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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS HUK 4109 TECHNOLOGY AND CRIMINAL LAW ELECTIVE 2 0 0 4

Offered By

Law

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR PINAR BACAKSIZ

Offered to

Law

Course Objective

The aim of this course is to discuss the effect of new technological developments and how criminal law might change in the future.

Learning Outcomes of the Course Unit

1   To be able to use fundamental technological concepts 2   To be able to absorb the relationship between AI, robotics and ethics 3   To be able to discuss the criminal law problems that may arise in the areas where artificial intelligence is used 4   To be able to discuss the criminal procedure law problems that may arise in the areas where artificial intelligence is used 5   To be able to discuss the regulations in comparative law

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction Robots Used in Production Lines and Criminal Liability 2 Technological Concepts Use of Artificial Intelligence in Criminal Procedure 3 Technological Concepts Developments in Comparative Law 4 International Documents Discussion of Current Developments 5 International Documents 6 Legal personality debates on artificial intelligence and robots 7 Robots Used in the Medine and Criminal Liability 8 Autonomous Vehicles and Criminal Liability 9 Unmanned Aerial Vehicles and Criminal Law 10 Intellectual Property Law and Artificial Intelligence

Recomended or Required Reading

Bacaksız Pınar/Sümer Seda Yağmur, Robotlar, Yapay Zeka ve Ceza Hukuku, Adalet Yayınevi, Ankara 2021 Kangal Zeynel, Yapay Zeka ve Ceza Hukuku, On Iki Levha Yayıncılık, Istanbul 2021

Planned Learning Activities and Teaching Methods

The course will be conducted with theoretical explanations and case discussions.

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)

pinarbacaksiz@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 13 2 26 Preparation for midterm exam 1 16 16 Preparation for final exam 1 29 29 Final 1 2 2 Midterm 1 1 1 TOTAL WORKLOAD (hours) 102

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 LO.2 1 1 1 LO.3 1 1 1 1 1 1 LO.4 1 1 LO.5 1 1 1 1