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030060 KU Artificial Intelligence and medical law (2022S)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 07.02.2022 00:01 to Mo 21.02.2022 23:59
- Deregistration possible until Mo 14.03.2022 23:59
Details
max. 30 participants
Language: German
Lecturers
Classes (iCal) - next class is marked with N
14.03.2022: Preliminary discussion and assignment of the presentation topics
11.05.2022: Introduction to the technical and legal basics
13.-15.06.2022: Presentation and discussion sessions
- Monday 14.03. 09:00 - 11:00 Seminarraum SEM63 Schottenbastei 10-16, Juridicum 6.OG (Kickoff Class)
- Wednesday 11.05. 10:00 - 13:00 Seminarraum SEM34 Schottenbastei 10-16, Juridicum, 3.OG
- Monday 13.06. 09:00 - 15:00 Seminarraum SEM61 Schottenbastei 10-16, Juridicum 6.OG
- Tuesday 14.06. 09:00 - 15:00 Seminarraum SEM61 Schottenbastei 10-16, Juridicum 6.OG
- Wednesday 15.06. 09:00 - 15:00 Seminarraum SEM61 Schottenbastei 10-16, Juridicum 6.OG
Information
Aims, contents and method of the course
Overview of the legal issues (e.g. data protection law, fundamental rights, professional law, liability law) arising from the use of artificial intelligence in medicine (e.g. diagnosis, drug research, chatbots). After an introduction to the technical and legal basics by the lecturers, the students give presentations on selected issues and prepare a thesis paper. The problems will be discussed together.
Assessment and permitted materials
Oral presentation on a selected topic.
Preparation of a thesis paper on the presentation.
Active participation in the discussion of the presentations.
Preparation of a thesis paper on the presentation.
Active participation in the discussion of the presentations.
Minimum requirements and assessment criteria
50% presentation, 30% thesis paper, 20% participation. For a positive assessment, the presentation must be held and positively evaluated.
Examination topics
Delivery of an oral presentation + preparation of a thesis paper + active participation in the discussion sessions.
Reading list
General: Topol, Deep Medicine (2019).Legal introduction: Paar/Stöger, Medizinische KI - Die rechtlichen "Brennpunkte", in Fritz/Tomaschek (Hrsg), Konnektivität (2021) 85; Schneeberger/Stöger/Holzinger, The European Legal Framework for Medical AI, in Holzinger ea (Hrsg), Machine Learning and Knowledge Extraction (2020) 209; Schönberger, Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications, International Journal of Law and Information Technology 2019, 171; Stöger/Schneeberger/Holzinger, Medical artificial intelligence: the European legal perspective, Communications of the ACM 11/2021, 34.Technical introduction: Alpaydin, Machine Learning. The New AI (2. Edition 2021); Burgstaller/Hermann/Lampesberger, Künstliche Intelligenz. Technisches und rechtliches Grundwissen (2019); Domingos, The Master Algorithm (2015); Kelleher, Deep Learning (2019); Lehr/Ohm, Playing with the Data:
What Legal Scholars Should Learn About Machine Learning, UCDL Rev 2017, 653, https://lawreview.law.ucdavis.edu/issues/51/2/Symposium/51-2_Lehr_Ohm.pdf
What Legal Scholars Should Learn About Machine Learning, UCDL Rev 2017, 653, https://lawreview.law.ucdavis.edu/issues/51/2/Symposium/51-2_Lehr_Ohm.pdf
Association in the course directory
Last modified: We 30.03.2022 11:27