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Biology transcends the limits of computation

Perry Marshall

Progress in Biophysics and Molecular Biology May 4, 2021 DOI: 10.1016/j.pbiomolbio.2021.04.006 (opens in new tab)

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Characteristics Theoretical or philosophical paper Peer reviewed
Citations 27
Key points Argues that the prevailing reductionist causal sequence in biology (chemicals → code → cognition) is inaccurate, and proposes instead that cognition → code → chemicals is the correct order. Contends that biological cognition is volitional and relies on inductive logic, and that information cannot be fully explained by known physical principles.

Abstract

Cognition-sensing and responding to the environment-is the unifying principle behind the genetic code, origin of life, evolution, consciousness, artificial intelligence, and cancer. However, the conventional model of biology seems to mistake cause and effect. According to the reductionist view, the causal chain in biology is chemicals → code → cognition. Despite this prevailing view, there are no examples in the literature to show that the laws of physics and chemistry can produce codes, or that codes produce cognition. Chemicals are just the physical layer of any information system. In contrast, although examples of cognition generating codes and codes controlling chemicals are ubiquitous in biology and technology, cognition remains a mystery. Thus, the central question in biology is: What is the nature and origin of cognition? In order to elucidate this pivotal question, we must cultivate a deeper understanding of information flows. Through this lens, we see that biological cognition is volitional (i.e., deliberate, intentional, or knowing), and while technology is constrained by deductive logic, living things make choices and generate novel information using inductive logic. Information has been called "the hard problem of life' and cannot be fully explained by known physical principles (Walker et al., 2017). The present paper uses information theory (the mathematical foundation of our digital age) and Turing machines (computers) to highlight inaccuracies in prevailing reductionist models of biology, and proposes that the correct causation sequence is cognition → code → chemicals.

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