Information Package / Course Catalogue
Artificial Intelligence and Professional Ethics
Course Code: EMY008
Course Type: Required
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 3
Objectives of the Course

The aim of this course is to enable students to gain awareness of ethics, professional responsibility, data security, and reliable information production in the use of artificial intelligence.

Course Content

The course covers ethics, professional ethics, data ethics, personal data protection, bias in AI, misinformation, customer confidentiality, ethics in listing and report production, legal responsibility, and digital security.

Name of Lecturer(s)
Learning Outcomes
1.The student relates the concepts of ethics, professional ethics, responsibility, and trust to the use of AI.
2.The student explains misinformation, bias, discrimination, and human oversight issues in the use of AI.
3.The student evaluates the risks of AI use in terms of personal data protection and customer confidentiality.
4.The student applies ethical principles in real estate listings, valuation, reporting, and customer communication.
5.The student identifies ethical risks and proposes solutions in an AI-supported real estate transaction.
Recommended or Required Reading
1.Instructor’s Lecture Notes
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Artificial Intelligence and Ethics: The concepts of artificial intelligence, ethics, professional ethics, responsibility, and trust are explained, and their relationship with the real estate sector is established.
Week 2 - Theoretical
Basic Principles of Professional Ethics: Basic ethical principles such as honesty, impartiality, confidentiality, responsibility, transparency, and public interest are discussed.
Week 3 - Theoretical
Ethical Issues in the Use of Artificial Intelligence: Misinformation, bias, discrimination, automated decision-making, and the importance of human oversight are explained.
Week 4 - Theoretical
Data Ethics and Protection of Personal Data: Personal data, sensitive data, customer information, data security, and confidentiality responsibilities in real estate consultancy are discussed.
Week 5 - Theoretical
Reliability and Verification in Artificial Intelligence: Checking AI outputs, source verification, risks of inaccurate information, and professional responsibility are explained.
Week 6 - Theoretical
Ethical Communication in the Real Estate Sector: Accurate communication with clients, avoiding misleading information, truthfulness in listings, and transparency in price and portfolio information are covered.
Week 7 - Practice
Ethical Case Evaluation: Students are asked to evaluate short ethical cases related to AI use, customer information, listing preparation, or price prediction.
Week 8 - Theoretical
Ethics in AI-Generated Listings, Reports, and Content: Accuracy, copyright, and misleading content risks in AI-generated listing texts, visuals, reports, and presentations are discussed.
Week 9 - Theoretical
Discrimination, Bias, and Fair Service Delivery: Bias in AI systems, customer selection, regional discrimination, exclusion based on income level, and the principle of fair service are explained.
Week 10 - Theoretical
Ethics in Land Registry, Zoning, and Valuation Processes: The accurate and complete transfer of title deed, zoning status, encumbrance, building condition, and valuation information to clients is emphasized.
Week 11 - Theoretical
Artificial Intelligence, Legal Responsibility, and Professional Risks: Wrong decisions based on AI outputs, limits of responsibility, legal risks, and the need to consult experts are explained.
Week 12 - Theoretical
Digital Security and Professional Confidentiality: Password security, document sharing, customer files, online platforms, and the risks of uploading data to AI tools are explained.
Week 13 - Theoretical
Ethical Decision-Making and Codes of Professional Conduct: Ethical dilemmas, decision-making processes, professional codes of conduct, and ethical guidelines for real estate agents are discussed.
Week 14 - Theoretical
General Review and Practical Ethical Scenario: The semester topics are reviewed; students are asked to identify ethical risks and propose solutions in a real estate transaction involving AI.
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%5
Quiz1%5
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140342
Assignment1055
Quiz1055
Midterm Examination101010
Final Examination101313
TOTAL WORKLOAD (hours)75
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
OÇ-1
2
3
2
3
5
2
3
2
2
1
4
5
2
OÇ-2
3
3
3
2
5
4
2
3
2
1
4
2
3
OÇ-3
2
3
2
3
5
4
5
2
1
4
2
2
3
OÇ-4
3
2
3
2
4
5
5
4
2
1
2
3
2
OÇ-5
2
3
2
5
4
5
4
2
2
3
2
5
4
Adnan Menderes University - Information Package / Course Catalogue
2026