Culture machine: How MetaCLIP codifies culture

Abstract

How is the cultural made computational? CLIP models are a recent artificial intelligence (AI) innovation which train on massive amounts of Internet data in order to align language and image, deploying this ‘grasp’ of cultural concepts to understand prompts, classify images and carry out tasks. To critically investigate this cultural codification, we explore MetaCLIP, a recent variation developed by Meta. We analyse the model’s metadata, a single file of 500,000 terms that aims to achieve a ‘balanced distribution’ or sufficiently broad understanding of concepts. We show how this model assembles histories, languages, ideologies and media artefacts into a kind of cultural knowledge. We argue this codification fuses the ancient technique of the list with a more recent technique of latent space . We conclude by framing these technologies as cultural machines that exert power in defining and operationalising a particular understanding of ‘culture’ invisibly and at scale.