PHILOSOPHY OF SCIENCE AND INFORMATION SYSTEMS: FOUNDATIONS AND PRACTICAL CHALLENGES
Keywords:
Philosophy of science, philosophy of information systems, philosophy of technology, foundations of information systems.Abstract
The philosophy of science has evolved from ancient times to the present day. Even today’s advancements in information technology are inextricably linked to the philosophy of science. Information systems are a key component of these technological advancements. They have evolved from mere technical tools for managing data into socially constructed entities rich in meaning that influence various aspects of society. This demonstrates that information systems cannot be separated from the social, cultural, and ethical contexts that surround them. The connection between the philosophy of science and information systems has become increasingly significant with the advent of AI technology. The philosophy of science has three main pillars—ontology, epistemology, and axiology—which serve as its conceptual and methodological foundations.
Ontology provides a framework for representing reality that serves as the foundation for system modeling; epistemology guides research paradigms and the methodologies used to acquire and validate knowledge; while axiology emphasizes the importance of values and ethics in both the design and implementation of information systems. With the development of technology, information systems are no longer viewed merely as technical devices, but rather as social constructs with far-reaching impacts. This transformation has become increasingly evident in the era of AI, making the philosophy of science a critical instrument that guides technological innovation to remain aligned with human values and broader social goals.
References
Badudu, J. S. (2014). The role of philosophy of science in building the epistemological foundation of research. Journal of Philosophical Studies and Social Theory, 15(1), 1-12.
Ball, B., Nagle, F., & Votsis, I. (2020). Editorial: Computationalism meets the philosophy of infor-mation. Review of Philosophy and Psychology, 11(3), 507–515.
Bonzio, S., Landes, J., & Osimani, B. (2021). Reliability: an introduction. Synthese, 198(S23), 5615–5624.
Brey, P. (2012). Anticipating ethical issues in emerging IT. Ethics and Information Technology, 14(4), 305-317.
Davison, R. M., Martinsons, M. G., & Ou, C. X. (2012). The roles of theory in canonical action research. MIS Quarterly, 36(3), 763-786.
Dewi, S. (2021). Epistemology in Information Systems research: Building knowledge between objectivity and interpretation. MEDIAISTIK Journal, 5(1), 22-35.
Dohn, N. B. (2024). Philosophical presuppositions in ‘computational thinking’—old wine in new bottles? Journal of Philosophy of Education, 58(6), 829–852.
Domingo-Ferrer, J., & Blanco-Justicia, A. (2020). Ethical value-centric cybersecurity: A method-ology based on a value graph. Science and Engineering Ethics, 26(3), 1267–1285.
Fejerskov, A. M. (2021). Algorithmic bias and the (false) promise of numbers. Global Policy, 12(S6), 101–103.
Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689-707.
Hassan, N. R. (2014). Useful philosophy for information systems. Proceedings of the International Conference on Information Systems (ICIS).
Heeks, R. (2022). Information and communication technology for development (ICT4D). Rout-ledge.
Hirschheim, R., & Klein, H. K. (2012). A glorious and not-so-short history of the information systems field. Journal of the Association for Information Systems, 13(4), 188-235.
Introna, L. D. (2016). Algorithms, governance, and governmentality: On governing in the algorith-mic society. Science, Technology, & Human Values, 41(1), 17-49.
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389-399.
Khasanah, N., & Suyanto, S. (2021). The implementation of local wisdom in the digital era. Journal of Ethnic and Cultural Studies, 8(2), 200-215.
Kousa, P., & Niemi, H. (2023). AI ethics and learning: EdTech companies’ challenges and solu-tions. Interactive Learning Environments, 31(10), 6735–6746.
Kroeze, J. H. (2011). Interpretivism in IS—A postmodern epistemology? Sprouts: Working Papers on Information Systems, 11(12), 1–19.
Mingers, J. (2004). Real-izing information systems: Critical realism as an underpinning philosophy for IS. Information and Organization, 14(2), 87–103.
Mingers, J., & Standing, C. (2017). Why things matter-the case for critical realism in IS research. European Journal of Information Systems, 26(2), 171-198.
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2).
Moor, J. H. (2006). The nature, importance, and difficulty of machine ethics. IEEE Intelligent Systems, 21(4), 18-21.
Myers, M. D., & Klein, H. K. (2011). A set of principles for conducting critical research in infor-mation systems. MIS Quarterly, 35(1), 17-36.
Nissenbaum, H. (2020). Privacy as contextual integrity. Washington Law Review, 79(1), 119-158.
Petras, V. (2024). The identity of information science. Journal of Documentation, 80(3), 579–596.
Pyrrho, M., Cambraia, L., & de Vasconcelos, V. F. (2022). Privacy and health practices in the digital age. The American Journal of Bioethics, 22(7), 50–59.
Rindfleisch, A. (2020). The ethical challenges of Artificial Intelligence. Journal of Marketing, 84(1), 22-25.
Sartika, M., & Sensuse, D. I. (2020). E-government adoption in Indonesia: A systematic literature review. Proceeding of the International Conference on Advanced Computer Science and Informa-tion Systems (ICACSIS).
Stahl, B. C. (2012). Morality, ethics, and reflection: A categorization of normative IS research. Journal of the Association for Information Systems, 13(8), 636–656.
Walsham, G. (2017). ICT4D research: reflections on history and futureagenda. Information Tech-nology for Development, 23(1), 18-41.
Wand, Y., & Weber, R. (1990). An ontological model of an information system. IEEE Transactions on Software Engineering, 16(11), 1282–1292.
Zhu, Z. (2025). Pragmatic ontology—Enhancing the philosophical foundation of critical systems thinking/practice. Systems Research and Behavioral Science, 42(1), 83–97.
Zuboff, S. (2015). Big other: surveillance capitalism and the prospects of an information civiliza-tion. Journal of Information Technology, 30(1), 75-89.















