High-Risk Memories? Comparative audit of the representation of Second World War atrocities in Ukraine by generative AI applications
For historians and memory scholars, this work empirically demonstrates the risk of historical distortion in generative AI, though the findings are specific to a single case study.
The study audits three generative AI applications for historical misrepresentation of Second World War atrocities in Ukraine, finding significant issues such as hallucinations and inconsistent moralization, highlighting risks for high-risk memories.
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.