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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.17741 |
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| _version_ | 1866916907323490304 |
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| author | Brinkmann, Levin Eisenmann, Thomas F. Nussberger, Anne-Marie Derex, Maxime Bonati, Sara Chirkov, Valerii Rahwan, Iyad |
| author_facet | Brinkmann, Levin Eisenmann, Thomas F. Nussberger, Anne-Marie Derex, Maxime Bonati, Sara Chirkov, Valerii Rahwan, Iyad |
| contents | 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 findings provide a framework for understanding how machines can persistently expand human cognitive skills and underscore the need to consider their broader implications for human cognition and cultural evolution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_17741 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Experimental Evidence for the Propagation and Preservation of Machine Discoveries in Human Populations Brinkmann, Levin Eisenmann, Thomas F. Nussberger, Anne-Marie Derex, Maxime Bonati, Sara Chirkov, Valerii Rahwan, Iyad Computers and Society 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 findings provide a framework for understanding how machines can persistently expand human cognitive skills and underscore the need to consider their broader implications for human cognition and cultural evolution. |
| title | Experimental Evidence for the Propagation and Preservation of Machine Discoveries in Human Populations |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2506.17741 |