Part 5/10:
The critical concept of a causal model involves grasping the cause-and-effect dynamics within a particular environment. For example, consider an AI trained to navigate roads in sunny Florida suddenly handling icy roads in Alaska. This shift presents a challenging scenario because the AI needs to adapt its strategies based on how ice affects driving safety and efficiency. Learning these causal relationships requires a level of understanding far beyond mere association, which is the default approach taken by many AI systems, such as response-based models like ChatGPT.