Group Selection as a Safeguard Against AI Substitution
Qiankun Zhong, Thomas F. Eisenmann, Julian Garcia, Iyad Rahwan

TL;DR
This paper investigates how different AI usage strategies impact cultural diversity and evolution, revealing that AI substitution can lead to cultural collapse, but complement strategies may preserve diversity through group selection.
Contribution
It introduces an agent-based and evolutionary game theory model comparing AI as a substitute versus a complement, highlighting their long-term cultural effects.
Findings
AI-substitute users dominate under individual selection
AI-complement users support cultural diversity at group level
Group boundaries influence the success of AI use strategies
Abstract
Reliance on generative AI can reduce cultural variance and diversity, especially in creative work. This reduction in variance has already led to problems in model performance, including model collapse and hallucination. In this paper, we examine the long-term consequences of AI use for human cultural evolution and the conditions under which widespread AI use may lead to "cultural collapse", a process in which reliance on AI-generated content reduces human variation and innovation and slows cumulative cultural evolution. Using an agent-based model and evolutionary game theory, we compare two types of AI use: complement and substitute. AI-complement users seek suggestions and guidance while remaining the main producers of the final output, whereas AI-substitute users provide minimal input, and rely on AI to produce most of the output. We then study how these use strategies compete and…
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Taxonomy
TopicsLanguage and cultural evolution · AI in Service Interactions · Evolutionary Game Theory and Cooperation
