Generic visuality of war? How image-generative AI models (mis)represent Russia's war against Ukraine

TL;DR

This paper examines how different image-generative AI models portray Russia's war against Ukraine, revealing variations influenced by context and some homogenization in war aesthetics.

Contribution

It provides an empirical analysis of how Western and non-Western genAI models depict war, highlighting the influence of geopolitical context on AI-generated representations.

Findings

Representation varies between models and prompts

Context influences the depiction of war scenes

Some consistent war aesthetics emerge across models

Abstract

The rise of generative AI (genAI) can transform the representation of different aspects of social reality, including modern wars. While scholarship has largely focused on the military applications of AI, the growing adoption of genAI technologies may have major implications for how wars are portrayed, remembered, and interpreted. A few initial scholarly inquiries highlight the risks of genAI in this context, specifically regarding its potential to distort the representation of mass violence, particularly by sanitising and homogenising it. However, little is known about how genAI representation practices vary between different episodes of violence portrayed by Western and non-Western genAI models. Using the Russian aggression against Ukraine as a case study, we audit how two image-generative models, the US-based Midjourney and the Russia-based Kandinsky, represent both fictional and factual episodes of the war. We then analyse the models' responsiveness to the war-related prompts, together with the aesthetic and content-based aspects of the resulting images. Our findings highlight that contextual factors lead to variation in the representation of war, both between models and within the outputs of the same model. However, there are some consistent patterns of representation that may contribute to the homogenization of war aesthetics.