High-Risk Memories? Comparative audit of the representation of Second World War atrocities in Ukraine by generative AI applications

TL;DR

This study empirically examines how generative AI models represent WWII atrocities in Ukraine, highlighting risks of misrepresentation and potential distortions of sensitive historical memories.

Contribution

It provides a comparative audit of genAI applications' handling of high-risk wartime memories, revealing specific types of misrepresentation and their implications.

Findings

GenAI models exhibit hallucinations regarding WWII atrocities.

Inconsistent moralization is observed across different AI applications.

Risks of misrepresenting sensitive historical events are significant.

Abstract

The rise of generative artificial intelligence (genAI) models poses new possibilities and risks for how the past is remembered by accelerating content production and altering the process of information discovery. The most critical risk is historical misrepresentation, which ranges from the distortion of facts and inaccurate depiction of specific groups to more subtle forms, such as the selective moralization of history. The dangers of misrepresentation of the past are particularly pronounced for high-risk memories, such as memories of past atrocities, which have a strong emotional load and are often instrumentalised by political actors. To understand how substantive this risk is, we empirically investigate how genAI applications deal with high-risk memories of the Second World War atrocities in Ukraine. This case is crucial due to the scope of the atrocities and the intense, often instrumentalised, contestation surrounding their memory. We audit the performance of three common genAI applications for different types of misrepresentation, including hallucinations and inconsistent moralization, and discuss the implications for future memory practices.