The Mathematician's Bias - and the Return to Embodied Computation

TL;DR

This paper explores the limitations of classical computation models, emphasizing the importance of embodied computation and suggesting that Turing's ideas remain relevant amidst ongoing debates about the nature of computation.

Contribution

It highlights the role of embodiment in computation and argues that Turing's conception of computation aligns with practical experiences, challenging traditional abstract models.

Findings

Embodiment is crucial to understanding computation.

Classical models face limitations in practical contexts.

Turing's ideas are validated by embodied computation perspectives.

Abstract

There are growing uncertainties surrounding the classical model of computation established by G\"odel, Church, Kleene, Turing and others in the 1930s onwards. The mismatch between the Turing machine conception, and the experiences of those more practically engaged in computing, has parallels with the wider one between science and those working creatively or intuitively out in the 'real' world. The scientific outlook is more flexible and basic than some understand or want to admit. The science is subject to limitations which threaten careers. We look at embodiment and disembodiment of computation as the key to the mismatch, and find Turing had the right idea all along - amongst a productive confusion of ideas about computation in the real and the abstract worlds.