Dr Livio Robaldo

Senior Lecturer in Computational Law, Law

+44 (0) 1792 602421

livio.robaldo@swansea.ac.uk

Available For Postgraduate Supervision

Research Links

https://orcid.org/0000-0003-4713-8990

Scopus

About

Livio Robaldo is a Senior Lecturer in Computational Law specialized in Natural Language Processing and Knowledge Representation. Livio earned his Ph.D. in Computer Science from the University of Turin in 2007. Afterwards, he worked as a PostDoc researcher at the University of Turin and the University of Luxembourg until 2020, when he got a Senior Lecturer position in Computational Law at the School of Law at Swansea University. He has authored many papers in international journals and conferences and had an active role in the writing and management of research projects in Artificial Intelligence and Law, also in collaboration with industry, among which three H2020 Marie Sklodowska-Curie projects.

Areas Of Expertise

Computational Law
Natural Language Processing
Knowledge Representation
Artificial Intelligence and Law
Natural Language Semantics
Legal Ontologies
Deontic Logic
Automatic Reasoning

Publications

Research Highlights

Robaldo, L. & Liga, D. (2023). Fine-tuning GPT-3 for legal rule classification. Computer Law & Security Review
https://doi.org/https://doi.org/10.1016/j.clsr.2023.105864, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64410
Esposito, C., Horne, R., Robaldo, L., Buelens, B., & Goesaert, E. (2023). Assessing the Solid Protocol in Relation to Security and Privacy Obligations. Information, 14(7), 411
https://doi.org/10.3390/info14070411, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63893
http://dx.doi.org/10.3390/info14070411
Robaldo, L., Pacenza, F., Zangari, J., Calegari, R., & Calimeri, F. (n.d.) Efficient compliance checking of RDF data. Journal of Logic and Computation
https://doi.org/10.1093/logcom/exad034, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63627
http://dx.doi.org/10.1093/logcom/exad034
Robaldo, L., Batsakis, S., Calegari, R., Calimeri, F., Fujita, M., Governatori, G., Morelli, M., Pacenza, F., Pisano, G., Satoh, K., Tachmazidis, I., & Zangari, J. (2023). Compliance checking on first-order knowledge with conflicting and compensatory norms: a comparison among currently available technologies. Artificial Intelligence and Law, 0
https://doi.org/10.1007/s10506-023-09360-z, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63481
http://dx.doi.org/10.1007/s10506-023-09360-z
Robaldo, L., Kober, G., & Paschke, A. (2023). Using BPMN for medical guidelines that integrate with FHIR-RDF. In Proceedings of 14th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences (SWAT4HCLS 2023)
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62317
https://ceur-ws.org/Vol-3415/paper-1.pdf

All Research

Journal Articles

Robaldo, L. & Liga, D. (2023). Fine-tuning GPT-3 for legal rule classification. Computer Law & Security Review
https://doi.org/https://doi.org/10.1016/j.clsr.2023.105864, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64410
Esposito, C., Horne, R., Robaldo, L., Buelens, B., & Goesaert, E. (2023). Assessing the Solid Protocol in Relation to Security and Privacy Obligations. Information, 14(7), 411
https://doi.org/10.3390/info14070411, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63893
http://dx.doi.org/10.3390/info14070411
Robaldo, L., Batsakis, S., Calegari, R., Calimeri, F., Fujita, M., Governatori, G., Morelli, M., Pacenza, F., Pisano, G., Satoh, K., Tachmazidis, I., & Zangari, J. (2023). Compliance checking on first-order knowledge with conflicting and compensatory norms: a comparison among currently available technologies. Artificial Intelligence and Law, 0
https://doi.org/10.1007/s10506-023-09360-z, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63481
http://dx.doi.org/10.1007/s10506-023-09360-z
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
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
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
Robaldo, L., Siragusa, G., Caro, L., & Violato, A. (2021). Textual Entailment for Cybersecurity: an Applicative Case. Journal of Applied Logics, 8(4), 975-992.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56726
https://www.collegepublications.co.uk/ifcolog/?00046
Robaldo, L., Antoniou, G., Baryannis, G., Batsakis, S., Governatori, G., Islam, M., Liu, Q., Siragusa, G., & Tachmazidis, I. (2021). Large-Scale Legal Reasoning with Rules and Databases. Journal of Applied Logics, 8(4), 911-939.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56725
https://www.collegepublications.co.uk/ifcolog/?00046
Robaldo, L., Pacenza, F., Zangari, J., Calegari, R., & Calimeri, F. (n.d.) Efficient compliance checking of RDF data. Journal of Logic and Computation
https://doi.org/10.1093/logcom/exad034, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63627
http://dx.doi.org/10.1093/logcom/exad034

Conference Contributions

Robaldo, L., Kober, G., & Paschke, A. (2023). Using BPMN for medical guidelines that integrate with FHIR-RDF. In Proceedings of 14th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences (SWAT4HCLS 2023)
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62317
https://ceur-ws.org/Vol-3415/paper-1.pdf
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/
Robaldo, L. & Adebayo, K. (2022). Compliance checking in reified IO logic via SHACL. In Fifteenth International Workshop on Juris-informatics, November 14 - 15, 2021, Keio University Kanagawa, Japan .
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58455
https://arxiv.org/abs/2110.07033
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
Amantea, I., Robaldo, L., Sulis, E., Boella, G., & Governatori, G. (2021). Semi-automated checking for regulatory compliance in e-Health. In 2021 IEEE 25th International Enterprise Distributed Object Computing Workshop (EDOCW)IEEE.
https://doi.org/10.1109/edocw52865.2021.00063, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa58454
Robaldo, L. (2021). Towards compliance checking in reified I/O logic via SHACL. In Proceedings of the Eighteenth International Conference on Artificial Intelligence and LawACM.
https://doi.org/10.1145/3462757.3466065, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56727

Edited Books

Robaldo, L., Casini, G., Torre, L., & Villata, S. (Eds.). (2022). Handbook of Legal AI. College Publications.
SU Repository: https://cronfa.swan.ac.uk/Record/cronfa62314
https://collegepublications.co.uk/handbooks/?00007

Supervision

Untitled (current)

PhD

Other supervisor: Dr Adam Wyner

Taught Modules

LAA250 Foundations in LegalTech

The module introduces key technologies, commonly referred to as `LegalTech¿, that are increasingly used in the legal industry and in the justice system, specifically to help law firms perform tasks faster and more accurately and to facilitate access to justice for citizens. The module is intended to prepare students for the key challenges arising from emerging digital technologies. The module illustrates the technical basics of key emerging technologies (e.g. machine learning, explainable AI, distributed ledger technologies etc), while addressing their pros and cons, legal and ethical challenges, risks and opportunities. The module also includes four interactive workshops in which the students will be required to present and critically analyze, together with the lecturer, an existing LegalTech application available on the market. This module does not require the students to have any specific technical background or prior knowledge of the topic.
LAA357 Foundations in LegalTech

The module introduces key technologies, commonly referred to as `LegalTech¿, that are increasingly used in the legal industry and in the justice system, specifically to help law firms perform tasks faster and more accurately and to facilitate access to justice for citizens. The module is intended to prepare students for the key challenges arising from emerging digital technologies. The module illustrates the technical basics of key emerging technologies (e.g. machine learning, explainable AI, distributed ledger technologies etc), while addressing their pros and cons, legal and ethical challenges, risks and opportunities. The module also includes four interactive workshops in which the students will be required to present and critically analyze, together with the lecturer, an existing LegalTech application available on the market. This module does not require the students to have any specific technical background or prior knowledge of the topic.
LAAM35 Artificial Intelligence and Law

The module introduces the students to AI technologies that may be concretely employed in the current LegalTech market. Special attention will be devoted to the distinction between Machine Learning technologies, based on statistical reasoning, and Semantic Web technologies, based on logical reasoning. The former represent the state of the art, as most current LegalTech solutions, both in academia and in industry, are based on them. The latter represent the future, in that they lead to human-understanding, transparency, and explainability, which has been deemed by many as desirable features of next-generation AI technologies, in particular in the legal domain. On the basis of the above distinction, the module will encourage students to critically analyze existing applications in the legal domain as well as 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. Notes:
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.

Dr Livio Robaldo

Telephone number

Email address

LinkedIn Account

Research Links

About

Areas Of Expertise

Publications

Research Highlights

All Research

Journal Articles

Conference Contributions

Edited Books

Supervision

Untitled (current)

Taught Modules

LAA250 Foundations in LegalTech

LAA357 Foundations in LegalTech

LAAM35 Artificial Intelligence and Law

LATM01 Artificial Intelligence in Commerce and Legal Practice

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