How much intelligence is there in artificial intelligence? A 2020 update

被引:18
|
作者
van der Maas, Han L. J. [1 ]
Snoek, Lukas [1 ]
Stevenson, Claire E. [1 ]
机构
[1] Univ Amsterdam, Amsterdam, Netherlands
关键词
Artificial Intelligence; Deep learning; Individual differences; Intelligence tests; Reinforcement; DEEP NEURAL-NETWORKS; REINFORCEMENT; MACHINE; MODELS; CHESS;
D O I
10.1016/j.intell.2021.101548
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Schank (1980) wrote an editorial for Intelligence on "How much intelligence is there in artificial intelligence?". In this paper, we revisit this question. We start with a short overview of modern AI and showcase some of the AI breakthroughs in the four decades since Schank's paper. We follow with a description of the main techniques these AI breakthroughs were based upon, such as deep learning and reinforcement learning; two techniques that have deep roots in psychology. Next, we discuss how psychologically plausible AI is and could become given the modern breakthroughs in AI's ability to learn. We then access the main question of how intelligent AI systems actually are. For example, are there AI systems that can solve human intelligence tests? We conclude that Shank's observation, that intelligence is all about generalization and that AI is not particularly good at this, has, so far, withstood the test of time. Finally, we consider what AI insights could mean for the study of individual differences in intelligence. We close with how AI can further Intelligence research and vice versa, and look forward to fruitful interactions in the future.
引用
收藏
页数:9
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