# Machine Culture

arXiv: https://arxiv.org/abs/2311.11388 · HTML: https://mlsanity.com/paper/2311.11388/

## Key facts

- Cited by 55 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Nov 2023.

## Built on by (most cited first, 30 of 55)

- [Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia](https://mlsanity.com/paper/2312.03664/) (2023)
- [Emergent social conventions and collective bias in LLM populations](https://mlsanity.com/paper/2410.08948/) (2024)
- [Delving into LLM-assisted writing in biomedical publications through excess vocabulary](https://mlsanity.com/paper/2406.07016/) (2024)
- [Cultural Evolution of Cooperation among LLM Agents](https://mlsanity.com/paper/2412.10270/) (2024)
- [Towards AI-Native Software Engineering (SE 3.0): A Vision and a Challenge Roadmap](https://mlsanity.com/paper/2410.06107/) (2024)
- [Empirical evidence of Large Language Model's influence on human spoken communication](https://mlsanity.com/paper/2409.01754/) (2024)
- [How AI Ideas Affect the Creativity, Diversity, and Evolution of Human Ideas: Evidence From a Large, Dynamic Experiment](https://mlsanity.com/paper/2401.13481/) (2024)
- [How malicious AI swarms can threaten democracy: The fusion of agentic AI and LLMs marks a new frontier in information warfare](https://mlsanity.com/paper/2506.06299/) (2025)
- [When LLMs Play the Telephone Game: Cultural Attractors as Conceptual Tools to Evaluate LLMs in Multi-turn Settings](https://mlsanity.com/paper/2407.04503/) (2024)
- [Group size effects and collective misalignment in LLM multi-agent systems](https://mlsanity.com/paper/2510.22422/) (2025)
- [LLM-based multi-agent poetry generation in non-cooperative environments](https://mlsanity.com/paper/2409.03659/) (2024)
- [Tracking the perspectives of interacting language models](https://mlsanity.com/paper/2406.11938/) (2024)
- [Cultural evolution in populations of Large Language Models](https://mlsanity.com/paper/2403.08882/) (2024)
- [Collective Innovation in Groups of Large Language Models](https://mlsanity.com/paper/2407.05377/) (2024)
- [Shaping Shared Languages: Human and Large Language Models' Inductive Biases in Emergent Communication](https://mlsanity.com/paper/2503.04395/) (2025)
- [From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models](https://mlsanity.com/paper/2407.09502/) (2024)
- [What fifty-one years of Linguistics and Artificial Intelligence research tell us about their correlation: A scientometric analysis](https://mlsanity.com/paper/2411.19858/) (2024)
- [Computational Hermeneutics: Evaluating generative AI as a cultural technology](https://mlsanity.com/paper/2604.16403/) (2026)
- [Antagonistic AI](https://mlsanity.com/paper/2402.07350/) (2024)
- [Using LLMs to Advance the Cognitive Science of Collectives](https://mlsanity.com/paper/2506.00052/) (2025)
- [AI Agent Behavioral Science](https://mlsanity.com/paper/2506.06366/) (2025)
- [AI shares emotion with humans across languages and cultures](https://mlsanity.com/paper/2506.13978/) (2025)
- [Battling Botpoop using GenAI for Higher Education: A Study of a Retrieval Augmented Generation Chatbots Impact on Learning](https://mlsanity.com/paper/2406.07796/) (2024)
- [Expertise elevates AI usage: experimental evidence comparing laypeople and professional artists](https://mlsanity.com/paper/2501.12374/) (2025)
- [Recognising, Anticipating, and Mitigating LLM Pollution of Online Behavioural Research](https://mlsanity.com/paper/2508.01390/) (2025)
- [Performative Debias with Fair-exposure Optimization Driven by Strategic Agents in Recommender Systems](https://mlsanity.com/paper/2406.17475/) (2024)
- [Social Learning through Interactions with Other Agents: A Survey](https://mlsanity.com/paper/2407.21713/) (2024)
- [Markovian Generation Chains in Large Language Models](https://mlsanity.com/paper/2603.11228/) (2026)
- [Exploring the Topology and Memory of Consensus: How LLM Agents Agree, Fragment, or Settle When Forming Conventions](https://mlsanity.com/paper/2606.04197/) (2026)
- [Revisiting Rogers' Paradox in the Context of Human-AI Interaction](https://mlsanity.com/paper/2501.10476/) (2025)

## Abstract (arXiv)

The ability of humans to create and disseminate culture is often credited as the single most important factor of our success as a species. In this Perspective, we explore the notion of machine culture, culture mediated or generated by machines. We argue that intelligent machines simultaneously transform the cultural evolutionary processes of variation, transmission, and selection. Recommender algorithms are altering social learning dynamics. Chatbots are forming a new mode of cultural transmission, serving as cultural models. Furthermore, intelligent machines are evolving as contributors in generating cultural traits--from game strategies and visual art to scientific results. We provide a conceptual framework for studying the present and anticipated future impact of machines on cultural evolution, and present a research agenda for the study of machine culture.