MV926K Artificial Intelligence in Legal Practice

Faculty of Law
Autumn 2023
Extent and Intensity
0/1/0. 3 credit(s). Type of Completion: k (colloquium).
Teacher(s)
Mgr. Tereza Novotná, Ph.D. (seminar tutor)
JUDr. Mgr. Jakub Harašta, Ph.D. (assistant)
Guaranteed by
prof. JUDr. Radim Polčák, Ph.D.
Institute of Law and Technology – Faculty of Law
Contact Person: Tereza Buchalová
Supplier department: Institute of Law and Technology – Faculty of Law
Timetable of Seminar Groups
MV926K/01: Mon 2. 10. to Fri 22. 12. each odd Tuesday 12:00–13:40 020, T. Novotná
MV926K/02: Mon 2. 10. to Fri 22. 12. each even Tuesday 18:00–19:40 020, T. Novotná
Prerequisites (in Czech)
! MV926Zk Calcul. in Law
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 40 student(s).
Current registration and enrolment status: enrolled: 30/40, only registered: 0/40
fields of study / plans the course is directly associated with
  • Law (programme PrF, PR_)
  • Law (programme PrF, M-PPV)
Course objectives
In this course, students will be introduced to current state-of-the-art technologies used to algorithmize law and process legal information. This will include tools for converting legal text into its logical representation (legal formalization and automatic reasoning) and generative tools based on large language machine learning models (GPT models, generative pre-trained transformers).
The aim of the course is to familiarize students with these technologies and how they work. The motivation to use the tools in practical law and the risks and limits of such use will be emphasized. The majority of the course will focus on practical demonstration and gaining experience in the independent use of tools based on the selected technologies.
Learning outcomes
After completing this course, students will understand the principles of operation, possibilities and risks of using algorithmic and generative technologies in practical law, with an emphasis on machine learning-based technologies and prospective generative technologies such as GPT. Through practical examples and case demonstrations, students will learn the basic skills for using these technologies to solve practical legal problems.
Syllabus
  • 1. Introductory lesson - introduction of technologies (including their differences) and discussion of how and why they are used in law, or what is their potential or risk for use in law
  • 2. Legal formalization and automatic reasoning I. - theoretical basis and functioning
  • 3. Legal formalisation and automatic reasoning II. - practical use of tools and working with them
  • 4. Large Language Machine Learning Models (GPT) I. - theoretical basis and functioning
  • 5. Large Language Machine Learning Models (GPT) II - practical use of models and working with them
  • 6. Final lesson - presentation and discussion of assignments
Teaching methods
Practically oriented seminars supported by an interactive curriculum. Individual work on a case using the chosen method and presentation at the final seminar.
Assessment methods
Students will be assessed on the basis of active participation in class and the work of practical cases and their presentation in the final class.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2024.
  • Enrolment Statistics (Autumn 2023, recent)
  • Permalink: https://is.muni.cz/course/law/autumn2023/MV926K