Features Technology
Artificial Intelligence for law enforcement

Policing is a labour-intensive business. A large criminal investigation may involve a team of officers who must interview lots of people with a great deal of information at play, and all of it must be handled with tremendous care.

But what if all that note-taking could be digitized and organized with the kind of analytics that used to be considered science-fiction? Imagine that an officer speaks to a witness or suspect and not only has the entire conversation at their fingertips but also data that actually demonstrates the individual’s emotion.

With the pandemic hopefully on the way out, organizations of all sizes are now adopting a mix of in-person, online and hybrid meetings. The latter utilizes both the virtual and in-person variety; the technology exists to let them make this choice wisely. In short, the future has arrived and one of the biggest beneficiaries of this might just be law enforcement.

Human-like AI (Artificial Intelligence) can enhance the meeting experience for both the host and the attendees by allowing participants to focus on the meeting and forget about labour-intensive tasks like notetaking. A full transcript and recording of what transpired are automatically created and then crafted into a concise executive summary, and this goes for a 1:1 meeting or a group session. And the technology can do even more by using what is called ‘collected telemetry’ (the conversation data that pertains to everything from context to emotion) to build an advanced analysis of performance and sentiment.

The technology uses facial and voice recognition, plus natural language processing, so you can quantify and measure elements of the corporate culture of an organization—this can also include the police. We’re talking about everything from people’s emotions and sentiments to trust and care. Comprehensive profiles of every single person and contact (i.e., members of the investigating team, witnesses, suspects, etc.) can be created and automated. This means every interaction is measured, analyzed and visualized, which then allows officers to take action.

There are many potential benefits for law enforcement. These include:

• Police must often interview people and transcribe when on the fly, but digitizing all that information saves huge amounts of time and effort, greatly enhances accuracy and makes everything instantaneous in real-time.
• With the analytics capability, police could automatically categorize information any way they choose.
• More police today wear body cameras to provide ‘vision intelligence’ but without video analytics. With AI all this data can undergo intense analytics.

This technology is essentially a speech and conversational intelligence platform that can be tailored to specific industries and professions. The latter can include healthcare practitioners like doctors and nursing practitioners, in addition to the police. Think of improvements in time management, client relations and forecasting, not to mention team building, recruitment and retention. It allows you to dig deep into the cause of potential rifts or upswings, which means you can discover risks you might otherwise have not found.

Policing is a labour-intensive business.

In the business world, organizations use conversational intelligence to create profiles of prospective or existing clients that quickly allow case managers to see trends in these prospects’ affinities. What topics (people, things, places, etc.) these people speak about most, and what their sentiments toward them are, can be determined quickly. Now take that to policing. In a police matter, this could be applied to investigations where repeat topics and sentiment can reveal subtle details that could be worth delving into further. Conversational AI gives investigators a dedicated partner that thoroughly analyzes every detail, no matter how small.

This level of scrutiny can also result in enhanced transparency, accountability and compliance. Conversational AI is already used quite extensively in the private sector to help enforce brand messaging and policy in both writing and speech. It could easily be applied to help police officers remain between the lines in terms of policy and procedure. This would provide an excellent and additional training tool for new officers, offering them coaching opportunities based on their real interactions.

And nowadays with cloud technology on the rise, this would allow any police officer or law enforcement organization to securely collaborate with sensitive data on the cloud. What’s coming next? How about automating real-time evidence and fact-based research (case precedents, commentaries relevant to a case, summaries, etc.). It’s all possible.

Fuad Miah is Chairperson and Co-founder of Uncanny Lab.

Justin Hacker is Chief Executive Officer and Co-founder of Uncanny Lab. Both can be reached at www.uclab.ai.