Trustworthy and Collaborative
Human-Centric Intelligence

As AI systems transition from isolated tools to active collaborators, the "Human-Centric" paradigm becomes essential. This evolution demands a fundamental shift in how we manage trust, privacy, and alignment. Current centralized models often fail to respect user agency or provide sufficient transparency in heterogeneous environments.

This session explores the convergence of Distributed Intelligence, Blockchain-based Trust, and Robust Perception. We aim to foster research on architectures that allow secure collaboration without exposing raw data, and explainable systems that truly align machine reasoning with human intent. We invite contributions addressing both theoretical foundations and real-world industrial or healthcare applications.