Understanding AI Brittleness

AI systems often exhibit brittleness, which refers to their inability to adapt when faced with new or slightly altered stimuli. For example, a language model trained to classify skin lesions mistakenly associated the presence of a ruler in images with malignancy, showcasing that it did not truly understand what a lesion or a ruler is. Instead of comprehending the underlying concepts, the AI relied on shortcuts based on training data, making it vulnerable to inaccuracies outside of that data set. This highlights the importance of developing a robust understanding within AI systems to create more reliable and generalized models of the world.