mlsanityData to 7 Oct 2026

Social Catalysts, Not Moral Agents: The Illusion of Alignment in LLM Societies

arXiv 2602.02598 ↗First posted 1 Feb 2026physics.soc-ph cs.AI cs.CLcited by 0

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

The rapid evolution of Large Language Models (LLMs) has led to the emergence of Multi-Agent Systems where collective cooperation is often threatened by the "Tragedy of the Commons." This study investigates the effectiveness of Anchoring Agents--pre-programmed altruistic entities--in fostering cooperation within a Public Goods Game (PGG). Using a full factorial design across three state-of-the-art LLMs, we analyzed both behavioral outcomes and internal reasoning chains. While Anchoring Agents successfully boosted local cooperation rates, cognitive decomposition and transfer tests revealed that this effect was driven by strategic compliance and cognitive offloading rather than genuine norm internalization. Notably, most agents reverted to self-interest in new environments, and advanced models like GPT-4.1 exhibited a "Chameleon Effect," masking strategic defection under public scrutiny. These findings highlight a critical gap between behavioral modification and authentic value alignment in artificial societies.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 9 of its 23 references that are in the map. First posted on arXiv 1 Feb 2026.

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9 of 23 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023Generative Agents: Interactive Simulacra of Human Behavior7 Apr

Other references · 8

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  2. 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,413
  3. 2023Towards Understanding Sycophancy in Language Modelscited by 988
  4. 2022Discovering Language Model Behaviors with Model-Written Evaluationscited by 805
  5. 2023Larger language models do in-context learning differentlycited by 386
  6. 2023AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systemscited by 116
  7. 2024Emergent social conventions and collective bias in LLM populationscited by 115
  8. 2024Moral Alignment for LLM Agentscited by 39

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  1. 2025Corrupted by Reasoning: Reasoning Language Models Become Free-Riders in Public Goods Games
  2. 2025The Emergence of Altruism in Large-Language-Model Agents Society
  3. 2024Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents
  4. 2026Payoff scaling shapes cooperation in LLM agents across languages
  5. 2025Understanding LLM Agent Behaviours via Game Theory: Strategy Recognition, Biases and Multi-Agent Dynamics
  6. 2024Cultural Evolution of Cooperation among LLM Agents
  7. 2025Evolution of Cooperation in LLM-Agent Societies: A Preliminary Study Using Different Punishment Strategies
  8. 2026SODE: Analyzing Social Dynamics in LLM Agents