Mel Andrews is a philosopher of science who primarily focuses on machine learning and the role of mathematical and computational methods in scientific modelling. Mel is currently a predoctoral research associate at the Department of Machine Learning at Carnegie Mellon University and doing a PhD in philosophy of science at the University of Cincinnati. They are also a visiting scholar at the Australian National University and the University of Pittsburgh. In this episode, we discuss the philosophy of artificial intelligence and machine learning, AI ethics and safety, scientific and mathematical realism, the ontology of the free energy principle and critical theory's relationship to AI research.

You can find more of Andrews' work at https://mel-andrews.com/ and ⁠https://x.com/bayesianboy

Watch the video version ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

RSam Podcast #43

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{Reference Links}

⁠https://link.springer.com/article/10.1007/s10539-021-09807-0

https://www.researchgate.net/profile/Mel-Andrews

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If the ideas I discuss in this podcast evoke your interest, consider visiting ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://theunhappyman.substack.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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014 - Jason Haas