This workshop aims to explore crucial issues raised by contemporary computational models and methods in AI. The focus will be on fostering discussions about the epistemological, ontological, and formal considerations, as well as the societal implications of AI systems. Key questions to be addressed include: What epistemological criteria should we use to evaluate current AI methods, such as machine learning and deep learning? What are the main components of an AI system, and what are its primary relationships with the humans or groups it interacts with? How can we represent these elements effectively? What role can logic play in investigating new AI-based technologies? Additionally, we will examine how these conceptual tools might help mitigate bias and manage risks in sensitive fields where AI is deployed.
Speakers
Christian J. Feldbacher-Escamilla (University of Cologne)
Roberta Ferrario (Laboratory for Applied Ontology – CNR)
Ekaterina Kubyshkina (University of Milan)
Catia Pesquita (University of Lisbon)
Giuseppe Primiero (University of Milan)
Camilla Quaresmini (Politecnico di Milano)