Tim Brunet

Constructive Neutral Evolution is an evolutionary mechanism that can explain much molecular inter-dependence and organismal complexity without assuming positive selection favoring such dependency or complexity, either directly or as a byproduct of adaptation. It differs from but complements other non-selective explanations for complexity, such as genetic drift and the Zero Force Evolutionary Law, by being ratchet-like in character. With CNE, purifying selection maintains dependencies or complexities that were neutrally evolved. Preliminary treatments use it to explain specific genetic and molecular structures or processes, such as retained gene duplications, the spliceosome, and RNA editing. Here we aim to expand the scope of such explanation beyond the molecular level, integrating CNE with Multi-Level Selection theory, and arguing that several popular higher-level selection scenarios are in fact instances of CNE. Suitably contextualized, CNE occurs at any level in the biological hierarchy at which natural selection as normally construed occurs. As examples, we focus on modularity in protein–protein interaction networks or “interactomes,” the origin of eukaryotic cells and the evolution of co-dependence in microbial communities—a variant of the “Black Queen Hypothesis” which we call the “Gray Queen Hypothesis”.

Recent debates about the biological and evolutionary conditions for sentience have generated a renewed interest in fine-grained functionalism. According to one such account advanced by Peter Godfrey-Smith, sentience depends on the fine-grained activities characteristic of living organisms. Specifically, the scale, context and stochasticity of these fine-grained activities. One implication of this view is that contemporary artificial intelligence is a poor candidate for sentience. Insofar as current AI lacks the ability to engage in such living activities it will lack sentience, no matter what its coarse-grained functions. In this paper, we review the case for fine-grained functionalism and show that there are contemporary machines that fulfil the fine-grained functional criteria identified by Godfrey-Smith, and thus are candidates for sentience. Molecular machines such as Brownian computers are analogous to metabolic activity in their scale, context and stochasticity, and can serve as the basis of AI. Molecular computation is a promising candidate for artificial sentience according to contemporary philosophical accounts of sentience.

Microbiologists are transitioning from the study and characterization of individual strains or species to the profiling of whole microbiomes and microbial ecology. Equipped with high-throughput methods for studying the taxonomic and functional characteristics of diverse samples, they are just beginning to encounter the conceptual, theoretical, and experimental problems of comparing taxonomy to function, and extracting useful measures from such comparisons. Although still unresolved, these problems are well studied in macro-ecology and are reiterated here as an historical precautionary for microbial ecologists. Beyond expected and unresolved terminological vagueness, we argue that assessments and comparisons of taxonomic and functional profiles in micro-ecology suffer from theoretically unresolvable arbitrariness and ambiguities. We divide these into problems of scale, individuation, and commensurability. We argue that there is no technically/theoretically “correct” scale, individuation, or comparison of taxonomy and function, but there are nonetheless better and worse methodologies for profiling.

We begin with the idea that lines of reasoning are continuous mental processes and develop a notion of continuity in proof. This requires abstracting the notion of a proof as a set of sentences ordered by provability. We can then distinguish between discrete steps of a proof and possibly continuous stages, defining indexing functions to pick these out. Proof stages can be associated with the application of continuously variable rules, connecting continuity in lines of reasoning with continuously variable reasons. Some examples of continuous proofs are provided. We conclude by presenting some fundamental facts about continuous proofs, analogous to continuous structural rules and composition. We take this to be a development on its own, as well as lending support to non-finitistic constructionism.

Constructive Neutral Evolution theory provides selectively neutral explanations of the origin and maintenance of biological complexity. This essay provides an analysis of CNE as an explanatory strategy defined by a tripartite set of conditions, and shows how this applies to cases of the evolution of complexity at higher-levels of the biological hierarchy. CNE was initially deployed to help explain a variety of complex molecular structures and processes, including spliceosomal splicing, trypansomal pan-editing, scrambled genes in ciliates, duplicate gene retention and fungal ATP synthetase structure. CNE has also been generalized to apply to phenomena at the cellular level, including protein-protein interaction network modularity, obligate microbial symbioses, eukaryogenesis and microbial unculturability. This essay further extends CNE to cases of complexity at levels of organization higher than the molecular and cellular. These are multicellular phenotypic complexity, multicellular ecological complexity and, some cases of cultural complexity.