Decision Making in Artificial Intelligence Training Programs

Herrera, Raykenler Yzquierdo; Pérez, Pedro Yobanis Piñero; Pupo, Iliana Pérez; Acuña, Luis Alvarado; García Vacacela, Roberto; Pupo, Luis Gabriel Hernández

Abstract

This work addresses the challenge of capacity building in the areas of artificial intelligence and data science. It starts by recognizing the need for new academic programs that consider these subjects as central themes. To develop researchers skilled in topics such as computational intelligence, decision-making in uncertain environments, generative artificial intelligence, and other trends in the development of new AI technologies in society, an ethical approach is required. In the methods section, the proposal addresses the fundamental challenges related to these topics and provides a brief analysis of the state of the art. Additionally, a training strategy is proposed, ranging from short-cycle programs to postgraduate education. The proposal includes a short-cycle program for a Data Science Technician, an Artificial Intelligence Engineering degree, and a master’s degree in Artificial Intelligence. In this way, the training is provided at various levels, accompanied by a strategy for continuous education. In the results analysis section, the proposal was evaluated by a group of specialists in curriculum design, yielding positive results. Finally, the conclusions focus on the fair and ethical development of artificial intelligence. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Más información

Título según SCOPUS: Decision Making in Artificial Intelligence Training Programs
Título de la Revista: Studies in Computational Intelligence
Volumen: 1195
Editorial: Springer Science and Business Media Deutschland GmbH
Fecha de publicación: 2025
Página de inicio: 183
Página final: 211
Idioma: English
DOI:

10.1007/978-3-031-83643-5_6

Notas: SCOPUS