Algorithmic Norms

The scientific problem

Despite the advancements in electronic judicial proceedings, the Judiciary faces a critical paradox: digitalization has not eliminated delays; it has merely transferred them to the digital environment. Today, systems operate predominantly as document repositories, lacking an intelligent comprehension of legal content. Current operating systems fail to address core issues related to: 1) Natural Language: legal texts are replete with ambiguities, contradictions, and critical nuances that remain unperceived by current systems; 2) Clerical Automation: the technological infrastructure requires clear signals to act, without which systems remain entirely dependent on court staff, who consume most of their time performing repetitive tasks. This disconnect generates noise within the judicial system: repetitive manual tasks, triage errors, and a layer of digital bureaucracy that must be purged from the Judicial System. In the electronic process, technical infrastructures, automated workflows, and algorithmic classifications cease to be mere auxiliary instruments and begin to organize institutional operations: they modulate time, priority, and visibility, while enhancing the coordination of procedural acts, leading to greater judicial cognitive domain. This normative layer does not present itself as statutory law or a judicial decision, yet it produces concrete effects on adjudication, clerical activities, and the governance of the justice system. The scientific problem lies in understanding how these normativities emerge and operate, and how they can be diagnosed and governed without rupturing procedural guarantees or the operative closure of the Law. Through second-order algorithmic norms, a new proposal for an effective solution to routine back-office challenges is presented, reaching a new level of efficiency and development for electronic Justice (e-Justice).