{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"Seven metaphors for AI","description":"If you wanted a petri dish for understanding metaphors\u2014how they emerge and evolve and jostle with each other\u2014it would be hard to do better than the world of AI. We talk about AI systems variously as coaches or co-pilots, little genies or alien intelligences. Some researchers claim that AIs "grow," that they're entering their phase of "adolescence." Critics deride AI products as slop and dismiss LLMs as a kind of autocomplete on steroids. What's behind these different characterizations? Which ones are accurate and which are unfair? And are our metaphors mostly colorful rhetoric or do they matter? Are they shaping how we understand, adopt, and ultimately regulate these new technologies?   My guest today is Dr. Melanie Mitchell. Melanie is a computer scientist and Professor at the Santa Fe Institute. She is the author of the book, AI: A Guide for Thinking Humans, and she writes a Substack by the same name.  This episode is a bit of a companion to our recent episode with Steve Flusberg. In that episode, Steve and I attempted a kind of crash course on metaphor and the human mind. Here, Melanie and I sit down for more of an extended case study: how metaphors are guiding, galvanizing, and maybe deceiving us in the contested realm of AI discourse. We unpack seven of the most widely used metaphors in this space. We consider how these metaphors are shaping not only our everyday understandings of AI, but also law and policy. We also talk about the metaphor and analogy capabilities of AI itself. Can these systems reason abstractly in the way that humans can? Along the way, Melanie and I touch on: AI-generated poetry, anthropomorphism, the original sin of AI research, the myth of Narcissus, psychometric testing and its pitfalls, metaphors for AI that are a bit hard to spot, and the question of whether an AI has ever come up with a decent analogy for itself.  Longtime fans of the show will know that we've had Melanie on the show once before. We invited her back, not only because she's thought about metaphor and analogy in AI discourse for decades, but because she's a voice of calm insight in an area that\u2019s increasingly awash in hype and polemic. Longtime fans of the show may also note that we are now celebrating our 6th birthday at Many Minds. That's right, the show launched in February 2020. If you'd like to support us as we recognize this milestone, you can leave us a rating or a review, recommend us to a friend, or give us a shout out on social media. Your support is always appreciated.  Without further ado, on to my conversation with Dr. Melanie Mitchell. Enjoy!    Notes 3:30 \u2013 For an overview of Douglas Hofstadter\u2019s work on analogy, see here. 8:00 \u2013 Much of our discussion in this interview draws on Dr. Mitchell\u2019s piece on the metaphors for AI in Science magazine.  13:30 \u2013 For earlier discussions of anthropomorphism on the show, see our earlier episodes here and here.  16:00 \u2013 See here for the original discussion of LLMs as \u201cstochastic parrots.\u201d 17:00 \u2013  See here for the original discussion of ChatGPT as a \u201cblurry jpeg.\u201d 18:30 \u2013 See here for the original discussion of LLMs as role players. 22:00 \u2013 See here for one use of the \u201cLLMs as crowds\u201d metaphor. See also a discussion of this metaphor (and other metaphors for AI) here.   25:00 \u2013 For one discussion of AI as a \u201ccultural technology\u201d by Alison Gopnik and colleagues, see here. For a more recent discussion of the same metaphor by Henry Farrell, Alison Gopnik and others, see here. 27:00 \u2013 For the podcast series on intelligence that Dr. Mitchell co-hosted for the Santa Fe Institute, see here.  28:00 \u2013 See here for an influential formulation of the idea that AI is an \u201calien intelligence.\u201d  29:00 \u2013 For philosopher Shannon Vallor\u2019s book about AI as \u201cmirror,\u201d see here. 31:00 \u2013 For the recent study on users\u2019 metaphors for AI systems, see here.  33:00 \u2013 For more on the rise of social AI, see our earlier episode here.  38:00 \u2013 For more on what AI researchers might learn from developmental and comparative psychologists, see Dr. Mitchell\u2019s recent post (summarizing her keynote at NeurIPs).  42:00 \u2013 For more on the ARC (Abstraction and Reasoning Corpus) and the research that Dr. Mitchell and colleagues have been doing with it, see here and here. 48:30 \u2013 For the study on humans' preference for AI-generated poetry, see here. 50:30 \u2013 For Brigitte Nerlich\u2019s documentation and discussion of various metaphors for AI (including AI\u2019s metaphors for itself), see here.   Recommendations  The AI Mirror, by Shannon Vallor \u2018Role play with large language models,\u2019 by Murray Shanahan (former guest!) et al. \u2018Large AI models are cultural and social technologies,\u2019 by Henry Farrell et al.   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":"