Experimental Evidence for the Propagation and Preservation of Machine Discoveries in Human Populations
Levin Brinkmann, Thomas F. Eisenmann, Anne-Marie Nussberger, Maxime Derex, Sara Bonati, Valerii Chirkov, and Iyad Rahwan

TL;DR
This paper demonstrates that AI systems can influence human problem-solving and cultural evolution when their discoveries are non-trivial, learnable, and advantageous, leading to lasting cultural shifts.
Contribution
It identifies key conditions under which machine discoveries are transmitted and preserved in human populations, supported by experiments and simulations.
Findings
Machine-discovered strategies can be transmitted and understood by humans.
Under certain conditions, machine strategies lead to enduring cultural change.
AI can expand human cognitive skills through cultural influence.
Abstract
Intelligent machines with superhuman capabilities have the potential to uncover problem-solving strategies beyond human discovery. Emerging evidence from competitive gameplay, such as Go and chess, demonstrates that AI systems are evolving from mere tools to sources of cultural innovation adopted by humans. However, the conditions under which intelligent machines transition from tools to drivers of persistent cultural change remain unclear. We identify three key conditions for machines to fundamentally influence human problem-solving: the discovered strategies must be non-trivial, learnable, and offer a clear advantage. Using a cultural transmission experiment and an agent-based simulation, we demonstrate that when these conditions are met, machine-discovered strategies can be transmitted, understood, and preserved by human populations, leading to enduring cultural shifts. These…
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