Program Overview

ARTIFICIAL INTELLIGENCE, CIVIL PROCEDURE, AND LEGAL PROFESSION

Overview

New technologies are significantly changing human epistemic strategies. The use of IT filters to manage information overload is becoming increasingly frequent, with terms like Algorithms, Artificial Intelligence, and Big Data being commonly used. This course aims to analyze the possible impact of new technologies, particularly Artificial Intelligence, on civil procedure and the role of lawyers. It will also examine the procedural aspects of the EU Regulation on Artificial Intelligence (AI ACT).

Aims and Content

Learning Outcomes

The course focuses on the analysis of basic concepts of Artificial Intelligence, machine learning, and predictive algorithms, and their possible applications in civil procedure, along with related implications for legal ethics.

Aims and Learning Outcomes

Through attendance and active participation in proposed activities and individual study, students will be able to:

• Know the basic concepts of Artificial Intelligence, machine learning, predictive algorithms, and Big Data, also in view of the EU AI ACT Regulation.
• Understand the possible applications of Artificial Intelligence to the civil process, including hints at its applications to Legal Design, blockchain, and smart contracts.
• Recognize the current applications of machine learning in the US discovery phase.
• Analyze the main technical, ethical, and deontological problems related to the use of artificial intelligence in civil procedure.
• Identify the possible transformations of the role of the lawyer resulting from the use of Artificial Intelligence.

Teaching Methods

The course will consist of frontal lessons, with strong recommendations for students' active participation in classrooms. Students with valid certifications for Specific Learning Disabilities (DSA), disabilities, or other special educational needs are invited to contact the instructor and the School/Department's disability coordinator at the beginning of the course to agree on personalized teaching arrangements.

Syllabus/Content

The course is divided into three parts:

1. The first part analyzes the basic concepts of Artificial Intelligence, machine learning, predictive algorithms, and Big Data.
2. The second part examines the current (and possible future) application of Artificial Intelligence to civil proceedings, with particular reference to Technology Assisted Review of documents used in the US discovery.
3. The third part analyzes some of the main technical, ethical, and deontological problems raised by the application of Artificial Intelligence to civil proceedings, with particular attention to the EU AI Act.

Recommended Reading/Bibliography

• Nieva-Fenoll, Intelligenza artificiale e processo, Torino, 2019, 1-143.
• Recommended readings include:
  • Comoglio, Nuove tecnologie e disponibilità della prova, Torino, 2018, 283-364.
  • Santosuosso, Sartor, Decidere con l'IA. Intelligenze artificiali e naturali nel diritto, Bologna, 2024.

Teachers and Exam Board

• Professor: Paolo Comoglio.
• Exam Board:
  • Paolo Comoglio (President).
  • Vincenzo Ansanello.
  • Enrico Righetti (Substitute).

Lessons

• Lessons Start: The start date of the classes can be found on the university's website.
• Class Schedule: The timetable for this course is available on the Portale EasyAcademy.

Exams

• Exam Description: Oral examination.
• Assessment Methods: The oral examination aims to verify that candidates have a homogeneous and critical preparation on all modules of the course. Attendance and active participation in lessons will be considered for the final evaluation.
• Exam Schedule:
  • 17/12/2025, 11:00, GENOVA, Orale.
  • 14/01/2026, 11:00, GENOVA, Orale.
  • 03/02/2026, 11:00, GENOVA, Orale.
  • 20/05/2026, 11:00, GENOVA, Orale.
  • 10/06/2026, 11:00, GENOVA, Orale.
  • 01/07/2026, 11:00, GENOVA, Orale.
  • 15/07/2026, 11:00, GENOVA, Orale.
  • 09/09/2026, 11:00, GENOVA, Orale.

Further Information

For other information not included in the teaching schedule, students are advised to ask the professor.

Agenda 2030 - Sustainable Development Goals

This course contributes to:

• Quality education.
• Gender equality.