Abstract

Recent work in neuroscience and artificial intelligence has revived an old philosophical question in a new form: is the brain best understood as a system that constantly predicts its sensory input, or does cognition involve something more than prediction? Predictive processing theories describe the brain as a mechanism that minimizes prediction error and have been highly successful in explaining perception, action, and learning. This paper argues that, while prediction plays an important role in how brains function, it cannot by itself explain understanding, meaning, or rational thought. The problem is not that predictive models are wrong, but that they are often asked to do too much philosophical work. Drawing on ideas from embodied cognition and interpretation, the paper shows why successful prediction does not amount to genuine understanding. Contemporary artificial intelligence systems are used as a test case: despite their impressive predictive abilities, they illustrate how behavior can be effective without being meaningful in the relevant sense. The paper proposes that cognition must be explained at more than one level, combining neural processes, bodily engagement with the world, and participation in norm-governed practices. On this view, the mind–body problem is not about mysterious mental substances, but about how different kinds of explanation fit together.