Alvarado-Acuña, Luis Segundo
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Alvarado-Acuña
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Luis Segundo
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lualvar@ucn.cl
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Publicación Decision Making in Artificial Intelligence Training Programs(Springer Nature, 2025-03-25) Yzquierdo-Herrera, Raykenler; Piñero-Pérez, Pedro Yobanis; Pérez-Pupo, Iliana; Alvarado-Acuña, Luis Segundo; García-Vacacela, Roberto; Hernández-Pupo, Luis GabrielThis 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.Publicación Framework for Strategic Planning and Assisted by Artificial Intelligence(Springer Nature, 2025-03-25) Alvarado-Acuña, Luis Segundo; Piñero-Pérez, Pedro Yobanis; Yzquierdo-Herrera, Raykenler; Piñero-Ramírez, Carlos Manuel; López-Correa, Francisco Javier; García-Vacacela, RobertoStrategic forecasting continues to be one of the fundamental elements in decision making. This branch of management sciences, like other branches of knowledge, is being influenced by artificial intelligence and other emerging technologies. In this work, in the first section of the methods section, a brief study is made of the state of the art of trends in strategic planning and the points of contact with artificial intelligence. The opportunities for improvement of existing strategic forecasting techniques with respect to the treatment of uncertainty are analyzed. In the second section, a proposal is made for a framewrok for strategic planning assisted by artificial intelligence techniques. This model allows aiding decision making while maintaining an adequate management of information uncertainty. Then, in the results analysis session, the proposals made are validated. Statistical techniques and expert and data triangulation methods are used. As conclusions, the validity of the proposal and its power for decision making under uncertainty is demonstrated. Future lines of work are also presented.