David Tapia Pino is an Electronic Engineer specialised in clascic control, as well as in reinforcement learning and explainable artificial intelligence. He received his Bachelor’s and Master’s degrees from the Universidad Técnica Federico Santa María, in Chile, where his thesis consisted in evaluating preference based reinforcement learning algorithms. In recent years, he has become increasingly interested in applying his explainable artificial intelligence knowledge to problems with real-world impacts, such as AI-related projects in medicine and, currently, the world of predictive maintenance and renewable energies, especially wind energy. He aims to contribute his knowledge of explainable AI in order to harness the power of these tools without having to introduce a black box into these critical processes.