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Given the well‐known limitations of the Turing test, there is a need for objective tests to both focus attention on, and measure progress toward, the goals of AI. In this paper we argue that machine performance on standardized tests should be a key component of any new measure of AI, because attaining a high level of performance requires solving significant AI problems involving language understanding and world modeling — critical skills for any machine that lays claim to intelligence. In addition, standardized tests have all the basic requirements of a practical test: they are accessible, easily comprehensible, clearly measurable, and offer a graduated progression from simple tasks to those requiring deep understanding of the world. Here we propose this task as a challenge problem for the community, summarize our state‐of‐the‐art results on math and science tests, and provide supporting data sets ( www.allenai.org ).
Clark et al. (Tue,) studied this question.