http://nlp.unibo.it/tag/project/ProjectHugo Blox Builder (https://hugoblox.com)en-usFri, 23 Jan 2026 00:00:00 +0000http://nlp.unibo.it/media/icon_hu_7613a4a452ac7087.pnghttp://nlp.unibo.it/tag/project/http://nlp.unibo.it/news/equal/Fri, 23 Jan 2026 00:00:00 +0000http://nlp.unibo.it/news/equal/<h2 id="project-info">Project info</h2> <p>The EquAl project addresses algorithmic evaluations, decisions, and predictions, to promote fairness and counter discrimination affecting individuals and groups. The research project fundedis by the EU Commission under the NextGenerationEU program and the Italian Ministry of Education, University and Research. (PRIN 2022. Ref. prot. n.: 2022KFLF3E-001 - CUP J53D23005560001).</p> <h2 id="useful-links">Useful Links</h2> <ul> <li><a href="https://site.unibo.it/equal/en/equal_project" target="_blank" rel="noopener">Project Page</a></li> <li><a href="program.pdf">Workshop Program</a></li> <li><a href="reproducibility-crysis.pdf">Federico Ruggeri&rsquo;s Speech</a></li> </ul>http://nlp.unibo.it/news/prima/Mon, 12 Jan 2026 00:00:00 +0000http://nlp.unibo.it/news/prima/<h2 id="project-info">Project info</h2> <p>PRIMA (PRivacy Infringements Machine-Advice) studies the law and practice of privacy policies, develops methods and techniques for their automated analysis, and implements a prototype to assess their lawfulness. It deploys legal analytics—a mix of data science, artificial intelligence, machine learning, natural language processing and statistics—to detect and assess privacy policies’ infringements.</p> <h2 id="useful-links">Useful Links</h2> <ul> <li><a href="https://site.unibo.it/prima/en/project" target="_blank" rel="noopener">Project Page</a></li> <li><a href="program.pdf">Workshop Program</a></li> <li><a href="explainability-via-highlights.pdf">Federico Ruggeri&rsquo;s Speech</a></li> </ul>http://nlp.unibo.it/projects_international/poline/Wed, 01 Jan 2025 00:00:00 +0000http://nlp.unibo.it/projects_international/poline/<p>POLINE aims at developing an AI-powered pilot tool for the retrieval and analysis of judicial principles of law in the CJEU and national case-law in Value Added Tax (VAT). The tool relies on AI techniques for extracting, clustering and linking judicial principles of law and is embedded in a modular platform, consisting of a Legal Database, Link Visualization and Customised Detection Module. It covers the case-law of the CJEU and the Italian, Swedish and Bulgarian Supreme Courts and will be accessible to judges, other legal practitioners, tax policymakers and taxpayers. The development of the tool will be based on a multidisciplinary approach combining theory and practice of judicial decision-making for the study of the concept of “judicial principle of law” and the analysis of the case-law; legal informatics methods for the creation of an ontology of judicial concepts in VAT and training datasets of annotated judicial principles of law; AI, machine learning, and NLP techniques for the automatic extraction of principles, the detection of textual and semantic similarity, and network analysis. The tool will be trialled in 3 online national testing events and disseminated in 3 national demonstration events and 1 final international conference. The pilot tool provides a robust and trustworthy use case of AI technologies for justice. It will provide non-discriminatory and effective access to justice. Through its collection of principles of law and NLP-powered search engine, the tool will assist judges in accessing legal knowledge reducing their work overload. Moreover, through the Customised Detection Test Module, the tool will allow recipients of VAT measures to identify judicial principles of law applied in a specific case and assess whether VAT law is correctly applied. By developing open-access automated techniques of knowledge extraction, the methods developed can be easily reused and expanded to include other fields of law and other legal systems.</p>http://nlp.unibo.it/projects_national/smartcasm/Mon, 01 Jan 2024 00:00:00 +0000http://nlp.unibo.it/projects_national/smartcasm/<p>The project involves using LLMs to integrate unstructured knowledge into industrial pipelines to speed up production and foster technical advancement.</p>http://nlp.unibo.it/projects_international/fair/Mon, 01 Jan 2024 00:00:00 +0000http://nlp.unibo.it/projects_international/fair/<p>The objective of the FAIR project is to contribute facing the research questions, methodologies, models, technologies, and ethical and legal rules to build AI systems capable of interacting and collaborating with humans, perceiving and acting in evolving contexts, to be conscious about their limits and capable to adapt to new situations, to be aware of the perimeters of safety and trust, and to be careful with the environmental and social impact that their creation and functioning may cause.</p>http://nlp.unibo.it/projects_national/gemeb/Mon, 01 Jan 2024 00:00:00 +0000http://nlp.unibo.it/projects_national/gemeb/<p>The project developing ad-hoc LLM-based solutions to speed up existing user assistance systems while guaranteeing privacy.</p>http://nlp.unibo.it/projects_national/prima/Mon, 01 Jan 2024 00:00:00 +0000http://nlp.unibo.it/projects_national/prima/<p>PRIMA (PRivacy Infringements Machine-Advice) studies the law and practice of privacy policies, develops methods and techniques for their automated analysis, and implements a prototype to assess their lawfulness.</p>http://nlp.unibo.it/projects_national/alma-gaie/Mon, 01 Jan 2024 00:00:00 +0000http://nlp.unibo.it/projects_national/alma-gaie/<p>&#x1f3c6; The project received the <a href="https://magazine.unibo.it/en/articles/artificial-intelligence-for-sustainable-pa-alma-gaie-wins-first-place" target="_blank" rel="noopener">“PA a colori” 2024 award</a> for sustainability in public administrations.</p> <p>A project funded by the University of Bologna aiming to develop an AI system for the automatic classification of research and educational products of the University of Bologna according to their contribution to the 17 Goals of the United Nations&rsquo; 2030 Agenda for Sustainable Development.</p>http://nlp.unibo.it/projects_international/ai4eu/Sun, 01 Jan 2023 00:00:00 +0000http://nlp.unibo.it/projects_international/ai4eu/<p>The EU-funded AI4EU is working to change Europe’s place in this race, by building the first European AI On-Demand Platform and Ecosystem that will share resources, tools, knowledge, algorithms and more between Member States. It will help to increase innovation and technology transfer, accelerate the growth of start-ups and SMEs, and fulfill the needs of the European AI community. The project will implement eight pilots led by industrial partners to demonstrate the platform’s capabilities.</p>http://nlp.unibo.it/projects_national/equal/Sat, 01 Jan 2022 00:00:00 +0000http://nlp.unibo.it/projects_national/equal/<p>The EquAl project addresses algorithmic evaluations, decisions, and predictions, to promote fairness and counter discrimination affecting individuals and groups. The research project fundedis by the EU Commission under the NextGenerationEU program and the Italian Ministry of Education, University and Research. (PRIN 2022. Ref. prot. n.: 2022KFLF3E-001 - CUP J53D23005560001) EquAl aims (i) to provide an understanding of the concepts of algorithmic unfairness and discrimination, bridging the notions adopted in social sciences, law, statistics, and artificial intelligence. (ii) To identify the ways in which algorithmic unfairness originates and spreads in different social contexts, affecting individuals and groups, and particularly to identify the cases in which algorithmic unfairness leads to prohibited discrimination. (iii) To analyse the ways in which the law currently addresses algorithmic discrimination and propose appropriate measures to implement or upgrade the existing regulatory framework. (iv) To examine the way in which technologies can promote fairness and support detecting and countering algorithmic unfairness and discrimination, in particular with regard to the assessment of asylum requests. By identifying and remedying algorithmic unfairness and discrimination, EquAl will contribute to preventing and mitigating harms to individuals and groups and favour the law-abiding deployment of AI. EquAl is premised on the fast-growing application of AI techniques for the purposes of prediction, evaluation, and decision making. Algorithmic approaches have the potential to transform many aspects of the economic and social life, delivering cost effective solutions, increasing the equity, efficiency, controllability and precision of decision-making processes. However, they may also lead to new and more subtle, opaque, and resilient forms of unfairness and discrimination. Some discriminatory effects have been already addressed by case-law in Europe and beyond, and some proposals exist to regulate aspects of automated decision-making, but no comprehensive regulatory framework exists yet. EquAl aims to place Italian legal research at the forefront in the domain of algorithmic fairness and non-discrimination, by: (a) delivering new insights on the specific nature, functioning, and evolution of fair and unfair instances of algorithmic decision-making; (b) evaluating existing anti-discrimination technologies and developing new methods to detect instances of unfairness in human and automated decisions and protect vulnerable individuals; (c) providing ethical and legal guidance and (d) supporting public bodies, NGOs and local communities, in particular, in the examination of asylum applications. EquAl’s contribution is crucial to enhance interdisciplinary cross-fertilisation, since currently different criteria and terminologies are used in debating algorithmic fairness and non-discrimination by different research communities (legal scholars, sociologists, computer scientists, statisticians), and to ensure that the corpus of EU and Italian anti-discrimination law, regulations, and case-law can be effectively applied in the algorithmic domain.</p>http://nlp.unibo.it/projects_national/laila/Sat, 01 Jan 2022 00:00:00 +0000http://nlp.unibo.it/projects_national/laila/<p>The project regards the application of Legal Analytics methods to a vast and heterogeneous set of legal information: legislations, contracts, and judgments. The purpose is the application of Artificial Intelligence, Machine Learning, and Natural Language Processing to extract legal knowledge, infer relationships, and produce data-driven forecasts.</p>http://nlp.unibo.it/projects_international/stairwai/Sat, 01 Jan 2022 00:00:00 +0000http://nlp.unibo.it/projects_international/stairwai/<p>The StairwAI project targets low-tech users with the goal of facilitating their engagement on the AI4EU on-demand Platform. This will be achieved through a new service layer enriching the functionalities of the on-demand platform and containing: (1) a multi-lingual interaction layer enabling conversations with the Platform in the user’s own language, (2) a horizontal matchmaking service for the automatic discovery of AI assets (tools, data sets, AI experts, consultants, papers, courses etc.) meeting the user business needs and, (3) a vertical matchmaking service that will dimension and provision hardware resources through a proper hardware provider (HPC, Cloud and Edge infrastructures).</p>http://nlp.unibo.it/projects_international/adele/Fri, 01 Jan 2021 00:00:00 +0000http://nlp.unibo.it/projects_international/adele/<p>Project ADELE is premised on the ongoing paradigm shift towards cognitive computing and human-centered AI which is transforming many socio-economic activities, including justice. The project applies legal analytics (LA) – a blend of data science, machine learning, and natural language processing techniques – to judicial decisions. It aims to develop methods to extract knowledge and engage in outcome predictions and there build a pilot tool to support legal research and decision-making processes in the judiciary.</p>http://nlp.unibo.it/projects_national/amica/Fri, 01 Jan 2021 00:00:00 +0000http://nlp.unibo.it/projects_national/amica/<p>The objective of the AMICA project was to exploit the argumentative content present in the scientific literature regarding Covid-19 to improve the retrieval of relevant and reliable articles. The project involved both medical and artificial intelligence experts and aimed to develop an argument mining-based search engine, specifically designed for the analysis of scientific literature related to Covid-19.</p>http://nlp.unibo.it/projects_international/humane-ai/Fri, 01 Jan 2021 00:00:00 +0000http://nlp.unibo.it/projects_international/humane-ai/<p>Facilitating a European brand of trustworthy, ethical AI that enhances Human capabilities and empowers citizens and society to effectively deal with the challenges of an interconnected globalized world. Funded by the European Commission under H2020, ICT-48. The University of Bologna participates with 4 departments: Computer Science and Engineering, Mathematics, Biomedical and Neuromotor Sciences, and Political and Social Sciences. We coordinate the Humane-AI-Net activities for the University of Bologna and work on several projects: the micro-project Ethical Chatbots, the micro-project Promoting Fairness and Diversity in Speech Datasets for Affective Computing, the micro-project A Transparent and Explainable Dialogue System for Immigration Services, the macro-project &ldquo;Learning with LLMs: Supporting complex reasons, planning &amp; argumentation applied to provide educational guidance&rdquo;.</p>http://nlp.unibo.it/projects_international/claudette/Sun, 01 Jan 2017 00:00:00 +0000http://nlp.unibo.it/projects_international/claudette/<p>CLAUDETTE is an interdisciplinary research project hosted at the Law Department of the European University Institute. The research objective is to test to what extent is it possible to automate reading and legal assessment of online consumer contracts and privacy policies, to evaluate their compliance with EU’s unfair contractual terms law and personal data protection law (GDPR), using machine learning and grammar-based approaches.</p>