# Modeling Reliance on XAI Indicating Its Purpose and Attention

arXiv: https://arxiv.org/abs/2302.08067 · HTML: https://mlsanity.com/paper/2302.08067/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Feb 2023.

## Built on by (most cited first, 4 of 4)

- [How explainable AI affects human performance: A systematic review of the behavioural consequences of saliency maps](https://mlsanity.com/paper/2404.16042/) (2024)
- [User Decision Guidance with Selective Explanation Presentation from Explainable-AI](https://mlsanity.com/paper/2402.18016/) (2024)
- [Dynamic Explanation Emphasis in Human-XAI Interaction with Communication Robot](https://mlsanity.com/paper/2403.14550/) (2024)
- [Should XAI Nudge Human Decisions with Explanation Biasing?](https://mlsanity.com/paper/2406.07323/) (2024)

## Abstract (arXiv)

This study used XAI, which shows its purposes and attention as explanations of its process, and investigated how these explanations affect human trust in and use of AI. In this study, we generated heat maps indicating AI attention, conducted Experiment 1 to confirm the validity of the interpretability of the heat maps, and conducted Experiment 2 to investigate the effects of the purpose and heat maps in terms of reliance (depending on AI) and compliance (accepting answers of AI). The results of structural equation modeling (SEM) analyses showed that (1) displaying the purpose of AI positively and negatively influenced trust depending on the types of AI usage, reliance or compliance, and task difficulty, (2) just displaying the heat maps negatively influenced trust in a more difficult task, and (3) the heat maps positively influenced trust according to their interpretability in a more difficult task.