But evading justice may have just become more difficult for those committing a crime using a gun with the discovery that AI can be used to determine which ammunition, and ultimately which firearm, was responsible for a particular gunshot.
Forensic scientists from King’s College London, Northumbria University, University of Lausanne and La Sapienza University of Rome have shown that this investigative work can be done using machine learning - a type of AI that can find trends in complex data. This allows experts to predict the original ‘ingredients’ of ammunition from the gunshot residue left behind on surfaces, such as spent cases, wounds, and potentially the shooter’s hands.
Court worthy evidence
Previously, it would have been necessary to recreate the scenario under ‘real-life’ conditions and to carry out a test in order to make evidence ‘court worthy’. But this new method, known as quantitative profile-profile relationship (QPPR) modelling, could make the process much quicker and easier.
Dr Leon Barron explained "Every case is going to be different in forensic science - there are many variables to consider; different times, locations, scenarios etc. We’ve shown that despite these variables and the complexity of gunshot residue when it comes out of the end of a gun, it is possible with machine learning to drag all that information back together again to find the original ammunition used."
In order to do this, the process also takes into account the gun that was fired, the ammunition itself and how it was dispersed, and then reads past these details.
Dr Barron said, "Machine learning represents one of the most promising ways to make sense of evidence more rapidly to support criminal investigations.
In the future, this technique may allow forensic teams to collect more information from the surrounding surfaces, so they can interrogate not only any ammunition used but also some individual characteristics of the person who came into contact with it.