mlsanityData to 7 Oct 2026

From Text to Trust: Empowering AI-assisted Decision Making with Adaptive LLM-powered Analysis

arXiv 2502.11919 ↗First posted 17 Feb 2025cs.HC cs.CLcited by 9

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Abstract (arXiv)

AI-assisted decision making becomes increasingly prevalent, yet individuals often fail to utilize AI-based decision aids appropriately especially when the AI explanations are absent, potentially as they do not %understand reflect on AI's decision recommendations critically. Large language models (LLMs), with their exceptional conversational and analytical capabilities, present great opportunities to enhance AI-assisted decision making in the absence of AI explanations by providing natural-language-based analysis of AI's decision recommendation, e.g., how each feature of a decision making task might contribute to the AI recommendation. In this paper, via a randomized experiment, we first show that presenting LLM-powered analysis of each task feature, either sequentially or concurrently, does not significantly improve people's AI-assisted decision performance. To enable decision makers to better leverage LLM-powered analysis, we then propose an algorithmic framework to characterize the effects of LLM-powered analysis on human decisions and dynamically decide which analysis to present. Our evaluation with human subjects shows that this approach effectively improves decision makers' appropriate reliance on AI in AI-assisted decision making.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 55 of its 101 references that are in the map. First posted on arXiv 17 Feb 2025.

Builds on

55 of 101 references.

References · 55

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38 more
  1. 2022Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionalscited by 191
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 7.

9 papers.

  1. 2025MoMoE: Mixture of Moderation Experts Framework for AI-Assisted Online Governancecited by 13
  2. 2025Guiding LLM Decision-Making with Fairness Reward Modelscited by 9
  3. 2026Human-LLM Collaborative Feature Engineering for Tabular Datacited by 1
  4. 2026Can LLMs Truly Embody Human Personality? Analyzing AI and Human Behavior Alignment in Dispute Resolutioncited by 1
  5. 2026More Isn't Always Better: Balancing Decision Accuracy and Conformity Pressures in Multi-AI Advicecited by 1
  6. 2026A-ProS: Towards Reliable Autonomous Programming Through Multi-Model Feedbackcited by 1
  7. 2026Who Does What? Archetypes of Roles Assigned to LLMs During Human-AI Decision-Makingcited by 0
  8. 2026Seeking Information with RAG-Assistants: Does Model Size Matter in Human-AI Collaborations?cited by 0
  9. 2026Annie, Are You Okay? How Style- and Context-Based Personalization Shape AI-Assisted Decision-Makingcited by 0