’t a clue how to program that kind of intuitive reasoning. Larson worries that we’re making two mistakes at once, defining human intelligence down while overestimating what AI is likely to achieve.
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