Cultural Evolution as Distributed Computation

The speed and transformative power of human cultural evolution is evident from the change it has wrought on our planet. This chapter proposes a human computation program aimed at (1) distinguishing algorithmic from non-algorithmic components of cultural evolution, (2) computationally modeling the algorithmic components, and amassing human solutions to the non-algorithmic (generally, creative) components, and (3) combining them to develop human-machine hybrids with previously unforeseen computational power that can be used to solve real problems. Drawing on recent insights into the origins of evolutionary processes from biology and complexity theory, human minds are modeled as self-organizing, interacting, autopoietic networks that evolve through a Lamarckian (non-Darwinian) process of communal exchange. Existing computational models as well as directions for future research are discussed. Introduction The origin of life brought about unprecedented change to our planet; new forms emerged creating niches that paved the way for more complex forms, completely transforming the lands, skies, and oceans. But if biological evolution is effective at bringing about adaptive change, human cultural evolution is arguably even more effective, and faster. Cultural change doesn’t take generations; it works at the speed of thought, capitalizing on the strategic, intuitive creative abilities of the human mind. This chapter outlines current and potential future steps toward the development of a human computation program inspired by the speed and effectiveness of how culture evolves. The overarching goal of the kind of research program outlined in this chapter is to develop a scientific framework for cultural evolution by abstracting its algorithmic structure, use this algorithmic structure to develop human-machine hybrid structures with previously unforeseen computational power, and to apply it to solving real problems. The proposed approach can be thought of as a "repeatable method" or “design pattern” for fostering cultural emergence, defined by specific computational methods for modeling interactions at the conceptual level, the individual level, and the social level, and their application to the accumulation of adaptive, open-ended cultural