# Not All Explanations Are Sought: Information-Seeking Psychology for Human-Centered XAI

Published: 2026-08-31 · Updated: 2026-08-31 · Category: Research

Source page: https://www.sipply.dev/story/not-all-explanations-are-sought-information-seeking-cb4a673f · 中文: https://www.sipply.dev/zh/story/not-all-explanations-are-sought-information-seeking-cb4a673f

## Summary

A recent paper on arXiv emphasizes the need to incorporate information-seeking psychology into the design of human-centered explainable AI (HCXAI). The authors argue that understanding cognitive biases is crucial for enhancing user engagement with AI explanations. By aligning AI systems with users' motivations for seeking explanations, designers can create more effective and user-friendly AI interfaces. This approach marks a significant shift from traditional methods that often overlook the psychological factors influencing user interaction with AI systems.

## Key takeaways

- Integrating information-seeking psychology can enhance user engagement with AI explanations.
- Cognitive biases play a significant role in how users interact with AI systems.
- Designing AI systems that align with user motivations can improve the effectiveness of explanations.

## Why it matters

This research highlights the critical role of user psychology in the development of explainable AI, which is essential for fostering trust and understanding in AI systems.

- **Product managers:** For product managers, this insight underscores the importance of user-centered design in AI products, ensuring that explanations are not only informative but also aligned with user needs and motivations.
- **Developers:** Developers should consider cognitive biases when creating AI systems, as this understanding can lead to more intuitive and effective user interfaces that enhance user experience.
- **Students and job seekers:** For students and job-seekers, this research presents an opportunity to explore the intersection of psychology and AI, a growing field that values interdisciplinary knowledge and user-centric design.

## Sources

- [Not All Explanations Are Sought: Information-Seeking Psychology for Human-Centered XAI](https://arxiv.org/abs/2608.27464) (arXiv cs.AI, 2026-08-31)

## 中文

### 并非所有解释都是被寻求的：以人为本的XAI的信息寻求心理学

一篇关于arXiv的最新论文强调了在以人为本的可解释AI（HCXAI）设计中融入信息寻求心理学的必要性。作者认为，理解认知偏见对于增强用户与AI解释的互动至关重要。通过将AI系统与用户寻求解释的动机对齐，设计师可以创建更有效且用户友好的AI界面。这种方法标志着与传统方法的显著转变，后者常常忽视影响用户与AI系统互动的心理因素。

**要点：**

- 整合信息寻求心理学可以增强用户与AI解释的互动。
- 认知偏见在用户与AI系统的互动中发挥重要作用。
- 设计与用户动机对齐的AI系统可以提高解释的有效性。

**为什么重要：** 这项研究突显了用户心理在可解释AI开发中的关键作用，这对于建立对AI系统的信任和理解至关重要。

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