Title:
Learning from World Wide Human-AI Social Interactions
Speaker: Stefano Melacci | University of Siena
Abstract:
The technologies most profoundly influencing contemporary society are based on the Web, on the social networks, and on Artificial Intelligence (AI). While these systems have considerably expanded human capacities for communication and knowledge exchange, they have simultaneously undermined privacy, concentrated control within a few dominant entities, and imposed substantial energy demands. The coexistence of humans and AI remains uncertain and largely unregulated, introducing risks that extend beyond strictly technological domains. This keynote advocates for a fundamental re-examination of these paradigms, grounded in the principles of privacy preservation, energy efficiency, and distributed system design, as promoted by Collectionless AI (collectionless.ai). Intelligence is relocated from centralized cloud infrastructures to edge devices endowed with increasing local computational capabilities, while retaining integrative information-sharing dynamics and learning over time. A major assumption is that of re-organizing the Web around communities that are called “Worlds.” They are autonomous ecosystems of agents that function as societies organized around shared goals, topics, or intents. Within these Worlds, agents learn, reason, and plan not only to advance individual objectives but also in response to collective constraints, operating through a peer-to-peer communication protocol. This vision is instantiated in UNaIVERSE, a platform designed to enable decentralized AI and human-AI coexistence, with privacy as a foundational design principle (https://unaiverse.io/). Use cases that illustrate how this paradigm may transform problem formulation and solution methodologies in decentralized intelligent systems are shown, thereby fostering and supporting novel research activities
Stefano Melacci | University of Siena
Bio:
Stefano Melacci is an Associate Professor of the Department of Information Engineering and Mathematics (DIISM), University of Siena (Italy), whose research activity is focussed on the field of Artificial Intelligence with emphasis on Machine Learning, mainly using Neural Networks. Prof. Melacci studies Machine Learning problems in which the machine processes data streams and interactions, from which it is expected to continuously learn to model its behavior in making predictions (Lifelong Learning, Learning Over Time), as well as approaches to integrate symbolic knowledge and neural models (Neural-Symbolic Learning & Reasoning). Prof. Melacci obtained his PhD in 2010 from the University of Siena, in addition to the Master’s Degree in Computer Engineering (cum Laude), on research topics involving Machine Learning. He was a Visiting PhD Student at the Ohio State University, Columbus, OH, USA, and he actively collaborated with the French startup CogniTalk for the design of Conversational Human-Machine Interfaces. He worked for the Italian company QuestIT for three years, conducting research aimed at developing automatic language processing technologies. Prof. Melacci is a member of the Siena Artificial Intelligence Lab (SAILab), co-author of the book “Machine Learning: A constraint-based approach” (MK, 2023, second edition). He was Associate Editor for the scientific journal IEEE Transactions on Neural Networks and Learning Systems for six years (2017-2022), and he is a member of the board of the National PhD Program in Artificial Intelligence for Society. He was the Program Chair of the International Conference on Lifelong Learning (CoLLAs, https://lifelong-ml.cc/Conferences/2024) 2024 and the main organizer of the Spring School on “Learning Over Time” (LOT, Siena, 2025, https://collectionless.ai/school). He is the co-author of the “Collectionless AI” perspective (https://collectionless.ai), and co-founder/chairman of the board of the innovative startup UNaIVERSE (https://unaiverse.ai).