The Persuasion Paradox: When LLM Explanations Fail to Improve Human-AI Team Performance
📰 ArXiv cs.AI
LLM explanations can increase user confidence but not necessarily improve human-AI team performance
Action Steps
- Identify the types of tasks where LLM explanations may not improve performance
- Analyze the relationship between explanation fluency and user confidence
- Evaluate the impact of LLM explanations on task accuracy and user reliance on AI
Who Needs to Know This
Data scientists and AI engineers can benefit from understanding the limitations of LLM explanations to improve human-AI collaboration, while product managers should consider the potential impact on user trust and decision-making
Key Insight
💡 Fluent LLM explanations can increase user confidence without improving task accuracy
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🤖 LLM explanations can boost confidence but not always accuracy #AI #LLMs
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