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.
翻译:生成式人工智能(genAI)的兴起可能改变社会现实不同方面的表征方式,包括现代战争。尽管学术界主要关注AI的军事应用,但生成式AI技术的日益普及可能对战争的描绘、记忆和解读方式产生重大影响。一些初步的学术研究强调了生成式AI在此背景下的风险,特别是其可能扭曲大规模暴力的表征,尤其是通过美化和同质化手段。然而,关于西方与非西方生成式AI模型在描绘不同暴力事件时的表征差异,目前知之甚少。本研究以俄罗斯对乌克兰的侵略为案例,审计了两种图像生成模型——美国的Midjourney和俄罗斯的Kandinsky——如何呈现战争中的虚构与真实事件。我们随后分析了模型对战争相关提示的响应性,以及生成图像的美学与内容特征。研究结果表明,情境因素导致战争表征在模型之间及同一模型内部均存在差异。然而,某些一致的表征模式可能助长战争美学的同质化。