Detecting Deepfakes: AI and Anti-Jewish Hate

Artificial Intelligence and Anti-Jewish Hate: a Case for Regulating Generative AI

This research focuses on AI-generated antisemitic fake images in digital communication (so-called deepfakes). It provides insights into, and an overview of, existing research practices. It evaluates available solutions for detecting AI-generated antisemitic deepfakes, creates a method for labelling such deepfakes in different online content, building on models established by our researchers for the “Decoding Antisemitism” project, and for the first time presents, analyses and evaluates a dataset with such labels.

Our results show that further research in this area is required if a model to detect artificially created antisemitic online content is to be accurate and successful. Current algorithmic solutions struggle to account for complex, nuanced forms of imagery, which are particularly prevalent in the dissemination of hate ideologies. As online actors try to avoid automatic recognition, they often resort to implicit rather than explicit, obvious patterns, making detection even more challenging.