In a celebrated passage of The Blind Watchmaker, Richard Dawkins writes: “It is raining instructions out there; it’s raining programs; it’s raining … algorithms. That is not a metaphor, it is the plain truth.”  This picture can be formalised through an algorithmic reworking of the infinite monkey theorem: replace monkeys at typewriters with monkeys at universal computers. The result is a clear: random mutation does not sample phenotypic space uniformly but instead generates an exponential bias toward simple outcomes describable by short algorithms. Evolution thus comes equipped with an intrinsic Occam’s razor. Simple descriptions are not merely elegant; they are vastly more likely to arise. This algorithmic bias helps explain several otherwise puzzling observations:

1. The prevalence of highly symmetric protein quaternary structures in the Protein Data Bank (symmetry admits far shorter descriptions than asymmetry) [1];
2. The strong developmental bias toward simple forms in computational biomorphs [2];
3. Repeated convergent evolution of simple functional RNA structures [3];
4. Phylogenetic data from angiosperms showing that transitions from complex to simple leaf shapes occur at much higher rates than the reverse [4].

Together, these examples show how developmental bias toward simplicity can drive evolutionary outcomes, challenging traditional readings of Mayr’s ultimate–proximate distinction.

[1] Symmetry and simplicity spontaneously emerge from the algorithmic nature of evolution. Iain G Johnston et al, PNAS 119, e2113883119 (2022).

[2] Bias in the arrival of variation can dominate over natural selection in Richard Dawkins’ biomorphs. Nora S. Martin et al, PLOS Comp. Bio., 20, e1011893. (2024)

[3] RNA secondary structures are conserved but random. S. von der Dunk et al, BioRxiv:2025.08.18.670923

[4] Developmental bias explains the evolutionary trend towards simple leaf shapes. James S. Malone et al, BioRxiv:2025.08.17.670617

Ard Louis is a theoretical physicist with a broad interdisciplinary set of interests, including self-assembling DNA, theories of evolution, the dynamics of soft matter, machine learning and applications of algorithmic information theory. He happily collaborates with biologists, chemists, computer scientists, mathematicians, philosophers and theologians. After his first degree in physics from the University of Utrecht, he completed a PhD with Neil Ashcroft at Cornell. He was a Royal Society Research Fellow in Theoretical Chemistry at the University of Cambridge, before moving to the Rudolf Peierls Centre for Theoretical Physics at the University of Oxford.