B9770 - SEM. ARTIFICIAL INTELLIGENCE AND CRIMINAL JUSTICE

Learning outcomes

This seminar will explore the challenges posed by artificial intelligence (AI) to the realm of criminal justice. Specifically, it will focus on whether AI poses specific issues to the attribution of criminal liability and whether we can talk of an accountability and/or liability gap (who should be blamed when an AI system goes wrong?). The students will have the opportunity to reflect on classical notions of criminal liability and assess whether they can be applied to such technology. The seminar will also touch upon the most recent European and international legislative efforts (e.g., the AI act) on this topic and give students the tools to analyze them critically.

Course contents

1. Artificial intelligence and criminal liability: gaps and challenges

2. Artificial intelligence and criminal liability: case studies

Readings/Bibliography

- Alexander Sarch & Ryan Abbott, Punishing Artificial Intelligence: Legal Fiction or Science Fiction, UC Davis Law Review 53:323-384 (2019);

- Alice Giannini, Artificial Intelligence, Criminal Liability for, Encyclopedia of the Philosophy of Law and Social Philosophy (2023); ⁠⁠

- Gabriel Hallevy, ‘The Criminal Liability of Artificial Intelligence Entities - from Science Fiction to Legal Social Control’, Akron Intellectual Property Journal: Vol. 4 : Iss. 2 , Article 1 (2010);

- Sabine Gleß, Emily Silverman and Thomas Weigend, ‘If Robots Cause Harm, Who Is to Blame? Self-Driving Cars and Criminal Liability’, New Criminal Law Review 19 no. 3 (2019);

- Susanne Beck, ‘Intelligent agents and criminal law—Negligence, diffusion of liability and electronic personhood’, Robotics and Autonomous Systems’, Volume 86, Pages 138-143(2016);

- Ying Hu, ‘Robot Criminals’, 52 U. Mich. J. L. Reform 487 (2019).

Teaching methods

The seminar will be held in two parts: in the first part, some general aspects and challenges of attributing criminal liability when AI is involved will be addressed. In the second part, the seminar will focus on case studies, such as current legislation addressing AI and criminal liability and real-life cases involving AI and criminal law.

Students are expected to come prepared to the lectures and will be involved in an interactive and open discussion. They will be provided with readings in advance to prepare for the lectures.

Assessment methods

An evaluation will be made at the end of the seminar based on participation and comments during the discussions.

Office hours

See the website of Emanuela Fronza