La ricerca di un modello per la regolare le nuove tecnologie

While algorithms are often perceived as objective and efficient tools, free from the biases and limitations of human action, they are inherently embedded with political choices at every stage of their design and implementation. Algorithms cannot be understood as isolated technical tools extracted from their societal and cultural contexts of development and 'growth'; analyzing them as self-contained entities overlooks the broader systems of thought, finance, politics, infrastructure, institutions, and interpersonal relationships that shape their creation and use." To effectively grasp, regulate, and redirect the so-called "algorithmic factor," it is crucial to develop a shared semantics that accounts for the culturally and socially embedded relationships between automated systems and individuals. Against this backdrop, we propose a tripartite hermeneutic paradigm—the Algorithmic Social System (SSA)—which disarticulates this "socio-technical construct" into three interacting factors: (1) data, (2) code, and (3) people. By examining the dynamic interplay among these factors, the model provides a lens to explore the power dynamics emerging from the computational porosity between human cognition and machine learning, as well as between private communication and data infrastructure. As an analytical prism, the SSA model offers a comprehensive framework for understanding the transformative relationships among technological artifacts, legal systems, and discourses. Analyzing how these three factors interconnect and reinforce one another is crucial to redirect the diffusional character of AI systems toward collective knowledge production rather than data extractivism.