The Drawback of Insight: Detailed Explanations Can Reduce Agreement with XAI
Not on the map. Why?
Abstract (arXiv)
With the emergence of Artificial Intelligence (AI)-based decision-making, explanations help increase new technology adoption through enhanced trust and reliability. However, our experimental study challenges the notion that every user universally values explanations. We argue that the agreement with AI suggestions, whether accompanied by explanations or not, is influenced by individual differences in personality traits and the users' comfort with technology. We found that people with higher neuroticism and lower technological comfort showed more agreement with the recommendations without explanations. As more users become exposed to eXplainable AI (XAI) and AI-based systems, we argue that the XAI design should not provide explanations for users with high neuroticism and low technology comfort. Prioritizing user personalities in XAI systems will help users become better collaborators of AI systems.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 Apr 2024.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 1; 2025: 1.
2 papers.