Participants engage in the full cycle of training a machine learning model—collecting data, defining categories, training the system, testing outputs, and refining performance.
Framed within a planetary survival scenario, participants collaborate with AI to build systems that assist in identifying critical resources. Emphasis is placed on decision-making, bias in data, and the limitations of AI systems.