A5084837357- Multi-Agent Systems and Negotiation
- Artificial Intelligence in Law
- Logic, Reasoning, and Knowledge
- Law, Economics, and Judicial Systems
- Semantic Web and Ontologies
- Ethics and Social Impacts of AI
- Dispute Resolution and Class Actions
- Legal Language and Interpretation
- Law, AI, and Intellectual Property
- Privacy, Security, and Data Protection
- Comparative and International Law Studies
- Legal processes and jurisprudence
- Law in Society and Culture
- Judicial and Constitutional Studies
- Digitalization, Law, and Regulation
- Legal Education and Practice Innovations
- European and International Contract Law
- Legal principles and applications
- Philosophical Ethics and Theory
- European Criminal Justice and Data Protection
- Legal and Labor Studies
- Auction Theory and Applications
- Free Will and Agency
- Political Philosophy and Ethics
- Classical Philosophy and Thought
University of Bologna
2015-2025
European University Institute
2016-2025
University of Łódź
2020-2021
Instytut Nauk Prawnych
2021
Max Planck Institute for Comparative Public Law and International Law
2021
Polish Academy of Sciences
2021
University of Modena and Reggio Emilia
2020
Zambon (Italy)
2010-2018
University of Windsor
2014
Universidade do Estado do Rio de Janeiro
2010
ABSTRACT Inspired by legal reasoning, this paper presents a semantics and proof theory of system for defeasible argumentation. Arguments are expressed in logic-programming language with both weak strong negation, conflicts between arguments decided the help priorities on rules. An important feature is that these not fixed, but themselves defeasibly derived as conclusions within system. Thus debates choice conflicting can also be modelled. The given fixpoint definition, while its stated...
We propose a computationally oriented non-monotonic multi-modal logic arising from the combination of temporalised agency and normative positions. argue about defeasible nature these notions then we show how to represent reason with them in setting Defeasible Logic.
This report contains preliminary results of the study aiming at automating legal evaluation privacy policies, under GDPR, using artificial intelligence (machine learning), in order to empower civil society representing interests consumers. We outline what requirements a GDPR-complaint policy should meet (comprehensive information, clear language, fair processing), as well are ways which these documents can be unlawful (if required information is insufficient, language unclear, or potentially...
This article's main contributions are twofold: 1) to demonstrate how apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice domain of healthcare and 2) investigate research question what does "trustworthy AI" mean at time COVID-19 pandemic. To this end, we present results a post-hoc self-assessment evaluate trustworthiness an system predicting multiregional score conveying degree lung compromise patients, developed verified by...
Abstract Machine learning classifiers are increasingly used to inform, or even make, decisions significantly affecting human lives. Fairness concerns have spawned a number of contributions aimed at both identifying and addressing unfairness in algorithmic decision-making. This paper critically discusses the adoption group-parity criteria (e.g., demographic parity, equality opportunity, treatment equality) as fairness standards. To this end, we evaluate use machine methods relative different...
ABSTRACT The Artificial Intelligence Act (AIA) relies on public authorities to survey and monitor the compliance systems of private companies establish appropriate discovery mechanisms render ex-officio enforcement possible. article analyses intricacies AIA interaction between authorities, thus preventing marketing AI that are dangerous both people society. striking complexity structure invites us consider use in enforcement. Such areas are: handling communication hundreds competent national...