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Quality Without Usefulness: LLM-Generated XAI Narratives as Trust Heuristics Rather Than Decision Aids

arXiv — cs.CL•Wednesday, May 27, 2026 at 4:00:00 AM
NeutralArtificial Intelligence
  • What Happened

    A recent study has investigated the effectiveness of Large Language Models (LLMs) in generating Natural Language Explanations (NLEs) for Explainable AI (XAI) outputs, revealing that while these narratives score high on quality metrics, they do not enhance practical decision-making accuracy. The research involved five controlled experiments in energy forecasting, indicating that NLEs may inflate user confidence without improving task performance.

  • Why It Matters

    This finding is significant as it challenges the assumption that high-quality explanations inherently lead to better decision-making, highlighting a potential disconnect between perceived and actual usefulness in AI-generated narratives.

  • The Bigger Picture

    The implications of this research extend to broader discussions on the role of LLMs in various domains, including credit risk assessment and misinformation detection, where the effectiveness of AI-generated explanations is critical. The ongoing exploration of LLM reasoning capabilities and the development of frameworks for improving explainability reflect a growing need for reliable AI systems that not only produce coherent narratives but also support informed decision-making.

— via World Pulse Now AI Editorial System
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