COURSE UNIT TITLE

: ETHICS IN ARTIFICIAL INTELLIGENCE AND LAW

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
HUK 1070 ETHICS IN ARTIFICIAL INTELLIGENCE AND LAW ELECTIVE 2 0 0 4

Offered By

Law

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR EZGI PALAS DAĞLI

Offered to

Law

Course Objective

It is aimed to explain the ethics of artificial intelligence and to teach the relationship between artificial intelligence ethics and law.

Learning Outcomes of the Course Unit

1   To be taugt the basic concepts of artificial intelligence
2   To be introduced artificial intelligence technology
3   To be examined ethical aspects of artificial intelligence
4   To be explained legal, criminal and administrative responsibility in artificial intelligence applications
5   To be taught the relationship between artificial intelligence ethics and law

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 To be explained the basic concepts of artificial intelligence
2 Historical Development of Artificial Intelligence Technology and Types of Artificial Intelligence
3 Legal Status of Artificial Intelligence
4 Use of Artificial Intelligence in Administrative Activities I
5 Use of Artificial Intelligence in Administrative Activities II
6 Evaluation of Artificial Intelligence in Terms of Fundamental Rights and Freedoms I
7 Evaluation of Artificial Intelligence in Terms of Fundamental Rights and Freedoms II
8 Artificial Intelligence and Legal and Criminal Liability
9 Artificial Intelligence and Administrative Liability I
10 Artificial Intelligence and Administrative Liability II
11 Relationship Between Artificial Intelligence and Ethics
12 Ethical Principles of Artificial Intelligence
13 Midterm exam
14 Evaluation of Artificial Intelligence Regulations in European Union and Turkish Law
15 General Assessment

Recomended or Required Reading

Aksu, Mustafa, Yapay Zekâ ve Hukuk, On Iki Levha, 2024.
-Bozkurt Yüksel, A. E., "AVRUPA KOMISYONU NUN YAPAY ZEKÂ TÜZÜK TEKLIFI NE GENEL BIR
BAKIŞ" Türkiye Adalet Akademisi Dergisi, 51, 2022.
-Çetin, Selin/Kumkumoğlu, Kemal, Yapay Zekâ Stratejileri ve Hukuk, Gelişen Teknolojiler ve Hukuk II: Yapay Zekâ, (Ed. Aksoy Rétornaz, E. Eylem/Güçlütürk, Osman Gazi), On Iki Levha Yayınları, 2021.
-Dülger, Murat Volkan, Yapay Zekâlı Varlıkların Hukuk Dünyasına Yansıması: Bu Varlıkların Hukuki Statüleri Nasıl Belirlenmeli Terazi Hukuk Dergisi, C. 13, S. 142,
2018.
-Ersoy Çağlar, Robotlar, Yapay Zekâ ve Hukuk, 5. Baskı, Istanbul 2020.
-Ipçi Özden, Avukatlık Mesleğinde Yapay Zekâ Kullanımı, On Iki Levha Yayıncılık, Istanbul 2021.
-Kağıtcıoğlu, Mutlu, Yapay Zekâ ve Idare Hukuku (Bugünden Geleceğe Yönelik Bir Değerlendirme) , Hacettepe Hukuk Fakültesi Dergisi, C. 11, S. 1, 2021.
-Kuçuradi Ionna, Etik, Ankara, Türkiye Felsefe Kurumu Yayınları, 2006.
-Nils J. Nilsson, Yapay Zeka-Geçmişi ve Geleceği, Istanbul, Boğaziçi Üniversitesi Yayınevi, 2018.
-Oğurlu, Yücel. Yapay Zekanın Idare Hukuku ve Idari Yargıda Doğuracağı Tartışmalar. iç. Idare Hukuku ve Idari Yargı
Uluslararası Sempozyumu. (24-26 Mayıs 2021)
-Sarı, Onur, Yapay Zekânın Sebep Olduğu Zararlardan Sorumluluk, Türkiye Barolar Birliği Dergisi, S. 147, 2020.
-Seyhan, Serkan, Yapay Zeka Teknolojileri Kapsamında Idarenin Sorumluluğu, On Iki Levha, 2023.
-Tanrıverdi, Ayşe Alımla, Yapay Zekânın Kamu Hizmetinin Sunumuna Etkileri, Adalet Dergisi, S. 66, 2021.
-Tansuğ, Çağla, Karayollarında Toplu Taşıma Hizmeti Sunumunda Yapay Zekâ Kullanımı, Otonom Araçlar ve Idarenin Sorumluluğu, Gelişen Teknolojiler ve Hukuk II: Yapay Zekâ, (Ed. Aksoy Rétornaz, E. Eylem/Güçlütürk, Osman Gazi), On Iki Levha Yayınları, 2021.
-Tezcan Durmuş/Erdem, Mustafa Ruhan/Sancakdar, Oğuz Sancakdar/Önok, Murat, Insan Hakları El Kitabı, 10. Baskı, Seçkin Yayıncılık, 2024.
-Yayla, Ahmet. Idare Hukuku Bakımından Yapay Zeka, Seçkin, 2023

Planned Learning Activities and Teaching Methods

Lecturing, preparation of the students for the topics before the lesson, repeating the topics explained after the lesson, preparing the homework, participation of the students by expressing their opinions and asking questions.

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)

ezgi.palas@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 2 26
Preparations before/after weekly lectures 13 2 26
Preparation for midterm exam 1 20 20
Preparation for final exam 1 25 25
Final 1 2 2
Midterm 1 1 1
TOTAL WORKLOAD (hours) 100

Contribution of Learning Outcomes to Programme Outcomes

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