This is a shorter post trying to put a few thoughts down. It is becoming imperative for us mathematicians (among many other people) to equip our students – and our colleagues – with frameworks and conceptual tools to navigate the emerging landscape in our profession.
Here are (a few) recent reads I have found very helpful.
Shorter reads
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What is mathematics now, and what should it be?, by Jeremy Avigad.
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Large AI models are cultural and social technologies, by Henry Farrell, Alison Gopnik, Cosma Shalizi, and James Evans.
Longer reads
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Mathematics in the age of AI (ok, not a read, more a “watch”), by Terence Tao, slides.
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AI as social technology, by Henry Farrell and Cosma Shalizi.
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AI, Human Cognition and Knowledge Collapse, by Daron Acemoglu, Dingweng Kong, and Asuman Ozdaglar.
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Artificial intelligence tools expand scientists’ impact but contract science’s focus, by Qianyue Hao, Fengli Xu, Yong Li and James Evans.
Blog posts
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Mathematics is not rational, really!, by Michael Harris.
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Reaping without sowing, by Tobias Osborne.
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The machines are fine. I’m worried about us, by Minas Karamanis.
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Machine god metaphors eat your brain, by Henry Farrell.
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Deep theorems were scarce and difficult and so became an effective mechanism to identify deep thought. AI has broken this system, by Bryna Kra (guest post in Terry Tao’s blog).