The legislative process is the backbone of a state built on solid institutions. Yet, due to the complexity of laws -- particularly tax law -- policies may lead to inequality and social tensions. In this study, we introduce a novel prototype system designed to address the issues of tax loopholes and tax avoidance. Our hybrid solution integrates a natural language interface with a domain-specific language tailored for planning. We demonstrate on a case study how tax loopholes and avoidance schemes can be exposed. We conclude that our prototype can help enhance social welfare by systematically identifying and addressing tax gaps stemming from loopholes.

We shift this perspective with the Privatech project to focus on corporations and law firms as agents of compliance. To comply with data protection laws, data processors must implement accountability measures to assess and document compliance in relation to both privacy documents and privacy practices. In this paper, we survey, on the one hand, current research on GDPR automation, and on the other hand, the operational challenges corporations face to comply with GDPR, and that may benefit from new forms of automation. We attempt to bridge the gap. We provide a roadmap for compliance assessment and generation by identifying compliance issues, breaking them down into tasks that can be addressed through machine learning and automation, and providing notes about related developments in the Privatech project.

Both [1, 11] suggests "the ease of in the legal domain. We extract legal indicators from judicial access to information" is a solution to address the gap in accessing judgments to decrease the asymmetry of information of the legal justice. Access to free basic legal information could help the user system and the access-to-justice gap. We use NLP methods to extract to navigate the justice system easily, understand better the legal interesting entities/data from judgments to construct networks area his problem falls into, and choose a lawyer with experience of lawyers and judgments. We propose metrics to rank lawyers on the subject matter of the dispute. In our work, we extract and based on their experience, wins/loss ratio and their importance in represent information from past judgments to increase the transparency the network of lawyers. We also perform community detection in of judicial procedures and make them more accessible to the network of judgments and propose metrics to represent the laypersons.