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Safeguarding Knowledge: Ethical Artificial Intelligence Governance in the University Digital Transformation

Safeguarding Knowledge: Ethical Artificial Intelligence Governance in the University Digital Transformation
Rafael Molina-Carmona (Universidad de Alicante) and Francisco José García-Peñalvo (Universidad de Salamanca)
In: Vendrell Vidal, E., Cukierman, U.R., Auer, M.E. (eds)
Advanced Technologies and the University of the Future
Lecture Notes in Networks and Systems, vol 1140.
Springer, Cham
https://link.springer.com/book/10.1007/978-3-031-71530-3


Acceso al pdf: https://doi.org/10.1007/978-3-031-71530-3_14

Abstract
Higher Education Institutions (HEIs) safeguard knowledge, uphold academic integrity, and contribute to societal progress. They are custodians of knowledge, promoting innovation, addressing societal challenges, and disseminating research ethically. With the rise of Artificial Intelligence (AI), effective gover- nance becomes crucial to ensure responsible use, protect rights, and foster inno- vation in HEIs. A proposal for a governance framework for AI in Higher Education is presented, designed to be simple, tailored to universities, and easily integrated into existing digital transformation efforts. Specific goals include examining AI’s impact, evaluating governance models, suggesting adaptable principles, and defining a framework that balances innovation, ethics, and regulatory compliance. It takes into account that AI in higher education reshapes teaching, research, and administration, and makes emphasis on ethical deployment and observation of the national and international policies and regulations. The proposal sets out four fundamental principles for AI in universities to be applied to every phase of knowledge generation: the principles of legality, neutrality, transparency, and promotion of innovation. As a consequence, the AI Governance Grid is obtained, that allows the identification of 12 key aspects to consider in order to ensure that the governance proposal complies with the principles. A structure for AI Governance is also proposed so that it is efficient and also takes advantage of the expertise that universities already have, as well as being in line with the international standards for IT Governance. Finally, a set of best practices for AI governance is also proposed that aims to provide practical guidance for simple implementation.