Responsible AI

Catalog description

This course explores the ethical, security, and safety considerations and challenges associated with the development, deployment, impact and governance of artificial intelligence (AI) technologies. Students will critically examine the ethical, security, and safety implications of AI in various domains, including healthcare, finance, law education, scientific research, social media, robotics and autonomous systems, news, and more. The course will also address the societal and cultural implications of AI, such as bias, transparency, accountability, the potential impact on jobs and privacy, and control and governance of AI. Through case studies, discussions, and hands-on exercises, students will develop a understanding of the ethical implications of AI and explore strategies for responsible AI development and implementation. Prerequisite(s): ITS 26500 FOR LEVEL UG WITH MIN. GRADE OF C Course Learning Outcomes 1. Understand why ethical, security, and safety analysis is essential when dealing with AI and explore the ethical, security, and safety dimensions of AI development, deployment, and impact. 2. Evaluate the impact of emerging AI applications in real-world scenarios. 3. Recognize the potential consequences of AI on society, individuals, and various domains including understanding biases, privacy and data protection concerns, and fairness issues. 4. Recognize issues with transparency and ethical, security, safety considerations in providing explanations for AI decisions. 5. Develop critical thinking skills to assess AI system’s ethical, security, and safety. They’ll learn how to clarify ethical, security, safety dilemmas and analyze AI applications in different contexts. 6. Evaluate critically existing policies related to AI and explore how ethical, security, safety, and socially responsible and accountability principles that can guide decision-making in their professional lives. 7. Analyze emerging AI governance strategies, critically assessing their origins, applications, landmark case studies, and effectiveness for responsible AI management and regulation. View Class Schedule