Recruitment procedure for Transfrom4Europe BA Tracks 2024/2025 at the University of Silesia in Katowice

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Artificial Intelligence and Law

Details
Code W5-LA-S2-WM-AI
Organizational unit Faculty of Law and Administration
Form of studies Full-time
Level of education First cycle
Language(s) of instruction English
Admission limit 25
Duration classes will start in the summer semester
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General data

syllabus

group instructor

dr Dominika Iwan-Sojka

ECTS credit allocation

3 ECTS

Type of class

 Lecture/Seminar, 24 hours

Course mode

online

Language

  English

 

List of topics

  1. AI-related terms and concepts, applications across industries and states,
  2. Ethics of AI – how far should we trust technology?
  3. International law on AI,
  4. European Union law on AI,
  5. Decentralised regulation of AI,
  6. Discriminatory algorithms,
  7. Data protection law,
  8. Cybersecurity,
  9. AI on trial,
  10. Weaponising AI,
  11. AI systems - A need for regulation?

 

Bibliography

1. M. Legg, F. Bell, Artificial Intelligence and the Legal Profession (Hart Publishing 2020).

2. A.M. Turing, "Computing machinery and intelligence", [1950] LIX Mind. A Quarterly Review of Psychology and Philosophy 236.

3. S. Newell, M. Marabelli, "Strategic opportunities (and cahllenges) of algorithmic decision making: A call for action on the long-term societal effects of datification", [2015] Journal of Strategic Information Systems 24.

4. R. Penrose, The Emperor's New Mind (OUP 2016).

 

Assessment methods and assessment criteria

The student is required to prepare and present a project on the given aspect of Artificial Intelligence’s impact on the law. Projects are prepared and presented by a group of 3-4 students and each of them is required to establish their input on the project (formal requirement). Merits of the project constitute a substantive requirement for final evaluation. Final positive evaluation requires positive evaluation in both formal and substantive requirements.

While presenting their project, students need to demonstrate they have learnt the indicated scope of knowledge on AI and law.

Teaching methods

  • Independent analysis of reading material and critical evaluation of discussed matters,
  • researching additional data,
  • arguments and possible answers to the problems.