Multilevel cultural evolution: From new theory to practical applications

David Sloan Wilson, Guru Madhavan, Michele J. Gelfand, Steven C. Hayes, Paul W. B. Atkins, and Rita R. Colwell

PNAS 120 (16) e2218222120

Evolutionary science has led to many practical applications of genetic evolution but few practical uses of cultural evolution. This is because the entire study of evolution was gene centric for most of the 20th century, relegating the study and application of human cultural change to other disciplines. The formal study of human cultural evolution began in the 1970s and has matured to the point of deriving practical applications. We provide an overview of these developments and examples for the topic areas of complex systems science and engineering, economics and business, mental health and well-being, and global change efforts.

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Multidisciplinary learning through collective performance favors decentralization

John Meluso and Laurent Hébert-Dufresne

PNAS 120 (34) e2303568120

Like chefs at a fast-moving restaurant or engineers in a multidisciplinary project, team members often complete separate, interrelated subsets of larger tasks with limited insight into the work of others. These contexts make it difficult for individuals to assess the value of their own contribution to the collective work. Our work shows that despite this obstacle, individuals can still learn from their neighbors when neighbors’ actions influence collective outcomes. Though the effects are modest, we found that teams with more interactions between members perform better when refining their work while teams with fewer interactions perform better when innovating. We also found that across 34 tasks with diverse qualities, teams that decentralize coordination responsibilities outperform those that do not.

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Self-similarity and the maximum entropy principle in the genetic code

Subhash Kak 

Theory in Biosciences volume 142, pages 205–210 (2023)

This paper addresses the relationship between information and structure of the genetic code. The code has two puzzling anomalies: First, when viewed as 64 sub-cubes of a 4×4×4 cube, the codons for serine (S) are not contiguous, and there are amino acid codons with zero redundancy, which goes counter to the objective of error correction. To make sense of this, the paper shows that the genetic code must be viewed not only on stereochemical, co-evolution, and error-correction considerations, but also on two additional factors of significance to natural systems, that of an information-theoretic dimensionality of the code data, and the principle of maximum entropy. One implication of non-integer dimensionality associated with data dimensions is self-similarity to different scales, and it is shown that the genetic code does satisfy this property, and it is further shown that the maximum entropy principle operates through the scrambling of the elements in the sense of maximum algorithmic information complexity, generated by an appropriate exponentiation mapping. It is shown that the new considerations and the use of maximum entropy transformation create new constraints that are likely the reasons for the non-uniform codon groups and codons with no redundancy.

Read the full article at: link.springer.com