This course explores the dual nature of Artificial Intelligence and Generative Artificial Intelligence (GAI) in addressing environmental challenges, examining both the negative impacts (e.g., use of valuable resources and carbon footprint), as well as its potential positive contributions to sustainability. We will see how AI technologies can optimise resource usage, enhance infrastructure planning, and influence human behaviour positively. We will also learn about how biases within AI systems may inadvertently exacerbate environmental issues. Through case studies in areas such as bias auditing, travel planning, product search optimisation, and food choices, students will gain insights into both opportunities and challenges.
The course structure includes group projects where students tackle sustainability problems empirically. These projects can focus on technical solutions or behavioural changes, with an emphasis on evaluating the impact of developed strategies. By engaging in hands-on research and analysis, students will develop skills in problem-solving, critical thinking, data-driven decision-making, and understanding bias in AI systems.
