City Research Online

Abstract

Introduction. We report an investigation into the use of generative AI large language model (LLM) tools by information seekers. We elicit the reasons for their use of LLMs in preference to established tools such as social media, interactive search, and libraries.

Method. A mixture of critical-incident retrospective interviews and live observations were used to capture data. The observations were recorded via Zoom, and all sessions were audio-recorded. Transcripts of the interviews and records of the LLM prompts used were all included in the analysis.

Analysis. Thematic analysis was undertaken on the transcript and LLM prompt data. Analysis was done manually, following an iterative process.

Results. Respondent’s preferences for when to use LLMs reflected a range of push factors driving them away from traditional environments, and a set of pull factors drawing them to LLMs. This pattern reflects previous research on migrations.

Conclusions. Information seekers are drawn to the potentially personalised and easy-to-access outputs of LLMs such as ChatGPT, and by the bias and difficulty of use that they ascribe to search engines and social media.

Publication Type:	Article
Additional Information:	© The Authors. Published by Wiley. This is an open-access article distributed under the terms of Creative Commons: Attribution Non-Commercial International Public License 4.0 (http://creativecommons.org/licenses/by-nc/4.0/).
Subjects:	H Social Sciences > HM Sociology H Social Sciences > HN Social history and conditions. Social problems. Social reform Q Science > QA Mathematics > QA75 Electronic computers. Computer science Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Departments:	School of Science & Technology School of Science & Technology > Department of Computer Science School of Science & Technology > Department of Computer Science > Human Computer Interaction Design
SWORD Depositor:	Symplectic Administrator

Export

Downloads