mlsanityData to 13 Oct 2026

Fair Like Us? Auditing LLM Alignment in Resource Allocation

arXiv 2609.29692 ↗First posted 31 Aug 2026cs.AI cs.CY cs.GTcited by 0

On the map: LLM alignment / RLHF / preference optimisation → Human values and AI feedback alignment

Abstract (arXiv)

Fair allocation of scarce, indivisible resources is an important challenge in many societal problems. While there are several formal theories of fairness, no single definition can always be satisfied. As large language models (LLMs) are increasingly used to support decisions and act as agents, they raise new concerns about distributional justice: their judgments are not directly tied to any specific fairness framework and may violate key normative principles. In this work, we introduce a general method for evaluating fairness reasoning in LLMs. We study first-person fairness judgments across a broad set of models and compare them directly with human responses on matched scenarios and elicitation conditions. We find that LLMs tend to prefer stricter fairness constraints than humans, show more self-interested behavior, are sensitive to how information is framed, and are difficult to align with human judgments using fine-tuning with current datasets.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Placed in Human values and AI feedback alignment, one of 10 directions in LLM alignment / RLHF / preference optimisation. Builds on 28 of its 76 references that are in the map. First posted on arXiv 31 Aug 2026.

Builds on

28 of 76 references.

Closest ancestors · 4

Same direction, newest first

  1. 2025Aligning Large Language Model Agents with Rational and Moral Preferences: A Supervised Fine-Tuning Approach28 Jul
  2. 2025Cultivating Pluralism In Algorithmic Monoculture: The Community Alignment Dataset13 Jul
  3. 2025Distributive Fairness in Large Language Models: Evaluating Alignment with Human Values1 Feb
  4. 2020Aligning AI With Shared Human Values5 Aug

Other references · 24

  1. 2024The Llama 3 Herd of Modelscited by 14,486
  2. 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,714
  3. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,541
  4. 2023Large Language Models Can Be Easily Distracted by Irrelevant Contextcited by 829
  5. 2023Evaluating the Moral Beliefs Encoded in LLMscited by 212
  6. 2023Do LLMs exhibit human-like response biases? A case study in survey designcited by 177
  7. 2023A Categorical Archive of ChatGPT Failurescited by 168
  8. 2023Debiasing Vision-Language Models via Biased Promptscited by 148
  9. 2025Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond)cited by 137
  10. 2022Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?cited by 89
  11. 2021Towards a Science of Human-AI Decision Making: A Survey of Empirical Studiescited by 86
  12. 2024Game-theoretic LLM: Agent Workflow for Negotiation Gamescited by 55
12 more
  1. 2025The Homogenizing Effect of Large Language Models on Human Expression and Thoughtcited by 35
  2. 2016Fair Public Decision Makingcited by 21
  3. 2025Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargainingcited by 11
  4. 2025Understanding LLM Agent Behaviours via Game Theory: Strategy Recognition, Biases and Multi-Agent Dynamicscited by 11
  5. 2025Many LLMs Are More Utilitarian Than Onecited by 7
  6. 2026Strategic Algorithmic Monoculture: Experimental Evidence from Coordination Gamescited by 7
  7. 2021Evaluating the application of NLP tools in mainstream participatory budgeting processes in Scotlandcited by 3
  8. 2025The Illusion of Rationality: Tacit Bias and Strategic Dominance in Frontier LLM Negotiation Gamescited by 3
  9. 2026The Judgment-Consequence Gap: LLM Moral Reasoning in Healthcare Decisionscited by 3
  10. 2025Exploring Large Language Model Agents for Piloting Social Experimentscited by 2
  11. 2025Can LLMs Help Allocate Public Health Resources? A Case Study on Childhood Lead Testingcited by 2
  12. 2025Bridging Theory and Perception in Fair Division: A Study on Comparative and Fair Share Notionscited by 1

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  1. 2025Guiding LLM Decision-Making with Fairness Reward Models
  2. 2025FairCoder: Probing LLM Bias in High-Stakes Decision Making via Coding Tasks
  3. 2025Interactional Fairness in LLM Multi-Agent Systems: An Evaluation Framework
  4. 2024Few-Shot Fairness: Unveiling LLM's Potential for Fairness-Aware Classification
  5. 2025Debiasing LLMs by Masking Unfairness-Driving Attention Heads
  6. 2026Beyond Arrow's Impossibility: Fairness as an Emergent Property of Multi-Agent Collaboration
  7. 2024With a Grain of SALT: Are LLMs Fair Across Social Dimensions?
  8. 2025Reasoning Towards Fairness: Mitigating Bias in Language Models through Reasoning-Guided Fine-Tuning