The way that law enforcers try to work out who committed a crime is constantly evolving to become more sophisticated. From the development of fingerprint profiling in the late 1800’s to more modern techniques such as DNA analysis and forensic testing at the scene.
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.
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.
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 says, ‘Machine learning represents one of the most promising ways to make sense of evidence more rapidly to support criminal investigations.
‘In the future, we may be able to use this technique to collect more information from the surrounding surfaces, so we can interrogate not only any ammunition used but also some individual characteristics of the person who came into contact with it. This could allow us to link the evidence together and link the evidence to the ‘who’.