Meta-morphogenesis and the Creativity of Evolution

Whether the mechanisms proposed by Darwin and others suffice to explain all details of the achievements of biological evolution remains open. Variation in heritable features can occur spontaneously, and Darwinian natural selection can explain why some new variants survive longer than others. But that does not satisfy Darwin’s critics and also worries supporters who understand combinatorial search spaces. One problem is the difficulty of knowing exactly what needs to be explained: Most research has focused on evolution of physical form, and physical competences and behaviours, in part because those are observable features of organisms. What is much harder to observe is evolution of information-processing capabilities and supporting mechanisms (architectures, forms of representation, algorithms, etc.). Information-processing in organisms is mostly invisible, in part because it goes on inside the organism, and in part because it often has abstract forms whose physical manifestations do not enable us to identify the abstractions easily. Compare the difficulty of inferring thoughts, percepts or motives from brain measurements, or decompiling computer instruction traces. Moreover, we may not yet have the concepts required for looking at or thinking about the right things: we may need more than the vast expansion of our conceptual tools for thinking about information processing capabilities and mechanisms in the last half century. However, while continually learning what to look for, we can collaborate in attempting to identify the many important transitions in information processing capabilities, ontologies, forms of representation, mechanisms and architectures that have occurred on various time-scales in biological evolution, in individual development (epigenesis) and in social/cultural evolution – including processes that can modify later forms of evolution and development: metamorphogenesis. Conjecture: The cumulative effects of successive phases of meta-morphogenesis produce enormous diversity among living information processors, explaining how evolution came to be the most creative process on the planet. Progress in AI depends on understanding the products of this process.