Artificial intelligence technology is making its mark on every aspect of our personal and professional lives. Policing is no exception. For several years, police officers have been using software for facial recognition, crowd monitoring, and crime prevention.
A few decades ago, artificial intelligence technology was little more than the subject of science fiction movies and novels. Today, this type of technology is entering all aspects of our lives, including law enforcement. When it comes to policing, robots, are helping with monitoring and policing low security areas like malls and high security and risky areas like power stations, construction sites..etc.
AI technology uses algorithms to analyze huge amounts of data in less time. Through learning human behaviors, the software also develops the ability to mimic and eventually forecast future actions. As the technology’s abilities and accuracy grow, AI is likely to spread even more widely within law enforcement.
Experts believe that smart technologies like AI can help reduce crime in cities by up to 40%. Artificial intelligence may also cut emergency service response rates by 20 to 35%. Despite those obvious benefits of AI when it comes to keeping citizens safe, the technology is not free from controversy. Most of those concerns relate to predictive policing and surveillance, according to consultants Deloitte.
Facial recognition technology is one of the most popular applications of AI technology. Facial recognition software allows police officers to identify individuals beyond doubt. They no longer have to manually check IDs across different databases. Apart from recording an actual image, most of these software applications also collect biometric data. Biometric information allows for more accurate identification. There are some challenges with facial recognition technology but they can be augmented with biometric information to bolster their accuracy.
Worldwide, law enforcement units use facial recognition technology to:
- Locate wanted individuals more easily
- Identify people featured in images with less risk of false positives
- Establish the identity of injured or unconscious victims in traffic accidents
- Retrospectively confirm a person’s identity and cross-check it against existing databases
Thanks to considerable developments over the past few years, facial recognition technology can now also be used live. Live facial recognition (LFR) compares camera feeds against watchlists of known and wanted criminals, for example. Because it works in real time, LFR enables police forces to arrive on location within minutes when the software finds a match.
There is definitely some very serious concern regarding bias in facial recognition and that stems from the biased data sets we feed for it to learn from. As we improve these data sets and use diverse data for these machines to learn from they will get better.
Also Read: Artificial Intelligence and disinformation.
Beyond Facial Recognition
Establishing the identity of wanted individuals has always been an important part of police work. AI can further improve that process, but the real power of this technology lies in crime prediction and prevention.
Artificial intelligence software can analyze unimaginable quantities of data, for example from CCTV feeds. Apart from looking for faces, the software also identifies trends, patterns of behavior, and other correlations much faster than humans could. Technology far surpasses humans when it comes to the amount of data to be analyzed.
Whilst the analysis forms the foundation of all AI applications, machine learning then enables the software to draw human-like conclusions. Based on those results, AI can predict the future. The process may sound straightforward, but machine learning takes time and several iterations before an algorithm draws meaningful conclusions.
Human behaviors are complex and often driven by a variety of motives. Theoretically, it is possible for software to learn and apply all of them in the future. However, at the moment, AI is playing a supportive role in law enforcement and policing. The technology is not yet capable of taking over from human officers.
For example, based on its data analysis, AI software can identify behavioral patterns and make predictions of potential future crimes based on these. But predictive policing based purely on technology remains controversial. This type of policing may be the main style of policing in the future, though.
Reducing Police Paperwork
Police forces worldwide have lamented the amount of paperwork officers have to complete following incidents they attend. Creating and updating case files keeps officers off the streets and can compromise the safety of citizens.
Saying that cutting down on case reports would also be problematic as they often form the basis of a successful prosecution of a crime. AI can help by automatically capturing the required data, thus minimizing the time officers devote to reporting. Officers may have to review and annotate the data that has been collected, but they will likely spend much less time than they would have needed to complete the entire process by hand.
Recording data through AI technology and fact-checking it afterward not only reduces the amount of time required. It also helps minimize the potential for human error or bias in a report.
Smart Knowledge Sharing of Incidents
Police incident reports used to gather dust in archives where different departments kept hard copy records of crime reports and investigations. AI technology, combined with collaborative software, makes it easier to share information between departments and agencies.
Sharing information often means accessing different databases and comparing their contents. Done by a single officer or even a team of officers, this would take hours, if not days. AI, on the other hand, can easily cross-reference the contents of several databases and share its conclusions.
Police forces not only gain access to more information. They also benefit from having an invaluable “team member” who digests vast quantities of data and draws human-like conclusions from it.
Smart knowledge sharing of this type benefits each of the involved police forces and law enforcement agencies.
Successful use of artificial intelligence technology in policing is based on confidence and mutual trust. This trust needs to exist between different arms of law enforcement when it comes to sharing data. It is also required between a police force and its community.
Robots and Security
Robots are working on improving, monitoring and security in low risk and high risk areas by patrolling malls, power grids… etc. These robots are used to reach areas not accessible or not conducive to human patrolling or monitoring.
Remote Monitoring and Inspection
Drones can provide crucial remote monitoring and inspections done without human intervention on the area being monitored or patrolled. The drone’s aerial capability allows it to inspect structures that are difficult to reach from the ground.
Researchers at the University of Maryland and the University of Zurich equipped a drone with event cameras and a sonar system to make it capable of detecting and dodging objects thrown at it. These drones can be used to intervene in an high risk environment without putting police force in the harms way.
Robotic Police Force
Huntington Park Police Department unveiled its latest recruit, a 400-pound robot known as HP RoboCop. It’s been patrolling California’s Salt Lake Park—and helping to make arrests—ever since. Just imagine a bunch of this robots working in unison to layout a security blanket around the city, this can very seriously reduce the crime in the area. This robot in particular has helped the police department round up criminals with evidence in 6-8 hours!
Without a certain level of trust and acceptance, smart, innovative police services in the community cannot deliver on their promise. Where citizens feel that they are subject to surveillance without being able to feel safer, they will not see the benefit of AI technology for policing.
As the capabilities of artificial intelligence technology grow and predictive policing becomes more of a reality, community trust also needs to grow. AI will only reach its full potential in policing when trust and technology truly come together.