TÜRKÇE
ENGLISH
Information
| Unit | INSTITUTE OF SOCIAL SCIENCES |
| PUBLIC LAW (MASTER) (WITH THESIS) | |
| Code | KMH724 |
| Name | RISK CRIMINAL LAW AND ARTIFICIAL INTELLIGENCE |
| Term | 2026-2027 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Belirsiz |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr. Öğr. Üyesi ARZU BALAN |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The course aims to develop an understanding of the impact of artificial intelligence technologies on criminal law, to examine the legal issues arising from the use of AI systems, to reassess fundamental criminal law concepts such as criminal liability, culpability, causation, and attribution within the context of artificial intelligence, and to provide both theoretical and practical knowledge regarding artificial intelligence and algorithmic decision-making systems.
Course Content
The course content consists of examining the issues arising from artificial intelligence and algorithmic systems in terms of criminal law. In this context, topics such as the legal nature of artificial intelligence, autonomous systems and criminal liability, algorithmic decision-making processes, risks arising from artificial intelligence, digital evidence, AI-supported criminal investigations, and the use of artificial intelligence technologies within the criminal justice system are addressed. In addition, new types of offenses related to artificial intelligence and the application of existing criminal offenses within the context of this technology are also evaluated.
Course Precondition
None
Resources
This course includes not only theoretical knowledge related to artificial intelligence and criminal law, but also the examination of practical examples. Within the scope of the course, it aims to relate theoretical knowledge to practice by addressing national and international legislative regulations, judicial decisions, and doctrinal opinions. In addition, the use of artificial intelligence systems in the criminal justice system, algorithmic decision-making processes, and the ethical and legal issues that may arise from these processes are discussed.-Balan, Arzu, Ceza Hukuku Teorisinde ‘Meta’morfoz: ‘Tehlike’ Suçları, Adalet Yayınevi. -Aydın, Devrim, Ceza Muhakemesinde Deliller, Yetkin Yayınevi. Erdoğan, Irmak, Yapay Zekâ ve Profilleme Teknolojilerinin Ceza Muhakemesinde Kişisel Veri İşlenmesine Etkileri -Ata, Sefa, Ceza Hukuku Bağlamında Yapay Zeka
Notes
-Coeckelbergh, Mark, AI Ethics, The MIT Press, Cambridge. -Ashworth, Andrew / Zedner, Lucia, Preventive Justice, Oxford University Press, 2015. -Arslan, Çetin, “Digital Evidence and Interception of Communication”, Journal of Criminal Law and Criminology, Vol. 3, No. 2, pp. 253–266. Elmas, Çetin, Artificial Intelligence Applications: Artificial Neural Networks / Machine Learning / Deep Learning / Deep Networks / Fuzzy Logic / Genetic Algorithms, Seçkin Publishing.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Upon successful completion of this course, students will be able to: Explain the effects of artificial intelligence and algorithmic systems on criminal law. |
| LO02 | Analyze the legal issues arising from artificial intelligence technologies from the perspective of criminal law. |
| LO03 | Evaluate fundamental criminal law concepts such as act, culpability, causation, and attribution in the context of artificial intelligence. |
| LO04 | Discuss the problems arising from autonomous systems and artificial intelligence technologies in terms of criminal liability. |
| LO05 | Identify the effects of AI-supported decision-making processes on the criminal justice system. |
| LO06 | Distinguish new types of offenses related to artificial intelligence and digital technologies and the application of existing offenses in this context. |
| LO07 | Explain the ethical and legal issues arising from artificial intelligence applications in criminal law. |
| LO08 | Critically analyze current developments in the field of artificial intelligence and criminal law and develop possible solutions. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Based on undergraduate qualifications, the ability to develop and deepen knowledge to an expert level in the same or a different field. | 5 |
| PLO02 | Beceriler - Bilişsel, Uygulamalı | Ability to utilize theoretical and practical knowledge at an expert level in their field. Ability to integrate and interpret knowledge acquired in their field with information from different disciplinary areas, and to create new knowledge. Ability to solve problems encountered in their field using research methods. | 2 |
| PLO03 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | The ability to independently conduct research requiring expertise in a specific field. | 4 |
| PLO04 | Yetkinlikler - Öğrenme Yetkinliği | The ability to critically evaluate the knowledge and skills acquired at an expert level in their field and to direct their own learning. | |
| PLO05 | Yetkinlikler - Alana Özgü Yetkinlik | the ability to monitor and teach social, scientific, cultural, and ethical values in the stages of data collection, interpretation, application, and dissemination related to their field. | |
| PLO06 | - | he ability to critically examine and develop social relationships and the norms that govern them. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Artificial intelligence, algorithm, and digitalization concepts: basic conceptual framework | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 2 | The development of artificial intelligence and its effects on law | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 3 | Digitalization and the transformation of criminal law: new problem areas in criminal law | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 4 | Fundamental concepts of criminal law in the context of artificial intelligence: act, culpability, causation, and attribution | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 5 | Autonomous systems and criminal liability: reconsideration of the concept of the offender | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 6 | Artificial intelligence–based risks and the concept of risk in criminal law | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 7 | Artificial intelligence and types of offenses: crimes committed through AI and emerging new offenses | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Yazılı Sınav, Sözlü Sınav, Ödev |
|
| 9 | Artificial intelligence in criminal procedure law: digital evidence, algorithmic analysis, and investigation processes | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 10 | Debates on criminal liability in the context of artificial intelligence: liability of producers, users, and developers | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 11 | Algorithmic decision-making and the criminal justice system: predictive policing and risk assessment systems | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 12 | Artificial intelligence and criminal procedure: digital evidence, data analysis, and algorithmic investigation methods | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 13 | Artificial intelligence, ethics, and criminal law: algorithmic bias, transparency, and accountability issues | Reviewing the relevant course materials | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 14 | Current developments in artificial intelligence and criminal law and comparative law discussions | Reviewing the relevant course materials | Öğretim Yöntemleri: Soru-Cevap |
| 15 | Practical work | Discussion of case studies related to the relevant topic | Öğretim Yöntemleri: Örnek Olay |
| 16 | Term Exams | Ölçme Yöntemleri: Ödev |
|
| 17 | Term Exams | Ölçme Yöntemleri: Sözlü Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 3 | 10 | 30 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 10 | 10 |
| Final Exam | 1 | 10 | 10 |
| Total Workload (Hour) | 162 | ||
| Total Workload / 25 (h) | 6,48 | ||
| ECTS | 6 ECTS | ||