CoChat
Sign Up
Cited by 65Library Science and InformationWeb and Library ServicesLibrary Science and Information Literacy

Impact of Conversational and Generative AI Systems on Libraries: A Use Case Large Language Model (LLM)

Khan, Rahat, Gupta, Nidhi, Sinhababu, Atasi, Chakravarty, Rupak·2024·Science & Technology Libraries
DOI 10.1080/0194262x.2023.2254814
Open this paper in CoChat — free account

Abstract

The study aims to examine how artificial intelligence (AI) could potentially affect specific services provided by academic libraries in the near future. To achieve this, the study uses three different Generative AI systems: ChatGPT, Perplexity, and iAsk.Ai. By analyzing the potential impact of AI on academic library services, the study aims to provide insights into how libraries can adapt to these changes to better serve their patrons. The three AI systems selected for this study represent different AI approaches that can be used in academic libraries. ChatGPT, for example, is a conversational AI system that can provide quick answers to patrons’ queries, while Perplexity is a language model that can assist with tasks such as cataloging and content classification. iAsk.Ai is a natural language processing (NLP) system that can assist with research and reference inquiries. By assessing the potential impact of these AI systems on academic library services, the study can provide insights into the future of library services and how AI could be used to enhance them. Ultimately, this could help academic libraries prepare for and adapt to the changing technological landscape, ensuring that they continue to meet the needs of their patrons in the years to come.

Integrity signals

Registry

Crossref · 10.1080/0194262x.2023.2254814

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Ethical concerns have been raised with the use of ChatGPT, such as potential negative impacts on genuine human connections and interactions, privacy, and human ingenuity.

    “Ethical concerns have been raised with the use of ChatGPT, such as the potential negative impacts of AI chatbots on genuine human connections and interactions, privacy, and human ingenuity [30,35,37].”

    From Consumer Responses to Generative AI Chatbots Versus Search Engines for Product Evaluation (2025) · cites this paper as [37]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Khan, R., Gupta, N., Sinhababu, A., & Chakravarty, R.
Affiliations
  • Prince Mohammad bin Fahd University (SA)
  • Government College of Education Sector-20, Chandigarh, India
  • Amity University Punjab, Mohali, India
  • Panjab University (IN)
Corresponding author
Gupta, Nidhi
ORCID
Venue
Science & Technology Libraries
Publisher
Informa UK Limited
Published
2023-09-11
Volume
43
Issue
4
Pages
319-333
ISSN
  • 0194-262X (ISSN-L)
  • 1541-1109
DOI
10.1080/0194262x.2023.2254814
OpenAlex
W4386601209
Cited by
65
References
6
Citations by year
2026: 13 · 2025: 34 · 2024: 17 · 2023: 1
FWCI
15.26
Type
journal article
Language
en
Open access
closed
Locations
Science & Technology Libraries (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Library Science and Information
  • Physical Sciences › Computer Science › Information Systems › Web and Library Services
  • Social Sciences › Library and Information Sciences › Library Science and Information Literacy
Keywords
generative AI, academic libraries, library services, large language models, ChatGPT, perplexity, conversational AI, reference services, library cataloging, natural language processing

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review