Authors:
Esperança Amengual-Alcover
1
;
Antoni Jaume-i-Capó
1
;
Miquel Miró-Nicolau
1
;
Gabriel Moyà-Alcover
1
and
Antonia Paniza-Fullana
2
Affiliations:
1
Department of Mathematics and Computer Science, University of the Balearic Islands, Ctra. de Valldemossa, Km. 7.5, 07122 - Palma de Mallorca, Spain
;
2
Department of Private Law, University of the Balearic Islands, Ctra. de Valldemossa, Km. 7.5, 07122 - Palma de Mallorca, Spain
Keyword(s):
Explainable Artificial Intelligence (XAI), Explainability, Health and Well-Being, XAI Evaluation Measurements, Evaluation Framework.
Abstract:
The integration of Artificial Intelligence in the development of computer systems presents a new challenge: make intelligent systems explainable to humans. This is especially vital in the field of health and well-being, where transparency in decision support systems enables healthcare professionals to understand and trust automated decisions and predictions. To address this need, tools are required to guide the development of explainable AI systems. In this paper, we introduce an evaluation framework designed to support the development of explainable AI systems for health and well-being. Additionally, we present a case study that illustrates the application of the framework in practice. We believe that our framework can serve as a valuable tool not only for developing explainable AI systems in healthcare but also for any AI system that has a significant impact on individuals.