Applied Informatics: Librarian Scepticism of Artificial Intelligence in Information Retrieval

Kayode Sunday John Dada

doi:10.32734/jocai.v10i2.25832

Authors

Kayode Sunday John Dada University Library, Federal University of Education, Zaria, Kaduna State, Nigeria

DOI:

https://doi.org/10.32734/jocai.v10i2.25832

Keywords:

Artificial intelligence Scepticism, Information retrieval, Information supply chain failure, Librarian professional identity, Nigerian university libraries

Abstract

Librarian scepticism towards artificial intelligence (AI) tools in information retrieval is routinely reframed in African higher education discourse as a capacity gap. This paper challenges that reframing. Using a convergent mixed-methods design — a survey of 214 librarians across 27 Nigerian universities, 32 semi-structured interviews, and documentary analysis of 81 institutional documents spanning 2015–2025 — the study pursues three objectives: (1) to examine the nature and structural determinants of librarian scepticism towards AI-assisted retrieval; (2) to determine whether AI adoption promotes or displaces substantive library usage in resource-constrained institutions; and (3) to investigate gendered and geographic dimensions of differential AI scepticism. Findings confirm that scepticism is epistemically rational and structurally grounded. In institutions where AI chatbots generate citation lists that the local collection cannot fulfil, the information outcome is zero regardless of interface sophistication — what the study theorises as an information supply chain failure (ISCF), structurally analogous to a health system that achieves a correct diagnosis but cannot dispense the medication. Only 27.1% of librarians reported that AI-generated references were typically retrievable locally (17.8% in rural institutions). Female librarians in northern Nigeria reported the highest scepticism and the lowest institutional support. No sampled institution held an operational AI-resource integration policy. The study concludes that AI adoption without collection integrity undermines library utility, and recommends a policy-first, resource-second integration framework.

Downloads

Download data is not yet available.

References

[1] A. Abbott, The System of Professions: An Essay on the Division of Expert Labor. Chicago, IL, USA: University of Chicago Press, 1988.

[2] M. K. Abubakar and C. N. Ihejirika, “Awareness and utilisation of artificial intelligence tools among library professionals in Nigerian federal universities,” Library Management, vol. 44, no. 3/4, pp. 201–218, 2023, doi: 10.1108/LM-07-2022-0075.

[3] D. Bawden and L. Robinson, Introduction to Information Science, 2nd ed. London, UK: Facet Publishing, 2022.

[4] E. M. Bender, T. Gebru, A. McMillan-Major, and S. Shmitchell, “On the dangers of stochastic parrots: Can language models be too big?” in Proc. 2021 ACM Conf. Fairness, Accountability, and Transparency (FAccT 2021), 2021, pp. 610–623, doi: 10.1145/3442188.3445922.

[5] M. Bigdeli, B. Jacobs, G. Tomson, R. Laing, A. Ghaffar, B. Dujardin, and W. Van Damme, “Access to medicines from a health system perspective,” Health Policy and Planning, vol. 28, no. 7, pp. 692–704, 2014, doi: 10.1093/heapol/czs108.

[6] G. A. Bowen, “Document analysis as a qualitative research method,” Qualitative Research Journal, vol. 9, no. 2, pp. 27–40, 2009, doi: 10.3316/QRJ0902027.

[7] V. Braun and V. Clarke, Thematic Analysis: A Practical Guide. London, UK: SAGE Publications, 2022.

[8] J. M. Budd, The Academic Library: Its Context, Its Purpose, and Its Operation, 3rd ed. Santa Barbara, CA, USA: Libraries Unlimited, 2023.

[9] D. H. Bui, V. T. Tran, and T. T. Le, “Artificial intelligence in cataloguing: A systematic literature review,” Journal of Librarianship and Information Science, vol. 55, no. 2, pp. 312–328, 2023, doi: 10.1177/09610006221091024.

[10] E. A. Chatman, “The impoverished life-world of outsiders,” Journal of the American Society for Information Science, vol. 47, no. 3, pp. 193–206, 1996, doi: 10.1002/(SICI)1097-4571(199603)47:3<193::AID-ASI3>3.0.CO;2-T.

[11] K. Crenshaw, “Demarginalizing the intersection of race and sex: A Black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics,” University of Chicago Legal Forum, vol. 1989, no. 1, pp. 139–167, 1989.

[12] J. W. Creswell and V. L. Plano Clark, Designing and Conducting Mixed Methods Research, 3rd ed. Thousand Oaks, CA, USA: SAGE Publications, 2018.

[13] V. Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. New York, NY, USA: St. Martin’s Press, 2018.

[14] M. Fricker, Epistemic Injustice: Power and the Ethics of Knowing. Oxford, UK: Oxford University Press, 2007.

[15] C. Fulton, “Quid pro quo: Information sharing in leisure activities,” Library Trends, vol. 57, no. 4, pp. 753–768, 2009, doi: 10.1353/lib.0.0056.

[16] C. Fulton and R. Vondracek, “Editors’ introduction: Pleasurable pursuits: Leisure and LIS research,” Library Trends, vol. 57, no. 4, pp. 611–617, 2009, doi: 10.1353/lib.0.0063.

[17] T. C. Guetterman, M. D. Fetters, and J. W. Creswell, “Integrating quantitative and qualitative results in health science mixed methods research through joint displays,” Annals of Family Medicine, vol. 13, no. 6, pp. 554–561, 2015, doi: 10.1370/afm.1865.

[18] I. Huvila, “Infrastructuring and the politics of library work,” Library Quarterly, vol. 92, no. 4, pp. 437–455, 2022, doi: 10.1086/720912.

[19] P. I. Ilo and G. Ifijeh, “Artificial intelligence and library services in Nigeria: Readiness, barriers, and prospects,” African Journal of Library, Archives and Information Science, vol. 33, no. 1, pp. 55–70, 2023.

[20] Z. Ji et al., “Survey of hallucination in natural language generation,” ACM Computing Surveys, vol. 55, no. 12, Art. no. 248, 2023, doi: 10.1145/3571730.

[21] S. Kwon, J. Park, and H. Seo, “Gender, institutional support, and technology scepticism in library professionals: A cross-national study,” Journal of the American Society for Information Science and Technology, vol. 73, no. 8, pp. 1123–1139, 2022, doi: 10.1002/asi.24619.

[22] R. D. Lankes, The Atlas of New Librarianship. Cambridge, MA, USA: MIT Press, 2011.

[23] H. L. Lee, V. Padmanabhan, and S. Whang, “The bullwhip effect in supply chains,” Sloan Management Review, vol. 38, no. 3, pp. 93–102, 1997.

[24] P. J. Lor and J. J. Britz, “An uncertain future for an information-rich world: Ethical implications of the political economy of information,” The International Information & Library Review, vol. 44, no. 3, pp. 143–151, 2012, doi: 10.1016/j.iilr.2012.07.003.

[25] B. D. Lund and T. Wang, “Chatting about ChatGPT: How may AI and GPT impact academia and libraries?” Library Hi Tech News, vol. 40, no. 3, pp. 26–29, 2023, doi: 10.1108/LHTN-01-2023-0009.

[26] J. Luo, M. Bergmann, and Y. K. Dwivedi, “Measuring AI scepticism: Scale development and validation,” Information Systems Frontiers, vol. 25, no. 4, pp. 1501–1518, 2023, doi: 10.1007/s10796-022-10271-4.

[27] E. C. Madu and C. C. Nwosu, “Perceived usefulness of AI tools in academic libraries: A survey of university libraries in South-East Nigeria,” International Journal of Digital Library Services, vol. 14, no. 1, pp. 38–57, 2024.

[28] National Information Technology Development Agency (NITDA), Digital Access and Connectivity Assessment of Nigerian Higher Education Institutions. Abuja, Nigeria: NITDA, 2023.

[29] National Universities Commission (NUC), Annual Accreditation Status Report of Nigerian Universities. Abuja, Nigeria: NUC, 2022.

[30] O. Nwosu, A. Akintola, and S. Chiemeke, “AI readiness and capacity building in Nigerian libraries: Challenges and opportunities,” Journal of Academic Librarianship, vol. 49, no. 3, Art. no. 102681, 2023, doi: 10.1016/j.acalib.2023.102681.

[31] R. B. Okiy, “Information resources and services in Nigerian university libraries: Access, availability, and the digital divide,” Library Review, vol. 72, no. 1/2, pp. 15–32, 2023, doi: 10.1108/LR-03-2022-0031.

[32] C. M. Owusu-Ansah and A. A. Amoah, “Perceptions of academic librarians in Ghana towards artificial intelligence in library services,” Library Management, vol. 43, no. 3/4, pp. 191–206, 2022, doi: 10.1108/LM-08-2021-0072.

[33] M. O. Salami and J. S. Adeoti, “Perceived barriers to artificial intelligence integration in university libraries in South-West Nigeria,” Libri, vol. 74, no. 1, pp. 51–65, 2024, doi: 10.1515/libri-2023-0012.

[34] R. Singh and P. Nair, “Gender and technology adoption in academic libraries of developing countries: Intersectional considerations,” IFLA Journal, vol. 49, no. 2, pp. 305–321, 2023, doi: 10.1177/03400352221140282.

[35] C. Teddlie and A. Tashakkori, Foundations of Mixed Methods Research: Integrating Quantitative and Qualitative Approaches in the Social and Behavioral Sciences. Thousand Oaks, CA, USA: SAGE Publications, 2009.

[36] J. Varlejs, “AI in collection development: Prospects, perils, and the professional knowledge question,” Collection Management, vol. 47, no. 2, pp. 82–99, 2022, doi: 10.1080/01462679.2021.2014551.

[37] A. S. Vieira, A. A. Baptista, and M. J. Gomes, “Learning analytics and academic libraries: A systematic review of the literature,” Journal of Librarianship and Information Science, vol. 54, no. 3, pp. 417–432, 2022, doi: 10.1177/09610006211024716.

[38] L. Weidinger et al., “Taxonomy of risks posed by language models,” in Proc. 2022 ACM Conf. Fairness, Accountability, and Transparency (FAccT 2022), 2022, pp. 214–229, doi: 10.1145/3531146.3533088.

[39] P. Yadav, “Health product supply chains in developing countries: Diagnosis of the root causes of underperformance and an agenda for reform,” Health Systems & Reform, vol. 1, no. 2, pp. 142–154, 2015, doi: 10.1080/23288604.2015.1030545.

[40] H. Zimba and S. F. Zulu, “Artificial intelligence adoption in Zambian academic libraries: Between aspiration and infrastructure,” Library Management, vol. 44, no. 8/9, pp. 511–527, 2023, doi: 10.1108/LM-03-2023-0024.