Mental, scientific, and artificial representations

The rise of artificial intelligence (AI) raises the question of whether we should introduce a new category of representations, next to mental and scientific representations. We argue that AI ‘representations’, in particular of deep neural networks, differ significantly from the mental and scientific representations central to the philosophy of (cognitive) science. These systems lack essential aspects, such as semantic content, the ability to misrepresent, and a clear use condition guiding behavior; it is often unclear why and what they represent. They also lack the capacity to form or identify misrepresentations which makes it impossible to assess their accuracy. Furthermore, AI systems do not satisfy a use condition in the same way as mental and scientific representations. We conclude that, while AI systems can, under certain conditions, be useful tools for scientific discovery, their internal states should not be mistaken for mental and scientific representations.