This ENIA Chair in AI and sustainability is dedicated to the development of hybrid or physics-informed artificial intelligence techniques for the achievement of sustainable development objectives in industrial production. New disruptive artificial intelligence methodologies will be developed to ensure the sustainability of the product in its entire life cycle, from design and manufacturing to the operational phase and predictive maintenance.
SustAInable revolves around three fundamental concepts that articulate sustainability in the life cycle of all productive activity and that will constitute the axes of the research and training activity of this chair: smart design, smart manufacturing and smart monitoring (smart design, smart manufacturing, smart sensing). The three lines are focused on achieving increased intelligence designed to enable informed decision-making based on ethical, reliable and robust criteria.
SustAInable proposes to develop a new generation of physics-informed hybrid artificial intelligence techniques that will enable substantial progress in terms of
- AI Sustainability
- AI Efficiency
- AI Reliability
- AI Ethics
- Human-Centric AI
SustAInable will therefore develop the disruptive concept of hybrid AI, which will unite data-driven models with those based on well-established physical laws. The hybrid paradigm allows for a reduction in the volume of data used, while achieving a substantial approach to reliable AI by ensuring that physical laws are adhered to in predictions. Depending on the application, hybrid AI can be the decision-maker, with humans acting as supervisors of the AI, or, conversely, humans can be the decision-maker, with hybrid AI assisting in the decision-making process.