Artificial intelligence is propped up by undervalued human labor: tips for doing well and doing good with applicable mathematics

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• Prof. Kay Kirkpatrick
• Wednesday 21 February 2024, 16:00-17:30
• MR5, CMS, Wilberforce Road, Cambridge, CB3 0WB.

If you have a question about this talk, please contact Sae Koyama.

On the surface, AI and machine learning have made a lot of progress recently, both theory and practice. But much of this progress is illusory, because it’s based on work done by underpaid humans, such as the popular AI paradigm Reinforcement Learning from Human Feedback, RLHF . Calculations can show, extrapolating from a current AI system supported by a number of human workers, that a future “human-level” AI would need to be supported by thousands of times that number of humans. Moreover, a lot of this AI/ML progress is harmful to humans, directly (Tesla crashes, surveillance) or indirectly (releasing gobs of carbon, driving up energy prices). For instance, data centers produce more greenhouse gases than airlines do; and training GPT -3 once releases as much carbon as driving a car for 112 years. We can steer the applications of mathematics in better directions, such as by responsible consumption of electronics and software, and relatedly, by protecting vulnerable workers. We can also spread awareness of these crucial issues and less visible issues, such as big tech’s capture of academia and undue influences on peer review. I’ll share some tips and stories about how things look when they go wrong and how we can do better.

This will be a hybrid talk. We will meet in the CMS , in MR5 . However, Prof. Kirkpatrick will be delivering the talk remotely, via Google Meet, and you are also welcome to join remotely instead: https://meet.google.com/jei-yrgd-iha

This talk is part of the C.U. Ethics in Mathematics Society (CUEiMS) series.

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• C.U. Ethics in Mathematics Society (CUEiMS)
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• MR5, CMS, Wilberforce Road, Cambridge, CB3 0WB
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