PulseAugur
EN
LIVE 13:42:19
research · [2 sources] ·

LLM narrative explanations may hinder decision-making performance

By PulseAugur Editorial · Summary by gemini-2.5-flash-lite from 2 sources

A new study published on arXiv explores how persuasive narrative explanations from large language models (LLMs) affect human decision-making in classification tasks. The research found that while these explanations increased reliance on AI, they did not significantly improve decision accuracy compared to AI predictions alone. Furthermore, more persuasive narratives may negatively impact response times and the ability to discern correct AI predictions, suggesting potential trade-offs in using narrative explanations. AI

Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →

IMPACT LLM narrative explanations may introduce performance trade-offs, requiring further research into their optimal application.

RANK_REASON Academic paper on LLM capabilities.

Read on arXiv cs.AI →

COVERAGE [2]

  1. arXiv cs.AI TIER_1 · Laura R. Marusich, Mary Grace Kozuch Dhooghe, Jonathan Z. Bakdash, Murat Kantarcioglu ·

    Human Decision-Making with Persuasive and Narrative LLM Explanations

    arXiv:2605.23867v1 Announce Type: cross Abstract: Large language models (LLMs) have the potential to aid and improve human decision-making in classification tasks, not only by providing fairly accurate predictions, but also in their ability to generate cogent narrative explanatio…

  2. arXiv cs.AI TIER_1 · Murat Kantarcioglu ·

    Human Decision-Making with Persuasive and Narrative LLM Explanations

    Large language models (LLMs) have the potential to aid and improve human decision-making in classification tasks, not only by providing fairly accurate predictions, but also in their ability to generate cogent narrative explanations of those predictions. Prior work has demonstrat…

RELATED ENTITIES

RELATED TOPICS