Abstract
Higher Education stakeholders, particularly academic institutions and faculty members, face a difficult and consequential choice regarding their approach to Foundation Models-based Artificial Intelligence. Initial reactions to the challenges it poses to long-standing academic traditions (“the death of the essay”) are often of a “contain/reject/forbid” nature. There are, however, sound arguments advocating for a more nuanced approach, combining preventive measures where appropriate with gradual and cautious embrace of its undeniable potential in nearly all facets of Higher Education.
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Acknowledgements
This work has been supported by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M20), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation.
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Duran-Heras, A., Reina, K., Arbáizar, J.P. (2024). Foundation Models-Based Artificial Intelligence in Universities: Alternative Approaches and Application Areas. In: Bautista-Valhondo, J., Mateo-Doll, M., Lusa, A., Pastor-Moreno, R. (eds) Proceedings of the 17th International Conference on Industrial Engineering and Industrial Management (ICIEIM) – XXVII Congreso de Ingeniería de Organización (CIO2023). CIO 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 206. Springer, Cham. https://doi.org/10.1007/978-3-031-57996-7_66
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DOI: https://doi.org/10.1007/978-3-031-57996-7_66
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