User Interaction for Human–AI Interaction and Collaboration

doi:10.1017/9781009587877.003

2 - User Interaction for Human–AI Interaction and Collaboration

Published online by Cambridge University Press: 19 September 2025

Dan Wu and

Qingyue Guo

Edited by

Dan Wu and

Shaobo Liang

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Dan Wu: Affiliation:
Wuhan University, China
Shaobo Liang: Affiliation:
Wuhan University, China

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Summary

It is of great importance to integrate human-centered design concepts at the core of both algorithmic research and the implementation of applications. In order to do so, it is essential to gain an understanding of human–computer interaction and collaboration from the perspective of the user. To address this issue, this chapter initially presents a description of the process of human–AI interaction and collaboration, and subsequently proposes a theoretical framework for it. In accordance with this framework, the current research hotspots are identified in terms of interaction quality and interaction mode. Among these topics, user mental modeling, interpretable AI, trust, and anthropomorphism are currently the subject of academic interest with regard to interaction quality. The level of interaction mode encompasses a range of topics, including interaction paradigms, role assignment, interaction boundaries, and interaction ethics. To further advance the related research, this chapter identifies three areas for future exploration: cognitive frameworks about Human–AI Interaction, adaptive learning, and the complementary strengths of humans and AI.

Keywords

Artificial Intelligence Human–AI Interaction Human–AI Collaboration User Interaction

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Type: Chapter
Information: Human-AI Interaction and Collaboration , pp. 14 - 42

DOI: https://doi.org/10.1017/9781009587877.003 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2025

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You will encounter all content (including footnotes, captions, etc.) in a clear, sequential flow, making it easier to follow with assistive tools like screen readers.

Short alternative textual descriptions
You get concise descriptions (for images, charts, or media clips), ensuring you do not miss crucial information when visual or audio elements are not accessible.

Full alternative textual descriptions
You get more than just short alt text: you have comprehensive text equivalents, transcripts, captions, or audio descriptions for substantial non‐text content, which is especially helpful for complex visuals or multimedia.

Visual Accessibility

Use of colour is not sole means of conveying information
You will still understand key ideas or prompts without relying solely on colour, which is especially helpful if you have colour vision deficiencies.

Use of high contrast between text and background colour
You benefit from high‐contrast text, which improves legibility if you have low vision or if you are reading in less‐than‐ideal lighting conditions.