AI-supported Search Interaction for Enhancing Users’ Understanding

doi:10.1017/9781009587877.007

6 - AI-supported Search Interaction for Enhancing Users’ Understanding

Published online by Cambridge University Press: 19 September 2025

Shaobo Liang and

Chenrui Shi

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

This chapter mainly investigates the role of Artificial Intelligence (AI) in augmenting search interactions to enhance users’ understanding across various domains. The chapter begins by examining the current limitations of traditional search interfaces in meeting diverse user needs and cognitive capacities. It then discusses how AI-driven enhancements can revolutionize search experiences by providing tailored, contextually relevant information and facilitating intuitive interactions. Through case studies and empirical analysis, the effectiveness of AI-supported search interaction in improving users’ understanding is evaluated in different scenarios. This chapter contributes to the literature on AI and human–computer interaction by highlighting the transformative potential of AI in optimizing search experiences for users, leading to enhanced comprehension and decision-making. It concludes with implications for research and practice, emphasizing the importance of human-centered design principles in developing AI-driven search systems.

Keywords

Artificial Intelligence Information Search Information Behavior Interactive Search

Information

Type: Chapter
Information: Human-AI Interaction and Collaboration , pp. 135 - 152

DOI: https://doi.org/10.1017/9781009587877.007 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2025

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