AI-driven Cultural Evolution 

How will AI accelerate the evolution of human culture and innovation?

The ability of humans to create and disseminate culture is often credited as the single most important factor in our success as a species. Culture evolves as a function of the range of available traits (variation), the ways these traits can replicate (transmission), and the success they encounter (selection). Whenever there is a major transition in any of these three processes, cultural evolution is altered. For example, in the space of roughly 200 years (1300–1500), European culture was rocked by a succession of major transitions in variation, transmission, and selection. Through the tales of Marco Polo and other explorers, Europeans were exposed to a broad set of novel cultural traits, such as paper money and coal burning (variation); the invention of the printing press made it easy to replicate cultural traits with great fidelity (transmission); and the Black Death drastically changed the social and economic opportunities of commoners, reshuffling the value of cultural traits (selection). 

Modern communication technologies have scaled some of the key factors that shape human cultural evolution, enabling the instant sharing of knowledge across the globe, and the rapid self-organization of online communities of interest. We believe that a particular digital technology, Artificial Intelligence (AI), can substantially impact the process of cultural evolution, from recommender algorithms altering the flow of knowledge, to AI agents becoming participants in the generation of culture itself, from music and visual art to scientific discoveries. Our long-term goal is to map the different ways in which AI will impact—or may already be shaping—human culture, and establish a research agenda for behavioral scientists studying hybrid cultural evolution in the digital age.

 

Sample Projects

Which factors facilitate success in human-AI collective learning and problem solving?
Can AI agents generate ideas that are both original and coherent, not merely random combinations?
AlphaGo's famously "alien" move foregrounded a central puzzle for human–machine culture: can humans do more than briefly imitate machine innovations, and instead learn, transmit, and sustain strategies that originate outside the human cognitive repertoire?
Do LLMs actively reshape how humans speak?
How do reward structures influence collective accuracy in online news consumption?
 
How does the way we describe AI-generated art shape perceptions of AI systems and the allocation of credit and responsibility among human stakeholders?

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