The increasing use of AI tools for information retrieval (IR) among students raises both ethical concerns and the need to examine their awareness of the potential algorithm bias that characterizes AI-enabled IR systems.
Purpose
The study investigated AI algorithm bias awareness and ethical concern as predictors of use of AI for information retrieval among LIS students in Nigeria.
Research Design
The study employed the descriptive type of correlational research design, based on its ability to describe the variables of the study and ascertain the relationship that existed among them.
Study Sample
A total of 213 respondents were selected for the study using the accidental sampling technique of the nonprobability type.
Data Collection
The instrument used for data collection was a self-developed structured questionnaire. The questionnaire was converted to an online survey using Google Forms to elicit data from the respondents for a period of four weeks.
Data analysis
The collected data were analysed using descriptive (frequencies, mean and standard deviation) and inferential (PPMC and multiple regression) statistics and with the aid of the Statistical Package for the Social Sciences (SPSS) version 28.
Results
Findings revealed a significant relationship among AI algorithm bias awareness, ethical concerns and use of AI for information retrieval among LIS students in Nigeria. The study also showed a high level of LIS students` awareness of the potential bias in AI algorithm in information retrieval. In spite of this, the study recorded that the level of LIS students’ use of AI for information retrieval is high.
Conclusions
The study concluded that the structure and content of LIS curriculum in Nigeria exposes the students to the rudiments of ICT application to librarianship, putting them at a position of knowledge-advantage.
AdelakunNO (2024) Exploring the impact of artificial intelligence on information retrieval systems. Information Matters4(5): 4834942.
2.
AhmadNMilicNIbahrineM (2021) Data and disinformation. Computer54(7): 105–110.
3.
Akın İnselMGonce KockenHAlbayrakI, et al. (2024) Data-driven AI for information retrieval of biomedical images. In: MalviyaRSundramSKumar DhanarajR, et al. (eds) Digital Transformation in Healthcare 5.0: Volume 1: Iot, AI and Digital Twin. De Gruyter, 307–330.
4.
AkterSMcCarthyGSajibS, et al. (2021) Algorithmic bias in data-driven innovation in the age of AI. International Journal of Information Management60: 102387.
5.
AlhayaniBMohammedHJChaloobIZ, et al. (2021) Effectiveness of artificial intelligence techniques against cyber security risks apply of IT industry. Materials Today: Proceedings21: 531.
6.
AllamHDempereJVishweshA, et al. (2023) Artificial intelligence in education: an argument of Chat-GPT use in education. In: 2023 9th International Conference on Information Technology Trends (ITT), Dubai, United Arab Emirates. IEEE, Vol. 2023, 151–156.
7.
BernardNBalogK (2023) A systematic review of fairness, accountability, transparency and ethics in information retrieval. ACM Computing Surveys57: 1–29.
8.
Bin-NashwanSASadallahMBouteraa (2023) Use of ChatGPT in academia: academic integrity hangs in the balance. Technology in Society75: 102370.
9.
BradleyF (2022) Representation of libraries in artificial intelligence regulations and implications for ethics and practice. Journal of the Australian Library and Information Association71(3): 189–200.
10.
ChenTGuoWGaoX, et al. (2021) AI-based self-service technology in public service delivery: user experience and influencing factors. Government Information Quarterly38(4): 101520.
11.
CollinsCDennehyDConboyKMikalefP (2021) Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management60: 102383. doi: 10.1016/j.ijinfomgt.2021.102383.
12.
EchedomAUOkuonghaeO (2021) Transforming academic library operations in Africa with artificial intelligence: opportunities and challenges: a review paper. New Review of Academic Librarianship27(2): 243–255.
FuSCutchinSMHowellK, et al. (2020) Full Paper: Algorithm Bias: Computer Science Student Perceptions Survey Paper Presented at Proceedings of the 2020 ASEE PSW Section Conference, Canceled. Retrieved from. https://peer.asee.org/36036
15.
GhotbiNTung HoM (2021) Moral awareness of college students regarding artificial intelligence. Asian Bioethics Review13(4): 421–433.
16.
GuptaPAn andASinghJ, et al. (2024) Study on artificial intelligence (AI) initiatives in e-service delivery systems: a service process perception model. International Journal of Services Operations and Informatics12(4): 344–366.
17.
HajigholamAMirhosseiniM (2023) A scoping review on the impact of algorithm bias on the perceived fairness. Research Square1: 3428999.
18.
HillJEHarrisCCleggA (2023) Method for using Bing’s AI-powered search engine for data extraction for systematic review. Research Synthesis Methods15(2): 347–353.
19.
Hodonu-wusuJO (2024) The rise of artificial intelligence in libraries: the ethical and equitable methodologies, and prospects for empowering library users. AI and Ethics1: 1-11.
20.
HuangCZhangZMaoB, et al. (2023) An overview of artificial intelligence ethics. IEEE transactions on artificial intelligence4(4): 799–819.
21.
KennedyI (2022) Sample size determination in test-retest and cronbach alpha reliability estimates. British Journal of Contemporary Education2(1): 17–29.
22.
KimTW (2023) Application of artificial intelligence chatbots, including ChatGPT, in education, scholarly work, programming, and content generation and its prospects: a narrative review. Journal of Educational Evaluation for Health Professions20: 38.
23.
KlimovaBPikhartMKacetlJ (2023) Ethical issues of the use of AI-driven Mobile apps for education. Frontiers in Public Health10: 1118116.
24.
KolbjørnsrudVAmicoRThomasRJ (2017) Partnering with AI: how organizations can win over skeptical managers. Strategy & Leadership45(1): 37–43.
25.
LacaveCMolinaAI (2022) A pilot experience to raise awareness among computer science undergraduate about the gender bias of algorithm. In: Garcia-PenalvoFJGarcia-HolgadoA (eds) Proceedings TEEM 2022: Tenth International Conference on Technological Ecosystems for Enhancing Multiculturality: TEEM 2022. Lecture Notes in Educational Technology. Springer, 414–423.
26.
LambrectATuckerC (2019) Algorithm bias? An empirical study of apparent gender-based discrimination in the display of stem career ads. Management Science65(7): 2966–2981.
27.
MakhortykhM (2023) No AI after Auschwitz? Bridging AI and memory ethics in the context of information retrieval of genocide-related information. In: MukherjeeAKulshresthaJChakrabortyA, et al. (eds) Ethics in Artificial Intelligent: Bias, Fairness and Beyond. Springer, 71–83.
28.
MalikARPratiwiYANumertayasaI, et al. (2023) Exploring artificial intelligence in academic essay: higher education student’s perspective. International Journal of Educational Research Open5: 100296.
29.
ManjunathaK (2023) A study on impact of artificial intelligence (AI) on library services. International Journal of Research in Library Science (IJRLS)9(4): 189–199.
30.
McDonaldNPanS (2020) Intersectional AI: a study of how information science students think about ethics and their impact. Proceedings of the ACM on Human-Computer Interaction4(147): 1–19.
31.
MelchiorreABZangerleESchedlM (2020) Personality bias of music recommendation algorithms in recsys 2020. In: SantosRLTBalby MarinhoLDalyEM, et al. (eds) Fourteenth ACM Conference on Recommender Systems. Virtual Event, Brazil, September 22-26, 2020. ACM, 533–538.
32.
NazerLHZatarahRWaldripS, et al. (2023) Bias in artificial intelligence algorithms and recommendations for mitigation. PLOS digital health2(6): e0000278.
33.
NobleSU (2018) Algorithm of Oppression: How Search Engines Reinforce Racism. New York University Press.
34.
OkuonghaeOIgbinoviaMAdebayoJ (2022) Technological readiness and computer self-efficacy as predictors of E-learning adoption by LIS students in Nigeria. Libri - International Journal of Libraries and Information Services72(1): 13–25.
35.
O’NeilC (2016) Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Broadway Books.
RamachandranSCutchinSMFuS (2021) Raising algorithm bias awareness among computer science students through library and computer science instruction. In: Paper Presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. ASEE.
38.
ReisJAmorimMCohenY, et al. (2020) Artificial intelligence in service delivery systems: a systematic literature review. In: RochaÁAdeliHReisL, et al. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing. Springer, Vol. 1159, 222–233.
39.
RudnickaZSzczepanskiJPregowskaA (2024) Artificial intelligence-based algorithms in medical image scan segmentation and intelligent visual content generation: a concise overview. Electronics13(4): 746.
40.
SaeidniaHR (2023) Ethical artificial intelligence (AI): confronting bias and discrimination in the library and information industry. Library Hi Tech News.
SchedlMHaugerDFarrahiK, et al. (2015) On the influence of user characteristic on music recommendation algorithms in advances in information retrieval. In: 37th European Conference on IR Research, ECIR 2015, Vienna, Austria, March 29-April 2, 2015. Proceedings (Lectures Notes in Computer Science, Vol. 9022), Allan Hanbury, Gabriella Kazai, Andreas. Rauber and Norbert Fuhr. ECIR, 339–345.
43.
SchedlMGomezELexE (2022) Retrieval and recommendation systems at the crossroads of artificial intelligence, ethics and regulation. In: SIGIR 22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval; 2022 July 11-15: Association for Computing Machinery, Vol. 2022, 3420–3424.
44.
ShinD (2021) Embodying algorithm, enactive artificial intelligence and the extended cognition: you can see as much as you know about algorithm. Journal of Information Science49(1): 1–14.
45.
ShinDShinE (2023) Datas impact on algorithm bias. Computer56(6): 90–94.
46.
ShinDZaidBBioccaF, et al. (2022) In platform we trust? Unlocking the black-box of news algorithms through interpretation of AI. Journal of Broadcasting & Electronic Media66(2): 235–256.
47.
SlimiZCarballidoBV (2023) Navigating the ethical challenges of artificial intelligence in higher education: an analysis of seven global AI ethics policies. TEM Journal12(2): 590–602.
48.
SoniDN (2023) The role of artificial intelligence in information and library science: opportunities and ethical considerations. International Journal of Research in Humanities & Social Sciences11(7): 41–43.
YlipulliJLuusuaA (2019) Without libraries what have we? Public libraries as nodes for technological empowerment in the era of smart cities, AI and big data. In: Conference: 9th International Conference on Communities and Technologies-Transforming Communities. ACM press, 92–101.
52.
YuYW, J. ZhangYZhangL, et al. (2023) EALM: introducing multidimensional ethical alignment in conversational information retrieval. In: Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in Asia Pacific Region. ACM, 32-39.
