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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS HUK 2072 ARTIFICIAL INTELLIGENCE AND LEGAL RESPONSIBILITY ELECTIVE 2 0 0 4

Offered By

Law

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR SERDAR NART

Offered to

Law

Course Objective

The aim of the course is to comprehend the place of artificial intelligence in the law of liability and to determine the liability for damages that may arise as a result of the act of artificial intelligence.

Learning Outcomes of the Course Unit

1   To be able to define artificial intelligence and its implications in our law 2   To be able to comprehend artificial intelligence applications 3   To be able to establish a connection between artificial intelligence and liability law 4   To be able to determine the liability arising from the acts of artificial intelligence in terms of private law 5   To be able to master international regulations on the responsibility of artificial intelligence

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 1. Definition of artificial intelligence 2 2. Types of artificial intelligence 3 3. Artificial intelligence applications 4 4. Elements of artificial intelligence 5 5. The place of artificial intelligence in liability law 6 6. Liability of AI under contracts 7 7. Liability of artificial intelligence in tort 8 8. The perfect responsibility of artificial intelligence 9 9. AI liability under product liability 10 10. Vicarious liability of artificial intelligence 11 11. Insurance in AI liability 12 12. Other aspects of legal liability of artificial intelligence 13 Exam 14 14. Artificial intelligence regulations in EU law 15 15.Evaluation of doctrinal views on the legal liability of artificial intelligence

Recomended or Required Reading

Bozkurt Yüksel, Armağan Ebru. Robot Hukuku. Istanbul: Aristo Yayınevi, 1. Bası, 2020. Bozkurt Yüksel, Armağan Ebru. Yapay Zeka Endüstri 4.0 Ve Robot Üreticiler-Hukuki Bakış. Istanbul: Aristo Yayınevi, 2019. Ersoy, Çağlar. Robotlar, Yapay Zeka ve Hukuk. 4. Baskı Istanbul: On Iki Levha Yayıncılık. 2019. Kaynak Balta, Büşra. Eser Kavramı Ve Yapay Zeka Ürünleri. Ankara: Seçkin Yayınları, 1. Baskı, Şubat 2021.

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 MTE MIDTERM EXAM 3 FCG FINAL COURSE GRADE 4 FCG FINAL COURSE GRADE roundKPU + FN,0 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) roundKPU + BUT,0

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

maydogdu1970@gmail.com

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 2 28 Preparations before/after weekly lectures 14 2 28 Preparation for midterm exam 1 24 24 Preparation for final exam 1 25 25 Final 1 2 2 Midterm 1 1 1 TOTAL WORKLOAD (hours) 108

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 PO.14 PO.15 LO.1 1 1 1 1 1 1 1 1 1 1 1 1 1 LO.2 1 1 1 1 1 1 1 1 1 1 1 1 LO.3 1 1 1 1 1 1 1 1 1 1 1 1 1 LO.4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 LO.5 1 1 1 1 1 1 1 1 1 1 1 1 1 1