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The rise of the internet has enhanced our lives in many ways. However, It’s also made it easier to commit the most terrible crimes. The anonymity of the internet and digital currency make it possible to share, sell and trade illicit material from drugs to weapons to victims of human trafficking. While the internet and digital technology have aided the explosion of certain crimes, they can also be an essential tool in the effort to identify victims, accelerate search and rescue times, deter abusers and disrupt the digital platforms where these crimes proliferate.
Technology providers like Veritone are building solutions that employ deep machine learning to fight crime by using it in ways like matching missing children photos to sexual exploitation images on the dark web, using traffic camera footage to locate a vehicle involved and investigating a mass shooting incident by identifying key moments in bystander or security images.
Deep machine learning means that, instead of being programmed to perform specific tasks, a computer can learn independently and adapt its understanding based on exposure to new data. The more data it is exposed to, the better the computer can begin to recognize and identify objects based on complex pattern recognition, until it’s finally able to independently and with a high degree of accuracy make predictions. According to, because computers can be trained with millions of labeled images, they can successfully identify images more quickly than a human can. The algorithms or “neural networks” that can classify what is or is not a picture of a stop sign can also be trained to match other types of images, like car models, license plates, weapons or missing persons.
A machine’s ability to “see” is similar to the way a barcode scanner “sees” the stripes in a uniform bar code. But computer vision – the ability to recognize and, more importantly, categorize and sort images – is what enables deep machine learning to have a wider application in police work.
According to the 2018 Technology Vision report from global management consulting firm Accenture: “There are few crimes today that do not have at least some digital component; for example, the use of social media to create disorder. That’s changing the way that the police need to prevent, detect and solve criminal activity.” Fortunately, it’s never been easier or more cost-effective to collect data, store it, and build custom machine learning and deep-learning models. Combining machine learning algorithms with the computational power of the Intel Xeon Scalable processor enables developers to create intelligent and innovative new products – powered by machine learning – that can help law enforcement agencies fight and investigate crime.
Tom Avery, Vice President, Veritone, explained how machine learning has helped coping with the heaps of data collected via digital methods: “One of the unintended consequences of bodycam video is that now all of a sudden the judicial system is just hammered with all this extra data that just a few years ago didn’t exist. The problem with unstructured audio and video data is that if you want to examine it for relevance or factual evidence, you have to sit down and watch it. If you’re already resource-constrained, how do you deal with that?”
Veritone’s aiWARE solution can help solve the challenge by using artificial intelligence to search stored audio and video for objects, spoken words, logos, faces, and more. Specific for law enforcement, Veritone’s IDentify employs AI to automatically compare known-offender and person-of-interest records with video and photographic evidence, enabling agencies to quickly identify potential suspects for further investigation.
“One of the biggest impacts we can have on law enforcement is actually making that data searchable,” Avery said. “Instead of watching it, you can take action against it using a suite of tools, just like you would use a search engine for data that you’re looking for an answer from.”