AI Professionals, AI developers, engineers, and researchers, Ethics and Philosophy Enthusiasts, Business Leaders and Students.

No specific prerequisites are required, but a general understanding of artificial intelligence concepts is helpful.

Course Outline:

Session 1: Introduction and Key Ethical Issues in AI.

• Understanding the significance of ethics in AI.
• Historical and contemporary ethical challenges in technology.
• The impact of AI on society and individuals.
• Introduction to ethical frameworks (e.g., utilitarianism, deontology, virtue ethics) and their application in AI.
• Bias and fairness in AI algorithms.
• Privacy and data ethics.
• Transparency, interpretability, and accountability.
• Autonomous systems and decision-making.
• Ethical considerations in AI research.

Session 2: Ethical Frameworks, Guidelines and Case Studies.

• AI ethics principles and guidelines (e.g., AI ethics principles by ACM and IEEE).
• Ethical AI design and development practices.
• Responsible AI deployment and monitoring.
• Case studies illustrating the application of ethical frameworks.
•  Real-world case studies of AI ethics (e.g., facial recognition, algorithmic bias, autonomous vehicles).
• Group discussion and analysis of case studies.
• Ethical decision-making and the role of stakeholders.
•  Addressing ethical dilemmas in AI.

Training Material Provided: Yes (Digital Format)