mlsanityData to 14 Oct 2026

Arti-"fickle" Intelligence: Using LLMs as a Tool for Inference in the Political and Social Sciences

arXiv 2504.03822 ↗First posted 4 Apr 2025cs.CY cs.AIcited by 1

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Abstract (arXiv)

Generative large language models (LLMs) are incredibly useful, versatile, and promising tools. However, they will be of most use to political and social science researchers when they are used in a way that advances understanding about real human behaviors and concerns. To promote the scientific use of LLMs, we suggest that researchers in the political and social sciences need to remain focused on the scientific goal of inference. To this end, we discuss the challenges and opportunities related to scientific inference with LLMs, using validation of model output as an illustrative case for discussion. We propose a set of guidelines related to establishing the failure and success of LLMs when completing particular tasks, and discuss how we can make inferences from these observations. We conclude with a discussion of how this refocus will improve the accumulation of shared scientific knowledge about these tools and their uses in the social sciences.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 34 of its 88 references that are in the map. First posted on arXiv 4 Apr 2025.

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34 of 88 references.

References · 34

  1. 2020Scaling Laws for Neural Language Modelscited by 6,586
  2. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  3. 2023Whose Opinions Do Language Models Reflect?cited by 773
  4. 2022Out of One, Many: Using Language Models to Simulate Human Samplescited by 752
  5. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 688
  6. 2025Agent Laboratory: Using LLM Agents as Research Assistantscited by 425
  7. 2023Understanding the Effects of RLHF on LLM Generalisation and Diversitycited by 396
  8. 2024Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researcherscited by 363
  9. 2023Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questionscited by 263
  10. 2024OR-Bench: An Over-Refusal Benchmark for Large Language Modelscited by 244
  11. 2024ProSA: Assessing and Understanding the Prompt Sensitivity of LLMscited by 149
  12. 2024Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Taskscited by 106
22 more
  1. 2024Revisiting Catastrophic Forgetting in Large Language Model Tuningcited by 99
  2. 2023Automated Annotation with Generative AI Requires Validationcited by 76
  3. 2023Simulating Social Media Using Large Language Models to Evaluate Alternative News Feed Algorithmscited by 65
  4. 2023Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remarkcited by 54
  5. 2023AI-Augmented Surveys: Leveraging Large Language Models and Surveys for Opinion Predictioncited by 48
  6. 2024LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation Capabilities Beyond 100 Languagescited by 48
  7. 2024Best Practices for Text Annotation with Large Language Modelscited by 36
  8. 2023LLMs for Science: Usage for Code Generation and Data Analysiscited by 34
  9. 2023Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuningcited by 32
  10. 2025LLM-based Human Simulations Have Not Yet Been Reliablecited by 30
  11. 2024AI for social science and social science of AI: A Surveycited by 29
  12. 2024Empirical evidence of Large Language Model's influence on human spoken communicationcited by 27
  13. 2024Evaluating the Effectiveness of LLMs in Introductory Computer Science Education: A Semester-Long Field Studycited by 26
  14. 2021Artificial intelligence in communication impacts language and social relationshipscited by 22
  15. 2024Large Language Models in Qualitative Research: Uses, Tensions, and Intentionscited by 21
  16. 2025Simulating Cooperative Prosocial Behavior with Multi-Agent LLMs: Evidence and Mechanisms for AI Agents to Inform Policy Decisionscited by 20
  17. 2024Prompt Design Matters for Computational Social Science Tasks but in Unpredictable Wayscited by 16
  18. 2024LitLLMs, LLMs for Literature Review: Are we there yet?cited by 14
  19. 2023Towards Coding Social Science Datasets with Language Modelscited by 11
  20. 2024Enhancing LLM-Based Text Classification in Political Science: Automatic Prompt Optimization and Dynamic Exemplar Selection for Few-Shot Learningcited by 5
  21. 2025LLMs for Translation: Historical, Low-Resourced Languages and Contemporary AI Modelscited by 2
  22. 2024LLMs in Political Science: Heralding a New Era of Visual Analysiscited by 1

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