Thanks to machine learning, the system improves its searches on the basis of such interactions with analysts, who can raise or lower the importance of different sets of criteria with a swipe. “An analyst can then say whether this is relevant or not and VALCRI will adjust the results,” says Neesha Kodagoda, also at Middlesex. The system might spot that shell casings were found at several recent crime scenes including the one the police are focusing on now, for example. All of this is then presented on two large touchscreens for a crime analyst to interact with. It scans millions of police records, interviews, pictures, videos and more, to identify connections that it thinks are relevant. VALCRI’s main job is to help generate plausible ideas about how, when and why a crime was committed as well as who did it. “The hard part is working out which dots need to be connected.”
“Everyone thinks policing is about connecting the dots, but that’s the easy bit,” says William Wong, who leads the project at Middlesex University London. The idea is that the system, called VALCRI, will be able to do the laborious parts of a crime analyst’s job in seconds, freeing them to focus on the case, while also provoking new lines of enquiry and possible narratives that may have been missed. UK police are trialling a computer system that can piece together what might have happened at a crime scene.