IP Harbour is proud to present a three-part series exploring Big Data and its use for crime prevention. Part 1 introduces Big Data and how it can be used for profiling and crime prevention. Part 2 will question whether using Big Data for crime prevention is responsible for unintended bias and prejudice within both law enforcement and in the judicial system. Finally, Part 3 will review how citizens are protected from being harmed by their personal data and if there are additional actions law enforcement and the Courts can take to reduce data’s potential harm.

The term ‘big data’ has become a buzzword easily thrown around today. It’s found in numerous news articles and even in Hollywood movies. The information discovered by the analysis of large data sets can ‘change the world’ – as expressed by Tom Hanks, who plays the CEO of an internet giant in the film, The Circle.

But what exactly is big data? And why is it being analysed? In simple terms, big data is a large volume and grouping of structured and unstructured data. The proliferation of technology and internet-enabled devices has meant that corporations and governments can collect information on an unprecedented scale with ease. Now, the emergence of new and advanced technologies, such as virtualization and predictive and stream analytics, have reimagined the way data exists. These technologies work together in different ways to provide meaning to the data, often by applying a number of algorithms that quickly work to sift, refine, and process data sets. This type of analysis unearths trends, predictions, and warnings that are highly sought after by companies, researchers, and governments.

Companies and researchers are not the only ones using big data to facilitate change; increasingly, law enforcement and judges are benefitting from it as well. These entities do not process the data themselves but rely on third-party platforms, such as SiloBreaker or PredPol. These platforms gather a variety of data sets containing information ranging from household income to internet search history. The analysis of these sets uncover valuable crime and behaviour patterns that are used to prevent crime in the form of protective policing and judicial decision making.

Big data has spearheaded the noticed positive shift in the past ten years from reactive to proactive policing. Proactive policing, synonymous with predictive policing, identifies potential terrorist attacks, riots and protests before they occur. Unearthed patterns can help to allocate the level of patrolling needed for concerts, busy roads, and neighbourhoods – saving valuable lives, time and resources.

In the judicial system, judges and magistrates are responsible for determining the length of an offender’s criminal sentence and look to a number of factors to aid them in their decision. Some factors such as the particular law surrounding the crime and the defendant’s admittance of guilt are weighted heavier than others. Recently, the following consideration has become a heavyweight: how likely is the defendant to reoffend? The answer to this question is being found in big data recidivism predictions. If the data shows the defendant has a higher possibility of reoffending, he or she will most likely serve a lengthier criminal sentence. But how does criminal sentencing aid in crime prevention? A stricter sentence keeps a dangerous individual off the streets for longer and acts to deter them against committing future crime.