Dr Livio Robaldo

Research Highlights

1. Siragusa, G. & Robaldo, L. (2022). Sentence Graph Attention for Content-Aware Summarization. Applied Sciences, 12(20), 10382

   https://doi.org/10.3390/app122010382, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa61559
2. Robaldo, L., Batsakis, S., Calegari, R., Calimeri, F., Fujita, M., Governatori, G., Morelli, M., Pisano, G., Satoh, K., & Tachmazidis, I. (2022). Taking stock of available technologies for compliance checking on first-order knowledge. In 37th Italian Conference on Computational Logic (CILC 2022)

   SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60449

   https://ceur-ws.org/Vol-3204/
3. Robaldo, L., Amantea, I., Sulis, E., Governatori, G., & Boella, G. (2022). Business Process Modelling in Healthcare and Compliance Management: A Logical Framework. Journal of Applied Logics - IfCoLog Journal, 9(4)

   SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60447

   https://www.collegepublications.co.uk/ifcolog/?00056
4. Robaldo, L., Antoniou, G., Atkinson, K., Baryannis, G., Batsakis, S., Caro, L., Governatori, G., & Siragusa, G. (2022). Explainable Reasoning with Legal Big Data: A Layered Framework. Journal of Applied Logics - IfCoLog Journal, 9(4)

   SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60445

   https://www.collegepublications.co.uk/ifcolog/?00056
5. Kober, G., Robaldo, L., & Paschke, A. (2022). Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach. In Studies in Health Technology and InformaticsIOS Press.

   https://doi.org/10.3233/shti220348, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59706

   http://dx.doi.org/10.3233/shti220348

All Research

• Untitled (current)

  PhD

  Other supervisor: Dr Adam Wyner

• LAAM35 Artificial Intelligence and Law

  The module introduces the students to IT technologies that may be concretely employed in the current LegalTech market. It provides an introduction to key elements of artificial intelligence (AI), including natural language processing (NLP) and machine learning (ML), focusing in particular on Semantic Web technologies for the legal domain, such as LegalDocML and RDF/OWL. These technologies have recently gained attention both in academia, industry, and standardization bodies. IT technologies based on semantics represent the path to explainability, which has been deemed by many as a desirable feature of next-generation AI technologies, in particular for LegalTech applications. The module also aims to encourage students to identify new use cases, which could be interesting for the current LegalTech industry and which could even set the ground for a future start-up project plan.

• LAAM37 Contemporary Issues in LegalTech

  LegalTech is revolutionising the way in which legal services are designed and delivered all around the world. New technologies are introduced at a very fast pace, with existing ones evolving rapidly in response to increased market demand. Regulators and policy-makers constantly introduce new and amended regulations to accompany the technological evolution, while courts deal with complex questions of interpretation and application of existing and new frameworks of law to legal technologies. Law firms and start-ups introduce new legal services based on LegalTech innovation, driving a transformation of the legal sector that has a profound impact on our society. This module seeks to explore the most cutting-edge issues that accompany such transformation, analysing current developments, related to the introduction of new technologies, amended or new regulations and relevant case law. It aims to contextualise such changes, providing a basis for future research, and to encourage a critical discussion on their significance and impact, predicting future trends and further developments. The module also seeks to help students develop skills that are becoming increasingly important for LegalTech professionals, for example in relation to entrepreneurship, ethics and interdisciplinarity. The module will offer a mix of different learning opportunities, with research-based lectures, practical workshops, seminars, guest lectures and talks with LegalTech professionals. This variety reflects the nature of the LegalTech field, where academic research sits alongside practical implementation, with innovation taking place in the diverse environments of law firms, start-ups, universities, legal innovation laboratories and more. The assessment offers students a chance to reflect critically on the knowledge and skills acquired throughout the year, to carry out research on a LegalTech development of interest and to communicate such research in a presentation and blog post. This will allow students to develop important professional skills, including in research and communication, helping them become well-informed, engaged and responsible LegalTech professionals.

• LAAM39 Introduction to Programming

  The module provides an introduction to programming, focusing on key concepts (variables, control structures, functions, object-oriented programming, etc.) that allow students to develop small-scale software and to understand implementations of LegalTech applications.

• LATM01 Artificial Intelligence in Commerce and Legal Practice

  Artificial Intelligence (AI) is becoming integral to the fabric of modern society and is already a staple of commercial organisations and businesses looking to enhance their productivity. It has been used for a variety of reasons, such as the reduction of financial paperwork via the electronicisation of commercial payments (that are now regularly made by computer), and increasingly for the incidence of smart contract payments automatically triggered by a payee¿s computer acting in collaboration with the debtor¿s IT systems. Where goods are ordered automatically (e.g. an industrialist¿s computer hooked up to a component supplier¿s server), they can also give rise to the formation of entirely new contracts. This module will focus on the use of AI within commercial and legal settings. It is often the case that once the technology is put in place issues will arise, such as the question of whether such technology can function within the parameters of existing legal rules. Human rights ¿ even within a commercial framework ¿ must also be considered as part of any analysis concerning the use of AI (notably, for example, the right to privacy). Overall, this module intends to provide an in-depth analysis of AI in the context of existing private legal rules while also exploring its role in society, what legal frameworks need to be developed.

• LATM02 Distributed Ledger Technology (Blockchain) and Commerce - Law and Regulation

  Distributed ledger technology (DLT) is an integral part of the emerging digital transformation taking place within commercial and financial industries. It has the potential to dramatically alter the way businesses operate, providing improved efficiency of current client requirements and opening doors for new services. In simple terms, DLT is a database that is distributed across several independent computing devices (nodes) where changes to data are protected and managed by cryptography and consensus ensuring that data cannot tampered with and that all parties have identical copies that can be considered as a reliable source of truth. This module intends to analyse the legal position of those employing such ledgers in the context of their businesses. To appreciate the potential legal problems emerging, the applications of such ledgers in different areas of commercial law (finance, insurance, shipping) will be studied. The module will then discuss whether any change in private law rules is required to ensure that such ledgers do not create unexpected consequences for relevant parties. Regulators are also actively exploring the need to regulate the use of such ledgers. Regulation is rather challenging in this area due to potential jurisdictional problems, and overly strict regulation could potentially reduce the commercial values of such ledgers. These issues, along with others, will be discussed as part of this module.