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.

Schank（1980）为《情报》撰写了一篇社论，内容为“人工智能中有多少情报？”。在本文中，我们将重新讨论这个问题。我们从对现代AI的简短概述开始，并展示自Schank发表论文以来的40年中AI的一些突破。接下来，我们将介绍这些AI突破所基于的主要技术，例如深度学习和强化学习；两种根植于心理学的技术。接下来，我们讨论人工智能在心理上似乎是合理的，并且随着人工智能学习能力的现代突破而变得可能成为现实。然后，我们进入一个主要的问题，即人工智能系统实际上是如何实现的。例如，是否有可以解决人类智能测试的AI系统？我们得出结论，尚克的观察，到目前为止，智能是关于泛化的，而人工智能并不是特别擅长于此，它经受住了时间的考验。最后，我们考虑AI洞察力对于研究智力个体差异可能意味着什么。我们将继续探讨AI如何进一步促进情报研究，反之亦然，并期待着未来的卓有成效的互动。