Fenomena Penggunaan Generative AI dalam Perilaku Pencarian Informasi Praktisi Teknologi
DOI:
https://doi.org/10.37014/medpus.v31i2.5222Keywords:
artificial intelligence, generative ai, information seeking behavior , phenomenologyAbstract
The emergence of generative AI technology which has provided new experiences for technology practitioners in searching for information to obtain professional information needs and complete their tasks, needs to be studied further as an effort to anticipate various impacts and potentials that may occur. Therefore, research is needed that identifies the use of generative AI technology in the information behavior patterns of technology practitioners at the start-up company PT XYZ. This research used qualitative with phenomenological approach. Based on the experiences of the three informants when using generative AI to search for information, the informants had different needs, but the informants had positive experiences in using generative AI to search for information, so that it could be an alternative solution to the needs and problems they experienced. Informants have varied experiences in searching for information, and in some contexts there are even experiences of using similar strategies. Several strategies from the informants' search experiences consisted of using simple prompts, using prompts that were supported by additional context, and using prompts that contained scenarios and narratives. The information seeking behavior pattern of technology practitioners who uses generative AI in PT XYZ were identified as very varied based on their task and job functions, both in terms of needs and the search strategies they used.References
Akbari, A., Rigi, T., & Fattahi, R. (2017). From information seeking behavior to knowledge seeking behavior: Analysis of conceptual and theoretical evolution. Iranian Journal of Information Processing and Management, 34(4), 1927–1954.
Andejany, M. (2023). Is an academic degree required for a successful product manger? Proceedings of the 7th North American International Conference on Industrial Engineering and Operations Management, Luck 1969, 1395–1407. https://doi.org/10.46254/na07.20220320
Creswell, J. W., & Creswell, J. D. (2023). Research design: qualitative, quantitative, and mixed methods approaches. In Sage Publication (6th ed.). SAGE Publications Ltd.
Erlianti, G., Zuve, F. O., Nabila, J., & Habiburrahman. (2022). Patterns of information seeking behavior from leckie’s perspective in the new normal era. In Proceedings of the 5th International Conference on Language, Literature, and Education (ICLLE-5 2022) (pp. 426–436). Atlantis Press SARL. https://doi.org/10.2991/978-2-494069-85-5_46
Gadhavi, H., & Vyas, K. (2023). An overview of information-seeking behavior. RESEARCH HUB International Multidisciplinary Research Journal, 10(4), 17–21. https://doi.org/10.53573/rhimrj.2023.v10n04.003
Greening, N. (2019). Phenomenological research methodology. Scientific Research Journal, VII(V), 88–92. https://doi.org/10.31364/scirj/v7.i5.2019.p0519656
Habiburrahman, H. (2023). Pola perilaku pencarian informasi dosen pembelajaran jarak jauh dalam perspektif leckie di era new normal. JIPI (Jurnal Ilmu Perpustakaan Dan Informasi), 8(1), 17. https://doi.org/10.30829/jipi.v8i1.13715
Jha, R. K. (2023). The role of a data analyst: Unlocking insights in a data- driven world. International Journal of Computer Science and Mobile Applications, 11(10), 4–7.
Karunaratne, T., & Adesina, A. (2023). Is it the new Google: Impact of ChatGPT on students’ information search habits. Proceedings of the European Conference on E-Learning, ECEL, 2023-Octob, 147–155. https://doi.org/10.34190/ecel.22.1.1831
Kundu, D. K. (2022). Models of information seeking behaviour: A Comparative study. SSRN Electronic Journal, July 2020. https://doi.org/10.2139/ssrn.4289303
Larsen, H. G., & Adu, P. (2021). The theoretical framework in phenomenological research. In The Theoretical Framework in Phenomenological Research. Routledge. https://doi.org/10.4324/9781003084259
Nhavkar, V. K., & Goel, S. K. (2023). Impact of generative ai on different stakeholders. International Journal For Multidisciplinary Research, 5(5). https://doi.org/10.36948/ijfmr.2023.v05i05.7743
Pagano, R., & Blair, G. (2023). Strategies for managing technological change: insights from practitioners. Tasambo Journal of Language, Literature, and Culture, 1(01), 94–102. https://doi.org/10.36349/tjllc.2023.v01i01.011
Petrovic, B., Poje, I., & Feldvari, K. (2024). The use of chatgpt in higher education teaching: subject information behavior of lis students. Proceedings of the 15th International Conference on Society and Information Technologies: ICSIT 2024, Icsit, 14–20. https://doi.org/10.54808/icsit2024.01.14
Puntoni, S., & Wertenbroch, K. (2024). Being human in the age of ai. Journal of the Association for Consumer Research. https://doi.org/10.1086/730788
Rahayu, S., & Purwaningtyas, F. (2023). Pola perilaku penelusuran informasi mahasiswa prodi ilmu perpustakaan UIN Sumatera Utara di era digital native. Comit: Communication, Information and Technology Journal, 1(2), 112–120. https://doi.org/10.47467/comit.v1i2.40
Ramlan, P., Tajuddin, S., Adri, K., Mardhatillah, & Febrianti, D. (2021). Artificial intelligence model back-end engine in gathering public services in carawali village. IOP Conference Series: Earth and Environmental Science, 717(1), 0–6. https://doi.org/10.1088/1755-1315/717/1/012048
Rios-Campos, C., Viteri, J. D. C. L., Batalla, E. A. P., Castro, J. F. C., Núñez, J. B., Calderón, E. V., Nicacio, F. J. G., & Tello, M. Y. P. (2023). Generative artificial intelligence. South Florida Journal of Development, 4(6), 2305–2320. https://doi.org/10.46932/sfjdv4n6-008
Sangari, M., & Zerehsaz, M. (2020). Collaborative information seeking in digital libraries, learning styles, users’ experience, and task complexity. Journal of Information Science Theory and Practice, 8(4), 55–66. https://doi.org/10.1633/JISTaP.2020.8.4.5
Shihab, S. R., Sultana, N., & Samad, A. (2023). Revisiting the use of chatgpt in business and educational fields: possibilities and challenges. Jurnal Multidisiplin Ilmu, 2(3), 534–545. https://journal.mediapublikasi.id/index.php/bullet
Sudirjo, F., Diantoro, K., Al-Gasawneh, J. A., Khootimah Azzaakiyyah, H., & Almaududi Ausat, A. M. (2023). Application of chatgpt in improving customer sentiment analysis for businesses. Jurnal Teknologi Dan Sistem Informasi Bisnis, 5(3), 283–288. https://doi.org/10.47233/jteksis.v5i3.871
Suriani, S., Abustan, A., Djakasaputra, A., Baharuddin, S. M., & Nur, I. (2023). Understanding sentiment and emotion through chatgpt to support emotion-based management decision making. Jurnal Minfo Polgan, 12(2), 1778–1788. https://doi.org/10.33395/jmp.v12i2.13000
Zhou, T., & Li, S. (2024). Understanding user switch of information seeking: From search engines to generative AI. Journal of Librarianship and Information Science. https://doi.org/10.1177/09610006241244800
Zlateva, P., Steshina, L., Petukhov, I., & Velev, D. (2024). A conceptual framework for solving ethical issues in generative artificial intelligence. Frontiers in Artificial Intelligence and Applications, 381, 110–119. https://doi.org/10.3233/FAIA231182
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.