Alison Gopnik - The Evolution of Human Intelligences

This is really interesting. See Empowerment Gain as Causal Learning, Causal Learning as Empowerment Gain: A bridge between Bayesian causal hypothesis testing and reinforcement learning.

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It explains what’s going on here:

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And Chris Fields has some ideas about where these sorts of behaviours came from, physiologically:

13:10 On the psychological arrow of time, see Carlo Rovelli Trying to Explain the Thermal Time Hypothesis to A General Audience.

41:23 on Geometric Phase, which is the idea that "We experience the actions of a high-dimensional environment on a low-dimensional boundary, so there has to be a many-one mapping from paths in the environment to paths on the boundary."

1:19:22 Great question about the dinosaurs and paleoscopy!

David Mermin's 2018 paper is Making better sense of quantum mechanics:

We still lack any consensus about what one is actually talking about as one uses quantum mechanics. There is a gap between the abstract terms in which the theory is couched and the phenomena the theory enables each of us to account for so well. Because it has no practical consequences for how we each use quantum mechanics to deal with physical problems, this cognitive dissonance has managed to coexist with the quantum theory from the very beginning. The absence of conceptual clarity for almost a century suggests that the problem might lie in some implicit misconceptions about the nature of scientific explanation that are deeply held by virtually all physicists, but are rarely explicitly acknowledged. I describe here such unvoiced but widely shared assumptions.

The paper by Dominic Horsman, Susan Stepney, Rob C Wagner and Viv Kendon is When does a physical system compute? the abstract on that web page is hilarious!

Computing is a high-level process of a physical system. Recent interest in non-standard computing systems, including quantum and biological computers, has brought this physical basis of computing to the forefront. There has been, however, no consensus on how to tell if a given physical system is acting as a computer or not; leading to confusion over novel computational devices, and even claims that every physical event is a computation. In this paper, we introduce a formal framework that can be used to determine whether a physical system is performing a computation. We demonstrate how the abstract computational level interacts with the physical device level, in comparison with the use of mathematical models in experimental science. This powerful formulation allows a precise description of experiments, technology, computation and simulation, giving our central conclusion: physical computing is the use of a … [sic!]

Maybe they were hoping an AI would fill that in?

The paper by Kauffman et al is The Reasonable Ineffectiveness of Mathematics in the Biological Sciences by Seymour Garte, Perry Marshall and Stuart Kauffman.

The known laws of nature in the physical sciences are well expressed in the language of mathematics, a fact that caused Eugene Wigner to wonder at the “unreasonable effectiveness” of mathematical concepts to explain physical phenomena. The biological sciences, in contrast, have resisted the formulation of precise mathematical laws that model the complexity of the living world. The limits of mathematics in biology are discussed as stemming from the impossibility of constructing a deterministic “Laplacian” model and the failure of set theory to capture the creative nature of evolutionary processes in the biosphere. Indeed, biology transcends the limits of computation. This leads to a necessity of finding new formalisms to describe biological reality, with or without strictly mathematical approaches. In the former case, mathematical expressions that do not demand numerical equivalence (equations) provide useful information without exact predictions. Examples of approximations without equal signs are given. The ineffectiveness of mathematics in biology is an invitation to expand the limits of science and to see that the creativity of nature transcends mathematical formalism.

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Tomas Petricek did a talk on the book Where Mathematics Comes From: