{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"What can AI teach us about the mind?","description":"Everyone is talking about AI these days. Often these conversations are about how AI might upend education, or work, or social life, or maybe civilization itself. But among cognitive scientists and psychologists the conversation inevitably drifts toward other questions. What does this latest generation of AI tell us about the human mind? Is it putting old ideas and theories to rest? Is it ushering in new ones? Will AI\u2014in other words\u2014also upend cognitive science? My guests today are Dr. Mike Frank and Dr. Gary Lupyan. Mike is a Professor of Psychology at Stanford University, where his lab focuses on language learning and cognition in children. Gary is a Professor of Psychology at the University of Wisconsin\u2013Madison, where his lab studies language and its role in augmenting human cognition. Both Gary and Mike have more recently been thinking a lot about AI and how it is challenging and deepening our understanding of the human mind.   In this conversation, we talk about being interested in AI as cognitive scientists\u2014while also being concerned about the technology as people. We discuss the linguistic abilities of frontier LLMs compared to the linguistic abilities of adult humans. We talk about a glaring "data gap" here\u2014the fact that, even though LLMs often rival human abilities, they require orders of magnitude more data to do so. We contrast the capabilities of large language models with so-called BabyLMs. We consider the fact that, as LLMs master language, they also master other abilities\u2014capacities for mathematical reasoning, causal understanding, possibly theory of mind, and more. And we talk about why language might be an especially potent form of input for an AI. Along the way, we touch on reference and the symbol grounding problem, the Platonic Representation Hypothesis, stimulus computability, confabulated citations, pattern matching and jabberwocky, the poverty of the stimulus argument, congenital blindness, Quine's topiary, the limits of in principle demonstrations, the WEIRD problem, and what the astonishing sophistication of disembodied AIs might suggest about the role of bodily experience in human cognition. Before we get to it, one small request: we\u2019re currently running a short survey of our listeners. You can find the link in our show notes. If you have a few minutes, we'd really love your input!  Alright friends, here's my conversation with Mike Frank and Gary Lupyan. I think you'll enjoy it!   Notes 5:00 \u2013 For more discussion of \u201cstochastic parrots\u201d and other ways of framing AI systems, see our recent episode with Melanie Mitchell. For the \u201coctopus test,\u201d see here. 8:00 \u2013 \u201cBabyLMs\u201d are\u2014in contrast to large LMs (aka LLMs)\u2014models that are trained on a more human-scale amount of linguistic input. For more on the BabyLM community, see here. 12:00 \u2013 For broad discussion of the use of AIs as \u201ccognitive models,\u201d see this paper by Dr. Frank and a colleague. The same paper discusses the idea of \u201cstimulus computability.\u201d  18:00 \u2013 For Dr. Frank\u2019s \u201cbaby steps\u201d paper, see here. 20:00 \u2013 For more on how Claude understands line breaks, see Anthropic\u2019s analysis of the issue here.  23:00 \u2013 For work on human-like grammaticality judgments in LLMs, see this paper by a team including Dr. Lupyan.  24:00 \u2013 See here for an influential paper on, among other things, how LLMs refute the idea that syntax is unlearnable. The article titled \u2018How linguistics learned to stop worrying and love the language models\u2019 is here; Dr. Lupyan\u2019s commentary\u2014\u2018Large language models have learned to use language\u2019\u2014here. 29:00 \u2013 For some of Dr. Lupyan\u2019s work on the \u201cabstractness\u201d of even concrete concepts, see here. 35:00 \u2013 For a classic paper on the so-called symbol grounding problem, see here.  37:00 \u2013 For the preprint putting forth the \u201cPlatonic Representation Hypothesis,\u201d see here. 40:30 \u2013 For more on the data gap between children and LLMs\u2014and what accounts for it\u2014see Dr. Frank\u2019s paper here. 45:00 \u2013 For a sampling of Dr. Frank and colleagues\u2019 work comparing language models to children, see here, here, and here. For more on the LEVANTE project, a collaborative effort spearheaded by Dr. Frank, see here. 48:00 \u2013 For the preprint\u2014"The Unreasonable Effectiveness of Pattern Matching," by Dr. Lupyan and a colleague\u2014see here. 55:00 \u2013 For more on Dr. Lupyan\u2019s perspective on the centrality of language in human cognition, see here. See also this more recent paper, considering the question in light of LLMs.  58:00 \u2013 For our earlier episode with Dr. Marina Bedny, see here. For the recent paper by Dr. Bedny and colleagues considering their research on congenital blindness in light of LLMs, see here. 1:01:00 \u2013 For classic work on language learning in blind children, see here. 1:02:00 \u2013 For a paper by Dr. Lupyan and colleagues on \u201chidden\u201d individual differences, see here. 1:03:00 \u2013 For more on \u201cmultiple realizability,\u201d see here. For our earlier episode with Dr. Eric Turkheimer, see here. 1:09:00 \u2013 For more on the work of Dr. Frank\u2019s collaborator, Dan Yamins, see here. 1:14:00 \u2013 See our earlier episode with Dr. M.J. Crockett for more discussion of the \u201cWEIRD problem\u201d around scientific uses of AI. In the same episode, we discussed how new scientific methods focus attention on questions that can be studied with those methods.    Recommendations A Mind at Play, by Jimmy Soni & Rob Goodman On Desire, by William Irvine Patterns, thinking, and cognition, by Howard Margolis Open Encyclopedia of Cognitive Science The BabyLM workshops\/community (e.g., the  entry on LLMs)   Many Minds is a project of the Diverse Intelligences Summer Institute, which is made possible by a generous grant from the John Templeton Foundation to Indiana University. The show is hosted and produced by Kensy Cooperrider, with help from Assistant Producer Urte Laukaityte and with creative support from DISI Directors Erica Cartmill and Jacob Foster. Our artwork is by Ben Oldroyd. Subscribe to Many Minds on Apple, Stitcher, Spotify, Pocket Casts, Google Play, or wherever you listen to podcasts. You can also now subscribe to the Many Minds newsletter here! We welcome your comments, questions, and suggestions. Feel free to email us at: manymindspodcast@gmail.com. For updates about the show, visit our website or follow us on Bluesky (@manymindspod.bsky.social). ","author_name":"Many Minds","author_url":"https:\/\/disi.org\/manyminds\/","html":"