Admissibility of Big Data is Changing Tactics in Criminal Court Cases

Most discussions around big data have focused on commercial benefits. Both small startups and the world’s largest corporations have used big data to minimize costs, improve the effectiveness of their marketing campaigns and identify new markets to penetrate. Since business implications of big data have monopolized the conversation, fewer people have discussed the benefits in the public sector.
Nevertheless, big data is a game changer for government agencies as well. Some of the biggest big data breakthroughs can be seen in court cases in the criminal justice system. The limits are still being debated, but it will have a profound impact on the future of criminal law.
Big data has made it much easier for law-enforcement officials to uncover evidence on all but the most careful criminals. Ross William Ulbricht, the founder of Silk Road, left behind digital breadcrumbs that eventually led to his capture. Authorities were able to use data mining tools to find an old forum post where he revealed his name and email address around the time Silk Road was founded.
This was one of the first times that law-enforcement used big data to bring a criminal mastermind to justice. However, it wasn’t one of the most impressive examples. Ulbricht made some blatantly stupid mistakes that would have eventually exposed him anyways.
Big data has played a more important impact in lower profile cases where criminals did a better job covering their tracks. It has helped officials dox online predators, scam artists and other criminals that have left subtler digital breadcrumbs. These criminals don’t realize how much information they give away.
They may allude to their general location by using phrases and terminology unique to the place they grew up. Pictures that they post online may have landscapes that are unique to certain regions. Pixilation of the pictures they use may be unique to certain types of cameras. They may unwittingly reveal small details about their past.


