Why AI Metaphors Matter

If you wanted a petri dish for understanding metaphors—how they emerge and evolve and jostle with each other—it 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's 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 – For an overview of Douglas Hofstadter's work on analogy, see here.

8:00 – Much of our discussion in this interview draws on Dr. Mitchell's piece on the metaphors for AI in Science magazine.

13:30 – For earlier discussions of anthropomorphism on the show, see our earlier episodes here and here.

16:00 – See here for the original discussion of LLMs as "stochastic parrots."

17:00 – See here for the original discussion of ChatGPT as a "blurry jpeg."

18:30 – See here for the original discussion of LLMs as role players.

22:00 – See here for one use of the "LLMs as crowds" metaphor. See also a discussion of this metaphor (and other metaphors for AI) here.

25:00 – For one discussion of AI as a "cultural technology" 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 – For the podcast series on intelligence that Dr. Mitchell co-hosted for the Santa Fe Institute, see here.

28:00 – See here for an influential formulation of the idea that AI is an "alien intelligence."

29:00 – For philosopher Shannon Vallor's book about AI as "mirror," see here.

31:00 – For the recent study on users' metaphors for AI systems, see here.

33:00 – For more on the rise of social AI, see our earlier episode here.

38:00 – For more on what AI researchers might learn from developmental and comparative psychologists, see Dr. Mitchell's recent post (summarizing her keynote at NeurIPs).

42:00 – 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 – For the study on humans' preference for AI-generated poetry, see here.

50:30 – For Brigitte Nerlich's documentation and discussion of various metaphors for AI (including AI's metaphors for itself), see here.

Recommendations

The AI Mirror, by Shannon Vallor

'Role play with large language models,' by Murray Shanahan (former guest!) et al.

'Large AI models are cultural and social technologies,' 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.

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