Smartphone footage of war crimes and police brutality is increasingly used in courtrooms, but no one has tested whether the rise of deepfakes has made judges, juries, or investigators distrust that evidence. The problem is a gap between assumption and fact. Legal scholars and human rights advocates have worried for years that hyper-realistic fake videos will erode trust in genuine user-generated recordings, potentially undermining prosecutions for mass atrocities. But no study has actually measured whether that mistrust exists, how deep it runs, or how it affects legal decisions. This project will provide the first systematic evidence on the question. If the research succeeds, it could reshape how courts and truth commissions handle digital evidence. It might lead to new guidelines for verifying footage, new training for prosecutors and judges, or new standards for what counts as reliable evidence in an age of synthetic media. The findings could also influence how human rights organisations collect and present video documentation, and how platforms moderate content during conflicts. The work sits at the intersection of law, psychology, and linguistics, and its primary output will be a clearer understanding of a problem that currently rests on untested assumptions.
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User-generated evidence - defined as information recorded by an ordinary citizen and used in legal adjudication - plays an increasingly important role in accountability processes. Across the world, advances in mobile phone technology and increasing internet access mean that millions of important photographs and videos depicting mass human rights violations have been, and will continue to be, created and shared online. Mass atrocity trials in Sweden, Germany, The Netherlands, and the International Criminal Court, amongst others, have already utilised this kind of evidence, as have UN Human Rights Council-mandated commissions of inquiry, fact-finding missions, and investigations. Yet, at the same time, the public is increasingly confronted with examples of deepfakes - hyper-realistic images, videos, or audio recordings created using machine learning technology - which are only likely to become more advanced and difficult to detect as the technology progresses. These two developments pose an important conundrum: have perceptions of deepfakes led to a mistrust in user-generated evidence? And if so, what does that mean for the role of such evidence in future human rights accountability processes? Much of the literature to date has expressed a concern that the rise in deepfakes will lead to mass mistrust in user-generated evidence, and that this in turn will decrease its epistemic value in legal proceedings. This may well be the case, but no study has yet tested that assumption. This is a major evidence gap that urgently needs to be addressed. Through an innovative interdisciplinary methodology at the intersection of law, psychology, and linguistics, this pioneering project will develop the first systematic account of trust in user-generated evidence, in the specific context of its use in human rights accountability processes.
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