mlsanityData to 14 Oct 2026

Large Language Models are Biased Because They Are Large Language Models

arXiv 2406.13138 ↗First posted 19 Jun 2024cs.CL cs.AIcited by 26

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Abstract (arXiv)

This position paper's primary goal is to provoke thoughtful discussion about the relationship between bias and fundamental properties of large language models. I do this by seeking to convince the reader that harmful biases are an inevitable consequence arising from the design of any large language model as LLMs are currently formulated. To the extent that this is true, it suggests that the problem of harmful bias cannot be properly addressed without a serious reconsideration of AI driven by LLMs, going back to the foundational assumptions underlying their design.

Key facts. Cited by 26 papers in the map (data through 14 Oct 2026). Builds on 6 of its 38 references that are in the map. First posted on arXiv 19 Jun 2024.

Builds on

6 of 38 references.

References · 6

  1. 2021On the Opportunities and Risks of Foundation Modelscited by 4,033
  2. 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 956
  3. 2016Semantics derived automatically from language corpora contain human-like biasescited by 901
  4. 2023Bias and Fairness in Large Language Models: A Surveycited by 639
  5. 2020On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behaviorcited by 119
  6. 2020Syntactic Structure from Deep Learningcited by 99

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 12; 2026: 12.

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  1. 2025How Linguistics Learned to Stop Worrying and Love the Language Modelscited by 51
  2. 2024Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)cited by 20
  3. 2024'Since Lawyers are Males..': Examining Implicit Gender Bias in Hindi Language Generation by LLMscited by 8
  4. 2025Sherkala-Chat: Building a State-of-the-Art LLM for Kazakh in a Moderately Resourced Settingcited by 4
  5. 2025Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the roomcited by 3
  6. 2025AMBEDKAR-A Multi-level Bias Elimination through a Decoding Approach with Knowledge Augmentation for Robust Constitutional Alignment of Language Modelscited by 2
  7. 2025ATA: A Neuro-Symbolic Approach to Implement Autonomous and Trustworthy Agentscited by 2
  8. 2025Problems With Large Language Models for Learner Modelling: Why LLMs Alone Fall Short for Responsible Tutoring in K--12 Educationcited by 2
  9. 2026Neural-Symbolic Knowledge Tracing: Injecting Educational Knowledge into Deep Learning for Responsible Learner Modellingcited by 1
  10. 2025A Detailed Study on LLM Biases Concerning Corporate Social Responsibility and Green Supply Chainscited by 0
  11. 2025What AI Speaks for Your Community: Polling AI Agents for Public Opinion on Data Center Projectscited by 0
  12. 2025Language models as tools for investigating the distinction between possible and impossible natural languagescited by 0
14 more
  1. 2025Large language models have learned to use languagecited by 0
  2. 2025Large language models are not about natural languagecited by 0
  3. 2025Linguists should learn to love speech-based deep learning modelscited by 0
  4. 2026BiasLab: A Multilingual Dual-Framing Framework for LLM Bias Measurement, Applied to Workplace and HR Contextscited by 0
  5. 2026Are Language Models Models?cited by 0
  6. 2026Adaptive Prompt Elicitation for Text-to-Image Generationcited by 0
  7. 2026Simulating Meaning, Nevermore! Introducing ICR: A Semiotic-Hermeneutic Metric for Evaluating Meaning in LLM Text Summariescited by 0
  8. 2026The Third Ambition: Artificial Intelligence and the Science of Human Behaviorcited by 0
  9. 2026Across the Levels of Analysis: Explaining Predictive Processing in Humans Requires More Than Machine-Estimated Probabilitiescited by 0
  10. 2026You Can't Fight in Here! This is BBS!cited by 0
  11. 2026Auditing demographic bias in AI-based emergency police dispatch: a cross-lingual evaluation of eleven large language modelscited by 0
  12. 2026Not-So-Strange Love: Language Models and Generative Linguistic Theories are More Compatible than They Appearcited by 0
  13. 2026Unequal Verdicts: Investigating Gender Bias in LLM-Based Fake News Detectioncited by 0
  14. 2026Language, Language Models, and What We're Talking Aboutcited by 0