5 found
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  1. The Ethical Knob: Ethically-Customisable Automated Vehicles and the Law.Giuseppe Contissa, Francesca Lagioia & Giovanni Sartor - 2017 - Artificial Intelligence and Law 25 (3):365-378.
    Accidents involving autonomous vehicles raise difficult ethical dilemmas and legal issues. It has been argued that self-driving cars should be programmed to kill, that is, they should be equipped with pre-programmed approaches to the choice of what lives to sacrifice when losses are inevitable. Here we shall explore a different approach, namely, giving the user/passenger the task of deciding what ethical approach should be taken by AVs in unavoidable accident scenarios. We thus assume that AVs are equipped with what we (...)
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    AI Systems Under Criminal Law: a Legal Analysis and a Regulatory Perspective.Francesca Lagioia & Giovanni Sartor - 2020 - Philosophy and Technology 33 (3):433-465.
    Criminal liability for acts committed by AI systems has recently become a hot legal topic. This paper includes three different contributions. The first contribution is an analysis of the extent to which an AI system can satisfy the requirements for criminal liability: accomplishing an actus reus, having the corresponding mens rea, possessing the cognitive capacities needed for responsibility. The second contribution is a discussion of criminal activity accomplished by an AI entity, with reference to a recent case involving an online (...)
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    CLAUDETTE: An Automated Detector of Potentially Unfair Clauses in Online Terms of Service.Marco Lippi, Przemysław Pałka, Giuseppe Contissa, Francesca Lagioia, Hans-Wolfgang Micklitz, Giovanni Sartor & Paolo Torroni - 2019 - Artificial Intelligence and Law 27 (2):117-139.
    Terms of service of on-line platforms too often contain clauses that are potentially unfair to the consumer. We present an experimental study where machine learning is employed to automatically detect such potentially unfair clauses. Results show that the proposed system could provide a valuable tool for lawyers and consumers alike.
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    Detecting and explaining unfairness in consumer contracts through memory networks.Federico Ruggeri, Francesca Lagioia, Marco Lippi & Paolo Torroni - 2022 - Artificial Intelligence and Law 30 (1):59-92.
    Recent work has demonstrated how data-driven AI methods can leverage consumer protection by supporting the automated analysis of legal documents. However, a shortcoming of data-driven approaches is poor explainability. We posit that in this domain useful explanations of classifier outcomes can be provided by resorting to legal rationales. We thus consider several configurations of memory-augmented neural networks where rationales are given a special role in the modeling of context knowledge. Our results show that rationales not only contribute to improve the (...)
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    Algorithmic Fairness Through Group Parities? The Case of COMPAS-SAPMOC.Francesca Lagioia, Riccardo Rovatti & Giovanni Sartor - forthcoming - AI and Society.
    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 of group-parity criteria as fairness standards. To this end, we evaluate the use of machine learning methods relative to different steps of the decision-making process: assigning a predictive score, linking a classification to the score, and adopting decisions based on the (...)
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