Despite the indisputable benefits that Artificial Intelligence (AI) can bring in society and in any industrial activity, humans typically have little insight about AI itself and even less concerning the knowledge on how AI systems make any decisions or predictions due to the so-called “black-box effect”.
Many of the machine learning/deep learning algorithms are opaque and not possible to be examined after their execution to understand how and why a decision has been made. In this context, to increase trust in AI systems, XMANAI aims at rendering humans (especially business experts from the manufacturing domain) capable of fully understanding how decisions have been reached and what has influenced them.
Building on the latest AI advancements and technological breakthroughs, XMANAI shall focus its research activities on Explainable AI (XAI) in order to make the AI models, step-by-step understandable and actionable at multiple layers (data-model-results).
XMANAI aims to design, develop and deploy a novel Explainable AI Platform powered by explainable AI models that inspire trust, augment human cognition and solve concrete manufacturing problems with value-based explanations. Adopting the mentality that “AI systems should think like humans, act like humans, think rationally, and act rationally”.
