MATHEMATICS (TURKISH, PHD)
PhD TR-NQF-HE: Level 8 QF-EHEA: Third Cycle EQF-LLL: Level 8

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
LAW3018 Artificial Intelligence and Law Fall 0 2 1 4
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: En
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Hybrid
Course Coordinator : Dr. Öğr. Üyesi MEHMET SİNAN ALTUNÇ
Course Objectives: The aim of this course is to teach the relationship between artificial intelligence (AI) and law, especially to law and engineering students. Students will learn basic artificial intelligence approaches and how they are applied. Students approach AI in society and designing society with AI, learning algorithms and discrimination arising in this context, ethical discussions, basic legal rights, privacy discussions, regulations expected to be created by the use of AI in autonomous and health applications, evaluation of the intellectual property in the age of AI. They will learn about the relationship between cybersecurity and law conceptually. In addition, a discussion environment will be created by examining sample cases. Sometimes national and international guests from various disciplines will be invited to the lecture to reinforce learning.

Learning Outputs

The students who have succeeded in this course;
Understanding the achievements of artificial intelligence from the past to the present, its usage areas, the relationship between artificial intelligence and law and creating a future perspective
Understanding and applying basic artificial intelligence approaches, working principles, needs and the points of application
Understanding the impact and ethical dimension of artificial intelligence technologies on society and social life.
Understanding the concepts of artificial intelligence, big data and privacy, and their legal evaluation.
Understanding global legal regulations in autonomous driving, health and other challenging areas.
Understanding the concept of cyber security and legal approaches.
Application of interdisciplinary and multidisciplinary work in the field of artificial intelligence and law.

Course Content

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction, Getting Acquainted, Speaking on Course Contents
2) Introduction to Artificial Intelligence and Law - Historical Process and Artificial Intelligence Concepts - Artificial Intelligence Usage Areas - The Relationship Between Artificial Intelligence and Law
3) Artificial Intelligence and Society - Cultural and Sociological Approach to Artificial Intelligence - Designing Society For / With Artificial Intelligence
4) Learning Algorithms and Ethics -Needs of artificial intelligence algorithms: Data, Hardware, Communication - Ethics by Design, Ethics by Default -Profiling and Automatic Decision Making - Misleading applications such as Deepfake -Reliable Artificial Intelligence and EU Approach
5) Challenges and Gaps in Artificial Intelligence in Law a. Artificial Intelligence in the Context of Fundamental Rights - Human Rights, Artificial Intelligence and Democracy - Artificial Intelligence Systems, Data and Bias - Reliable and Explained Artificial Intelligence Concepts
6) b. Privacy Discussions - Artificial Intelligence Systems and Personal Data - Privacy in Personalization, IoT and Artificial Intelligence applications - Workplace Practices and Uses in the Public Domain
7) c. Personality and Legal Liability -Philosophy vs Law -Discussions on Personality and Legal Perspective in Artificial Intelligence -Contract and Tort Responsibility in Artificial Intelligence
8) d. Artificial Intelligence and Criminal Law-1 - Artificial Intelligence and Criminal Liability - The Element of Will in Artificial Intelligence: Intent-Possible Intent-Negligence Discussions - Adversarial Machine Learning Methods and Artificial Intelligence as an Offensive Weapon
9) e. Artificial Intelligence and Criminal Law-2 - Criminal Justice and Yapay Zeka - The Usage of AI in the Law Enforcement Activities - Profilling and ADM in the Law Enforcement Justice
10) f. Autonomous Driving: The Regulation Challenge Artificial intelligence technologies for autonomous driving: Computer vision, Reinforcement learning, sensor technologies - Discussions: Advantages and Risks - Case Study.
11) g. Automation in Healthcare - Artificial intelligence usage areas and approaches in the field of health -Personal Care Robots For Consumers Use of Robotic Technology and Responsibility for Healthcare Professionals
12) h. Intellectual Property in the Age of Artificial Intelligence - Generative artificial intelligence approaches and usage areas - Intellectual Property Right of Artificial Intelligence or Developer? - What Do International Organizations Say? -Possible Developments and Possible Solutions
13) i. Cyber security - The Concept of Cyber Security and ""Managing Cyber Space"" The Role of Artificial Intelligence in the Context of Cyber Security and Cyber Diplomacy -Regulation and Cyber Security: Tough Law and Soft Law Tools of TR, EU and NATO
14) Paper presentations

Sources

Course Notes: 1. Makale: Ronald Leenes - Laws on Robots, Laws by Robots, Laws in Robots: Regulating Robot Behaviour by Design 2. Rapor: European Parliament - European Civil Law Rules in Robotics 3. Rapor: ICO - Big data, artificial intelligence, machine learning and data protection 4. Makale: Sophia Duff & Jamie Hopkins - Sit, Stay, Drive: The Future of Autonomous Car Liability 5. Rapor: European Commision - AI and IP Report 6. Kitap: Yapay Zekâ Geçmişi Geleceği, Nils Nilsson 7. Kitap: 50 Soruda Yapay Zeka, Cem Say 8. Kitap: Derin Öğrenme, Ian Goodfellow et all. 1. Paper Ronald Leenes - Laws on Robots, Laws by Robots, Laws in Robots: Regulating Robot Behaviour by Design 2. Raport: European Parliament - European Civil Law Rules in Robotics 3. Raport: ICO - Big data, artificial intelligence, machine learning and data protection 4. Paper: Sophia Duff & Jamie Hopkins - Sit, Stay, Drive: The Future of Autonomous Car Liability 5. Raport: European Commision - AI and IP Report 6. Book: A Brief History of AI, Nils Nilsson (English/Turkish) 7. Book: 50 Soruda Yapay Zeka, Cem Say (Turkish) 8. Book: Deep Learning Book, Ian Goodfellow, at all. (English)
References:

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance % 0
Laboratory % 0
Application % 0
Field Work % 0
Special Course Internship (Work Placement) % 0
Quizzes % 0
Homework Assignments 2 % 20
Presentation % 0
Project 1 % 20
Seminar % 0
Midterms 1 % 20
Preliminary Jury % 0
Final 1 % 40
Paper Submission % 0
Jury % 0
Bütünleme % 0
Total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 2 28
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 14 4 56
Presentations / Seminar 0 0 0
Project 1 2 2
Homework Assignments 2 4 8
Quizzes 0 0 0
Preliminary Jury 0 0 0
Midterms 1 2 2
Paper Submission 0 0 0
Jury 0 0 0
Final 1 2 2
Total Workload 98

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution