95082 - Artificial Intelligence, Law and Society

Learning outcomes

The student will acquire the following competences and skills: - awareness of the information and communication technologies (ICTs) and of their socio-economical impacts - awareness of main issues pertaining to the regulation of ICTS - knowledge of emerging aspects of European ICT Law - awareness the basic principles and issues on e-goverment, e-governance and e-democracy - knowledge of the legal regulation of ICTs in the Europe - awareness the Digital Agenda for Europe framework. The student will acquire the awareness of risks and opportunities of ICTs and the ability to address legal issues pertaining to ICTs in a European and comparative perspective.

Course contents

• For students attending the course (frequentanti), the detailed course content corresponds to the list of readings and materials with the possibility of replacing some contents with new topics discussed during the lectures.
• For students not attending the course (non frequentanti) the detailed course content corresponds to the Handbook “Artificial Intelligence and Legal Analytics” (Ashley 2017), Cambridge University Press.

Erasmus students follow the same programme of italian students.

For students coming from other degree courses, that have already passed an exam of Legal Informatics, the course contents for possible integration shall be agreed with the professor.

The course is divided into two parts: Computable Law; Legal issues of AI and autonomous systems.

Computable Law:

Introduction to computable law: the enablers; main approaches and methods

Legal retrieval systems (all different systems and approaches): introduction to legal information retrieval, new trends, case studies

Man-made models (man-made ontologies, norms, rules, case based reasoning, argumentation): legal knowledge representation (logic, ontology and computation); case studies

Machine learning systems: introduction to big data and the law, legal text analytics; case studies

Legal issues of AI and autonomous systems:

Legal issues of AI: Big data, Algorithmic decision making, algorithmic justice: predictive systems and the issues of fairness and transparency, data protection

Legal issues of autonomous systems: automation in socio-technical systems; liability and automation; task-responsibility, main kinds of involved liabilities: personal liability, enterprises liabilities, product liability, liability of standard setters. Cases studies: aviation, autonomous driving, health care, robot, autonomous agents.

Readings/Bibliography

For students not attending the course:

Kevin D. Ashley, Artificial Intelligence and Legal Analytics (2017) Cambridge University Press

Teaching methods

Lectures are held by Prof. Lagioia and Prof. Contissa with the support of collaborators.

We warmly invite students to actively participate in the lectures and discuss with teachers and other students news and events, related to the topics of the course.

During the course the students will have a chance to attend different conferences held by professors and professional lawyers on the topics of this course.

In accordance with the health emergency from Covid-19, teaching will be carried out following the traditional method of lectures.

Further information are available at the following Internet address: https://dsg.unibo.it/en/teaching/projects-and-teaching-methodologies

The exam can only be taken after having passed the exams of Constitutional Law and Private Law.

Assessment methods

The exam, consisting of a group activity and an oral test, both of which are compulsory, will take place as follows:

1) Group activity: Students are required to form groups of max 3/4 students. Each group chooses a topic from the list below. [The list of topics will be defined during the course]

Each group must:

• choose a paper/topic from the list that will be made available on Virtuale
• write a brief description (max 1000 characters) about the tentative proposal
• communicate the topic, group members' names, abstract (1000 characters) to francesca.lagioia@unibo.it to be sent by 17 October 2024
• prepare a short paper (max 10 pages) and deliver a presentation

This will be useful to arrange the scheduling of group presentations that will be published on the course webpage.

In order to maintain a good variety in the scheduling and only in the case several groups submit similar proposals, we may ask to change the object of the presentation.

IMPORTANT: each group will prepare a presentation of the proposal and every student in the group must present part of it for at least 4/5 minutes. This activity will be evaluated, and we will assign a score to it, expressed in /30.

2) Oral test: students who have passed the group activity (min 18/30) can take the oral test. The test will take place on Microsoft Teams.

The oral test consists of two or three questions that may cover the entire content of the course.

In the oral test, the student starts with the grade obtained in the group activity, to which a maximum of 3 points may be added, and it may also lead to reducing the grade from the group activity.

*** Information for BAES students ***

The AI, Law and Society course for BAES programme students consists of the following topics (argumenti on Virtuale):

• Argomento 5: AI, Influence and Manipulation
• Argomento 6: AI and the GDPR

• Argomento 8: Liability and Automation

• Argomento 11: Fairness in Automated Decisions

  Readings:

• Introduction to Machine Learning
• Lagioia, Rovatti, Sartor, “Algorithmic fairness through group parities? The case of COMPAS‐SAPMOC” (2022)
• EP study, “The impact of the General Data Protection Regulation (GDPR) on artificial intelligence”
• Contissa, “Automation and Liability: an analysis in the context of socio-technical systems” (2017)

Exam rules for BAES students

The exam will be an oral test consisting of three questions related to the selected topics and readings above.

 

 

 

 

Office hours

See the website of Francesca Lagioia

See the website of Giuseppe Contissa