The course below covers 12 selected topics in AI as well as suggested activities for students. Depending on the focus and depth chosen (and the background of the audience), the course is suitable as an elective course for undergraduates, or for first-year graduate students, as well as working professionals.
Weekly Schedule
Week 1: Introduction to AI and Society
- Overview of AI technologies
- Historical context and societal impact
- Key ethical frameworks
Week 2: AI Governance and Regulation
- Global regulatory efforts (EU AI Act, U.S. frameworks)
- Corporate compliance and risk management
Week 3: Bias, Fairness, and Ethics in AI
- Algorithmic bias and discrimination
- Inclusive design and mitigation strategies
Week 4: AI and the Future of Work
- Automation, job displacement, and reskilling
- Human-AI collaboration models
Week 5: AI and Surveillance
- Privacy concerns and surveillance capitalism
- Case studies: facial recognition, predictive policing
Week 6: AI in Political Influence and Disinformation
- Deepfakes, microtargeting, and lobbying
- Media manipulation and electoral risks
Week 7: AI for Climate Modeling and Disaster Response
- Forecasting, resource allocation, and emergency planning
- Case studies in environmental AI
Week 8: Sustainable Supply Chains Powered by AI
- Logistics optimization and waste reduction
- Transparency and traceability tools
Week 9: Smart Cities and Urban Sustainability
- AI in traffic, energy, and waste management
- Ethical concerns in urban data collection
Week 10: Green AI and Environmental Footprint
- Energy demands of AI models
- Sustainable computing strategies
Week 11: AI in Circular Economy Models
- Lifecycle tracking, recycling, and reuse
- Business models for sustainability
Week 12: AI Entrepreneurship for Social Impact
- Startups solving global challenges with AI
- Funding, scaling, and impact metrics
