Algorithms learn performed emotions, not real ones, from limited datasets.
Emotion detection algorithms were often trained on the JAFFE dataset, which contains images of 10 Japanese female models performing seven facial expressions. The problem is the algorithm doesn’t learn how someone actually looks when angry, but rather how those specific women performed an angry expression. This distinction is critical. The models were acting out emotions rather than genuinely experiencing them, so the training data captures performance, not authentic emotional states. This makes the foundation of emotion detection fundamentally flawed.
— It’s The Data, Stupid! Why AI Might Get It Wrong. · Forbes