AI Ethics and Regulation

TEACHING UNIT 1. INTRODUCTION TO THE ETHICS AND PHILOSOPHY OF AI Historical context and evolution of AI from the past to the present Fundamental ethical principles of AI Ethical dilemmas in the design and application of AI systems The social, economic, and cultural impact of AI Fundamentals of the philosophy of AI and its implications TEACHING UNIT 2. ALGORITHMIC BIAS AND DISCRIMINATION Sources of bias in AI data and algorithms Types of Bias Identified in AI Fairness and Equity Metrics for AI Models Advanced Techniques for Detecting and Mitigating Bias Analysis of Case Studies on Algorithmic Discrimination Frameworks for Evaluating Algorithmic Fairness LEARNING UNIT 3. PRIVACY, DATA PROTECTION, AND GOVERNANCE IN AI SYSTEMS Key data protection regulations Privacy challenges in the AI data lifecycle Privacy-preserving techniques using cryptography and computing Implementation of privacy-by-design and privacy-by-default principles Data governance and compliance strategies in AI development Challenges of data anonymization and de-identification in AI LEARNING UNIT 4. RESPONSIBILITY AND ACCOUNTABILITY IN AI DECISION-MAKING Explainability (XAI) and algorithmic transparency Models for attributing responsibility in autonomous systems Algorithmic auditing and tools for independent evaluation AI impact assessment as a preventive tool Implications of civil and criminal liability for AI TEACHING UNIT 5. INTERNATIONAL REGULATORY FRAMEWORK FOR AI: PERSPECTIVES AND TRENDS Initiatives and Recommendations from Global Organizations on AI Comparison of Regulatory Approaches Across Different Jurisdictions Development of Technical Standards and Certifications for Trustworthy AI The Role of Public-Private Collaboration in AI Governance LEARNING UNIT 6. APPLICATION OF ETHICS AND REGULATION OF AI IN KEY SECTORS Ethical and regulatory implications of AI in healthcare Challenges of AI in the financial and banking sectors Ethics of AI in criminal justice and security systems Considerations for AI in the Labor Market and Education Applications of Ethical Principles in the Development of Autonomous Vehicles LEARNING UNIT 7. RESPONSIBLE AI IN PRACTICE: GOVERNANCE TOOLS AND POLICIES (GOOGLE AI PRINCIPLES) Practical implementation of responsible AI frameworks in organizations Open-source tools and libraries for ethical AI The Google AI Principles Designing multidisciplinary teams and internal codes of conduct for AI Strategies for communicating about AI and fostering public trust TEACHING UNIT 8. ADVANCED GOVERNANCE AND FUTURE DILEMMAS OF AI Advanced governance and future dilemmas of AI Ethical Implications of AI for Environmental Sustainability and Resource Consumption Emerging Models of AI Governance (public algorithms, mandatory external audits) The Future of Human Rights in the Age of AI Cybersecurity in AI and the Protection of Critical Infrastructure