Digital Foundations of Evolvable Genomic Intelligence and Human Proteanism

Le résumé fourni par la source

Despite prolific innovations and diversity in economic and biological systems, the theoretical impasse on novelty production has led to a longstanding reliance on randomness or statistical white noise error terms. Extant Decision Sciences and Game Theory, respectively, conflate rationality with an optimal choice from a prespecified action set and rule out Nash equilibria with strategic innovation or ‘surprises’. In contrast, the Wolfram-Chomsky schema implies that only digital software systems incorporating Gödel Incompleteness can produce novelty. Advances in gene science and neuroscience show how this relates to genomic intelligence which reaches its apogee in general-purpose highly protean human intelligence. Key developments with the Adaptive Immune System (AIS) and the Mirror Neuron System (MNS), latterly mostly in primate brains, involve distinctive Gödelian features for eukaryote intelligence of self-reference (Self-Ref) and offline virtual self-representation (Self-Rep) for complex self-other interaction with prodigious open-ended capacity for anticipative malware detection and novelty production within a unique self-referential blockchain distributed ledger. This initially developed in the AIS, which from the get-go accounts for somatic hypermutations for novel anti-body production and in humans as unbounded proteanism for novel extended phenotypes in the form of artifacts outside of ourselves. Thus, models of bounded rationality, extant Decision Sciences and Complexity Economics that overlook human proteanism for novelty production may have no basis in the evolution of human intelligence and complexity. Clearly, radical rethinking is needed to navigate the burgeoning digital world.

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