Abstract
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.
In 1980 Roger C. Schank wrote an editorial for Intelligence entitled “How much intelligence is there in artificial intelligence (AI)?”. His first observation was the lack of any interaction between the fields of intelligence research and artificial intelligence research. Since then limited interactions have taken place. His second observation was that AI is relevant for intelligence research. This was based on the state of the art of research in both fields, at that time, when AI was still in its infancy. Given the breathtaking developments in modern AI, it is worthwhile to ask Schank’s question again. We contend that the question’s relevance has increased over time. Shank’s third observation was that real intelligence is all about generalization, which at that time was a weak point in AI, but perhaps not anymore.
