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Lecturer(s)
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Madleňáková Lucia, JUDr. Ph.D.
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Pospíšil Daniel, JUDr. Ph.D.
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Tomoszek Maxim, JUDr. Ph.D.
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Kozieł Michal, Dr. Mgr. Ph.D.
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Course content
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Lectures: 1. How large language models work and their significance for the law and lawyers: principles, limitations, hallucinations, and data traffic lights according to the UP Recommendations. 2. Prompt engineering for legal tasks: the anatomy of an effective prompt, iterative tuning, and structured prompting techniques. 3. AI-assisted legal information retrieval: integration of LLMs with verified legal sources, verification and documentation of the research process. 4. The use of AI in drafting legal documents: the boundary between AI assistance and independent legal judgment, a five-level model of the degree of AI assistance. 5. Ethics and professional responsibility in the use of AI in law: confidentiality, data protection, academic integrity, model ethical scenarios. 6. Fundamentals of digital humanism in law: the role of humans and the role of AI; design of workflows combining AI support and human judgment; current regulatory framework (AI Act), risks (AI2027). The seminars build on individual topics through hands-on work with Microsoft 365 Copilot Business and other tools on tasks derived from the students? current coursework: 1. Hands-on training in using LLMs and the UP data traffic light system 2. Creating and refining prompts using practical examples 3. Critical review of AI output; common LLM errors 4. AI-assisted legal research?practical exercises, use of various sources, source verification, and integration with legal databases 5. Discussion of model-based ethically complex situations, the limits of AI use, and a personal AI code of conduct 6. Final integrative project
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Learning activities and teaching methods
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Dialogic Lecture (Discussion, Dialog, Brainstorming), Training in job and motor Skils, Activating (Simulations, Games, Dramatization)
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Learning outcomes
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This course develops students´ability to effectively use large language models (LLMs) in the study of law and the practice of law. Students will gain practical familiarity with the principles underlying LLMs, learn to formulate effective prompts for legal tasks, systematically verify content generated by LLMs, and combine it with verified legal sources. The course also fosters the ability to critically reflect on the ethical and accountability aspects of using AI in legal studies and practice, in accordance with Palacký Universitys´ Recommendation on the Use of Artificial Intelligence Tools and the recommendations of professional organizations. Instruction takes the form of lectures focused on the theoretical and ethical framework and seminars in which students work directly with Microsoft 365 Copilot Business and other digital resources (ASPI, EUR-Lex, Beck-online) on specific application tasks. The course will help students develop their ability to study and understand the law and teach them to work more effectively and responsibly as future lawyers by utilizing available technologies.
In terms of knowledge, students will be able to describe how large language models work, including their limitations (hallucinations, limited knowledge of current and specifically Czech law, context window), explain the principles of secure data handling when working with AI tools (data traffic lights, sensitivity zones), and apply the UP Recommendations on the Use of AI in practice, including the five-level model of AI assistance for specific tasks. In terms of skills, students will be able to design and iteratively refine prompts for legal research, case law analysis, and document preparation; conduct AI-assisted legal research combining LLMs with verified legal databases (ASPI, EUR-Lex, Beck-online), and systematically verify AI-generated content, including the identification of hallucinations and factual errors. Students will be able to prepare legal documents and analyses using AI while maintaining their own legal judgment and responsibility for the final product. In terms of values, students will learn the ethical and professional rules governing responsibility for AI-generated outputs, the principle of transparency in disclosing the use of AI, and procedures ensuring compliance with confidentiality and personal data protection rules when working with digital tools. Students will develop a critical and reflective approach to technology as a prerequisite for lifelong professional development in the rapidly evolving environment of digital legal technologies.
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Prerequisites
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Enrollment in this course or its completion does not require completion of other courses. To successfully complete the course, students must have access to an institutional Microsoft 365 account within the UP environment. No legal knowledge beyond that covered in the first year of the master?s program is required.
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Assessment methods and criteria
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Student performance
The course concludes with a credit (zápočet). The requirements for successfully passing the course are: active participation in at least 5 of the 6 seminars, submission of two mid-term assignments (a prompt log and a research report documenting AI-assisted legal research on a topic of the student?s choice), and a final portfolio containing artifacts from seminar work, declarations of AI use for each assignment, and a final reflective essay.
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Recommended literature
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Doporučení k využívání nástrojů umělé inteligence na UP: Praktický průvodce pro výuku, vědu, výzkum, administrativu a podpůrné činnosti. Univerzita Palackého v Olomouci, (ai.upol.cz).
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(2024). Nařízení Evropského parlamentu a Rady (EU) 2024/1689, kterým se stanoví harmonizovaná pravidla pro umělou inteligenci (AI Act).
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Příručka CCBE k používání generativní AI advokáty.
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Stanovisko ČAK k užívání umělé inteligence (AI) při poskytování právních služeb.
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Stromberg, David and Lei, Victor and Wu, Yanhui. (2026). The Generative AI Learning Penalty: Evidence from Chinese Secondary Education (SSRN.com, June 02, 2026)..
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