ARTIFICIAL INTELLIGENCE ENGINEERING
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
AIN2008 Computers and Ethics Spring 2 0 2 5
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: En
Type of course: Must Course
Course Level: Bachelor
Mode of Delivery: E-Learning
Course Coordinator : Instructor MUSTAFA ÜMİT ÖNER
Course Objectives: This course aims to provide technical and non-technical information for candidates who will be AI engineers.

Learning Outputs

The students who have succeeded in this course;
To adopt ethical approaches from the design by developing AI-powered products

Course Content

This course deals with the use of data and other technologies developed with the introduction of the internet into our lives, both in social life and in the business environment, in accordance with ethical norms.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction and Defining the Field of Computer Ethics
2) Perspectives on Artificial Intelligence
3) Concepts of AI Ethics
4) Technical Recommendations on the Ethics of AI
5) Ethical Principles, Benefits, and Issues of AI
6) Data Privacy-Preserving Techniques
7) Legal Aspects of IoT
8) Cybersecurity Cases on Global Perspectives
9) AI Ethics Stakeholders and Ethical Digital Ecosystem
10) Human Rights and AI
11) AI Ethics & Consequences
12) Blockchain and Ethical Perspective
13) Responsible Use of AI in Digital Organizations
14) Metaverse and Gaming Technologies by Ethical Perspective

Sources

Course Notes: Bernd Carsten Stahl, "Artificial Intelligence for a Better Future: An Ecosystem Perspective on the Ethics of AI and Emerging Digital Technologies”, Springer, ISBN-978-3-030-69978-9, 2020. European Commission, “Ethics Guidelines for Trustworthy AI”, https://ec.europa.eu/futurium/en/ai-alliance-consultation.1.html Gry Hasselbalch, “Data Ethics of Power: A Human Approach in the Big Data and AI Era”, Edward Elgar Publishing, ISBN: 978 1 80220 310 3, 2021.
References: Bernd Carsten Stahl, "Artificial Intelligence for a Better Future: An Ecosystem Perspective on the Ethics of AI and Emerging Digital Technologies”, Springer, ISBN-978-3-030-69978-9, 2020. European Commission, “Ethics Guidelines for Trustworthy AI”, https://ec.europa.eu/futurium/en/ai-alliance-consultation.1.html Gry Hasselbalch, “Data Ethics of Power: A Human Approach in the Big Data and AI Era”, Edward Elgar Publishing, ISBN: 978 1 80220 310 3, 2021.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance 14 % 15
Laboratory % 0
Application % 0
Field Work % 0
Special Course Internship (Work Placement) % 0
Quizzes % 0
Homework Assignments % 0
Presentation 1 % 45
Project % 0
Seminar % 0
Midterms 1 % 30
Preliminary Jury % 0
Final 1 % 10
Paper Submission % 0
Jury % 0
Bütünleme % 0
Total % 100
PERCENTAGE OF SEMESTER WORK % 90
PERCENTAGE OF FINAL WORK % 10
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
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 0 0 0
Presentations / Seminar 1 40 40
Project 0 0 0
Homework Assignments 0 0 0
Quizzes 0 0 0
Preliminary Jury 0 0 0
Midterms 1 30 30
Paper Submission 0 0 0
Jury 0 0 0
Final 1 20 20
Total Workload 132

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Have sufficient background in mathematics, science and artificial intelligence engineering.
2) Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions.
3) Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose.
4) Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction.
5) Select and use modern techniques and tools necessary for engineering applications.
6) Design and conduct experiments, collect data, and analyse and interpret results.
7) Work effectively both as an individual and as a multi-disciplinary team member.
8) Access information via conducting literature research, using databases and other resources
9) Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning.
10) Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field.
11) Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level.
12) Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age. 5
13) Have a sense of professional and ethical responsibility. 5
14) Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices. 5