Keynote: Learning from World Wide Human-AI Social Interactions

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.