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Lecturer(s)
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Tomoszek Maxim, JUDr. Ph.D.
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Bartoň Michal, doc. JUDr. Ph.D.
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Course content
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- Legal regulation of artificial intelligence in a comparative perspective - Artificial intelligence and fundamental human rights and freedoms, ethical issues of artificial intelligence - issues of legal liability of artificial intelligence
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Learning activities and teaching methods
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Monologic Lecture(Interpretation, Training), Dialogic Lecture (Discussion, Dialog, Brainstorming)
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Learning outcomes
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Digital technologies offer a wide range of opportunities to develop legal literacy. The Street-law method of legal education, which is widespread around the world, consists in providing information about law to non-lawyers by law school students, on the one hand fulfils the third role of the university and, on the other hand, develops a number of competences relevant for professional development and future employment, such as problem solving, effective communication, competences for lifelong learning, the ability to communicate clearly about law with lay people, etc. In the Street-law project course, students will first get acquainted with the Street-law method and its basic principles in direct teaching, then they will work on their own semester-long project focused on strengthening legal literacy using modern information technologies, targeting a selected marginalized group within the framework of project- and practice-oriented teaching with service-learning elements. They will present this project to the course supervisor and other students during the course and then implement it practically.
Introducing students to the Street-law method. Ability to work with elements of service-learning using modern information technologies, targeting selected marginalized groups, ability to present and implement own project using these elements.
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Prerequisites
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Completion of this course is not conditional on completion of other courses
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Assessment methods and criteria
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Student performance
Active student participation in lectures and written essays is required. Full-time students must attend at least 80% of the lectures, while combined students must attend 50% of the lectures and one individual consultation.
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Recommended literature
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BECKERS, A., TEUBNER, G. (2023). Three Liability Regimes for Artificial Intelligence - Algorithmic Actants, Hybrids, Crowds. Hart Publishing.
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CUSTERS, B., FOSCH-VILLARONGA, E., (eds.). (2022). Law and Artificial Intelligence. T.M.C. Asser Press.
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DIMATTEO, A., L., PONCIB?, Ch., CANNARSA, M., (eds.). (2022). The Cambridge Handbook of Artificial Intelligence - Global Perspectives on Law and Ethics. Cambridge University Press.
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DUBBER, D., M., PASQUALE, F., DAS, S., (eds.). (2021). Oxford Handbook of Ethics of AI. Oxford University Press.
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KERRIGAN, CH. (2022). Artificial Intelligence: Law and Regulation. Edward Elgar Publishing.
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LEGG, M., BELL, F. (2020). Artificial Intelligence and the Legal Profession. Hart Publishing.
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YEUNG, K., LODGE, M., (eds.). (2019). Algorithmic Regulation. Oxford University Press.
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