# Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation

arXiv: https://arxiv.org/abs/2402.12590 · HTML: https://mlsanity.com/paper/2402.12590/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 29 of its 63 references that are in the map.
- First posted on arXiv 19 Feb 2024.

## Builds on (most cited first, 29 of 29)

- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Tree of Thoughts: Deliberate Problem Solving with Large Language Models](https://mlsanity.com/paper/2305.10601/) (2023)
- [Improving Factuality and Reasoning in Language Models through Multiagent Debate](https://mlsanity.com/paper/2305.14325/) (2023)
- [Towards Understanding Sycophancy in Language Models](https://mlsanity.com/paper/2310.13548/) (2023)
- [Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate](https://mlsanity.com/paper/2305.19118/) (2023)
- [Out of One, Many: Using Language Models to Simulate Human Samples](https://mlsanity.com/paper/2209.06899/) (2022)
- [ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate](https://mlsanity.com/paper/2308.07201/) (2023)
- [Transformers learn in-context by gradient descent](https://mlsanity.com/paper/2212.07677/) (2022)
- [Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm](https://mlsanity.com/paper/2102.07350/) (2021)
- [Hallucination is Inevitable: An Innate Limitation of Large Language Models](https://mlsanity.com/paper/2401.11817/) (2024)
- [A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration](https://mlsanity.com/paper/2310.02170/) (2023)
- ["Kelly is a Warm Person, Joseph is a Role Model": Gender Biases in LLM-Generated Reference Letters](https://mlsanity.com/paper/2310.09219/) (2023)
- [Theory of Mind for Multi-Agent Collaboration via Large Language Models](https://mlsanity.com/paper/2310.10701/) (2023)
- [Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia](https://mlsanity.com/paper/2312.03664/) (2023)
- [PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations](https://mlsanity.com/paper/2307.02762/) (2023)
- [Revolutionizing Finance with LLMs: An Overview of Applications and Insights](https://mlsanity.com/paper/2401.11641/) (2024)
- [How FaR Are Large Language Models From Agents with Theory-of-Mind?](https://mlsanity.com/paper/2310.03051/) (2023)
- [Simulating Social Media Using Large Language Models to Evaluate Alternative News Feed Algorithms](https://mlsanity.com/paper/2310.05984/) (2023)
- [LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay](https://mlsanity.com/paper/2310.14985/) (2023)
- [The Persuasive Power of Large Language Models](https://mlsanity.com/paper/2312.15523/) (2023)
- [Welfare Diplomacy: Benchmarking Language Model Cooperation](https://mlsanity.com/paper/2310.08901/) (2023)
- [From LLM to Conversational Agent: A Memory Enhanced Architecture with Fine-Tuning of Large Language Models](https://mlsanity.com/paper/2401.02777/) (2024)
- [Accelerating science with human-aware artificial intelligence](https://mlsanity.com/paper/2306.01495/) (2023)
- [Balancing Autonomy and Alignment: A Multi-Dimensional Taxonomy for Autonomous LLM-powered Multi-Agent Architectures](https://mlsanity.com/paper/2310.03659/) (2023)
- [Emergence of Scale-Free Networks in Social Interactions among Large Language Models](https://mlsanity.com/paper/2312.06619/) (2023)
- [An evolutionary model of personality traits related to cooperative behavior using a large language model](https://mlsanity.com/paper/2310.05976/) (2023)
- [The Wisdom of Polarized Crowds](https://mlsanity.com/paper/1712.06414/) (2017)
- [New Directions in Science Emerge from Disconnection and Discord](https://mlsanity.com/paper/2103.03398/) (2021)

## Built on by (most cited first, 13 of 13)

- [AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society](https://mlsanity.com/paper/2502.08691/) (2025)
- [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)
- [Can Machines Think Like Humans? A Behavioral Evaluation of LLM Agents in Dictator Games](https://mlsanity.com/paper/2410.21359/) (2024)
- [Safety Must Precede the Deployment of Open-Ended AI](https://mlsanity.com/paper/2502.04512/) (2025)
- [On the Dynamics of Multi-Agent LLM Communities Driven by Value Diversity](https://mlsanity.com/paper/2512.10665/) (2025)
- [Evolving Interpretable Constitutions for Multi-Agent Coordination](https://mlsanity.com/paper/2602.00755/) (2026)
- [Computational Multi-Agents Society Experiments: Social Modeling Framework Based on Generative Agents](https://mlsanity.com/paper/2508.17366/) (2025)
- [In Silico Sociology: Forecasting COVID-19 Polarization with Large Language Models](https://mlsanity.com/paper/2407.11190/) (2024)
- [Research Superalignment Should Advance Now with Alternating Competence and Conformity Optimization](https://mlsanity.com/paper/2503.07660/) (2025)
- [Artificially intelligent agents in the social and behavioral sciences: A history and outlook](https://mlsanity.com/paper/2510.05743/) (2025)
- [Internal vs. External: Comparing Deliberation and Evolution for Multi-Agent Constitutional Design](https://mlsanity.com/paper/2605.09128/) (2026)
- [Self-Emergence Agent Architecture:Behavior-Inertia HMM, Reflexive Metacognition,and Social-Contrastive Self-Modeling](https://mlsanity.com/paper/2609.17331/) (2026)

## Abstract (arXiv)

Large language model behavior is shaped by the language of those with whom they interact. This capacity and their increasing prevalence online portend that they will intentionally or unintentionally "program" one another and form emergent AI subjectivities, relationships, and collectives. Here, we call upon the research community to investigate these "societies" of interacting artificial intelligences to increase their rewards and reduce their risks for human society and the health of online environments. We use a small "community" of models and their evolving outputs to illustrate how such emergent, decentralized AI collectives can spontaneously expand the bounds of human diversity and reduce the risk of toxic, anti-social behavior online. Finally, we discuss opportunities for AI cross-moderation and address ethical issues and design challenges associated with creating and maintaining free-formed AI collectives.