Can the Law be converted into programming code using AI/ML/LLM and logic formulas without losing legal theory principles, legal linguistic expressivity, Democratic and Constitutional principles? Can a whole Legal System be managed digitally by using knowledge Graphs, Semantic Web techniques, Legal ontologies, AI? Can the translation be made automatically executable using Smart Contracts and immediately enforceable? How does the digitalization of the Law simple, transparent, and accountable for the citizens? Can Legal Design help in this task of communication?
This project aims to answer these questions using interdisciplinary instruments from philosophy of law, constitutional law, legal informatics, including AI&Law, computational linguistics, computer science, HCI, and Legal design. We use Hybrid AI to mitigate the weakness of symbolic AI in semantics.
The project is organised in 5 main sub-projects of research.
1. Analyse post-reductionism/textualism/normativism of philosophy of law in infosphere
Legal text serialization is only one of the multiple representations of the legal normative content (e.g. oral, picture). The Law is a complex set of ingredients: law-making process, legal actions, legal speech acts (e.g. text), political nuances (e.g. intention of the legislator), cultural elements, linguistic implicit concepts (e.g. new terms), different signifieds (e.g. interpretation), logic formula (e.g. commands). We investigate the theoretical relationship between normative statements, textual provisions, logic formula, non-linguistic formats (e.g. icons), programming coding of legal rules with the aim to define, and model, objectivity and subjectivity, explicit and implicit, linguistic and non-linguistic in relation of Legal Sources (e.g. Official Gazette).
2. Include Legal Hermeneutic in eLegislation
We use a new approach based on the interactive dialogue between software applications (text and code) to include the legal interpretation theory in the digital transformation of legal sources, especially in the GenAI era. We implement the explicability of the AI (Guidotti) by relying on argumentation theory to inject interpretation values into the computable system (Sartor, Prakken, Governatori, Rotolo, Boella, van der Torre, van Engers). Computer science techniques like XML, LOD, AI & Law, Legal reasoning, LLM/ML, Knowledge Graph, NLP, HCI and XR Interactive Systems, help to model a framework where to include flexibility of interpretation to prevent the crystallisation of the law in rigid coding.
3. Integrate Legal language role in normativism with computational linguistics models
There is a dense debate on the language of law (Oppenheim, Hart, Bobbio, Ross, Scarpelli, Olivecrona, Conte, Kalinowski, Wróblewski, Marmor, Schauer) and how an abstract statement (norm) is transformed in textual proposition (speech acts) and how it evolves (e.g. interpretation), and finally how logic language can model it formally. We involve computational linguists and semiotic experts working with philosophers of law to investigate the proxy role of the legal language in normative and prescriptive action.
4. Define Constitutional legitimacy of the digital legal sources and its e-enforceability
We investigate the constitutional and parliamentary law perspective (Lupo, Pollicino) in case we support the thesis that the coding law is a legitimate, authentic, and official Legal Source (Official Gazette). It is also important to understand the enforceability of the consumable-Law and whether DLT technology (e.g. smart contract) permits to implement automatic enforceability (e-enforceability).
5. Implement Better Regulation with Legal Design
We investigate which simplification forms we can adopt to visualize the machine-consumable law in a human-consumable manner for implementing simplification, better regulation principles, transparency, and accessibility. Visualization is another form of translation of the legal, so we understand which Human-Computer-Interaction instruments we can use to implement the Legal Design principles and preserve the normative message.