There’s a new Sheriff in town – AI!

AI tool that can do '81 years of detective work in 30 hours' is being trialled by police in Avon and Somerset.  Makes sense. Its ability to deal with huge amounts of structured and unstructured databases, along with recent agentic capabilities make it a useful tool, It could save huge amounts of dull labour and raise conviction rates.

The numbers are astounding. An evaluation showed it was able to review the evidential material in 27 complex cases in just 30 hours - which it is estimated would have taken up to 81 years for a human to do. It is not as if it will be taking jobs as many countries have a shortage of police officers and it takes years of training to become a detective. The point is to increase the quality and speed of detection.

Sector specific

Keynoting at conferences where the audience has absolute focus in a sector is sometimes better than the general conferences. They are keen to find out how AI can help them with their specific problems and goals. It leads to more practical discussions and questions. In the last year I have given presentations to national tax, police, waste management, recruitment, immigration, HR, military and global consultancy organisations, also specific online learning companies. They all have one thing in common – they already use AI, sometimes extensively, at an operational level, and know they need to get to grips with this technology in other areas, as it is the technology of the age. I will do a short series of articles on specific sectors, as I’m on the road in several countries giving more of these over the next few weeks. 

First up – the police, as I’ve given three keynotes to national police Colleges in the UK and Netherlands and for the EU. There’s a new sheriff in town – AI! Well not really, as the police are pioneers of AI. 

AI in policing

ANPR (Automatic Number Plate Recognition) was invented in UK in 1976 and in use since 1979. It truly revolutionised policing and now the UK has 60 million ANPR ‘reads’ a day. It acts as a deterrent to reduce crime and catches everything from stolen vehicles and uninsured vehicles to major crime and counter terrorism. Then there are its more mundane uses which we use every day in car parks, tolls and logistics tracking. It is a great example of the massive benefits that can accrue from a simple piece of AI, in this case character image recognition, something that has been around for decades.

CCTV was first used in UK in 1960 for crime prevention and the detection of offenders. Again, with face recognition, it can and has been used to identify serious offenders such as murderers, sex offenders and figures in organised crime. It is now essential for crowd control and public order. It is often combined with face recognition, not only from CCTV but also mobile phone footage, dashcams and doorbells. 

It is also used when you cross borders on immigration gates. I haven't spoken to a border guard coming back to the UK for many years. It has been automated. In fact, humans are now the main point of failure. My wife cannot enter the US because of a poorly trained TSA guard at LAX, who knew neither the rules nor had the ability to solve the simple problem (a long story - see end of this article). When you slide in your passport at an automated gate, it compared your face with one stored on the chip on your passport. This has literally eliminated the need for thousands of border control agents. Why? It is accurate. Finger printing will be introduced across the EU this year, again using AI. The same can be done for documentation.

There is a very long list of other uses, including crime analysis and investigation, forensic analysis, traffic management, drone surveillance, cybercrime detection and social media monitoring. I could go on but you get the idea. AI is already deeply embedded in crime deterrence and detection.

Of course, AI may create its own problems with scams and deepfakes. This will undoubtedly happen. My own view is that this is less a threat than people think. Deepfakes are usually moderated out by AI on social media by AI, as it polices itself. Yet audio and video are increasingly used to scam people, to make the scammers seem authentic. At this level the police need training on that topic.

One of the great things about these events are the concrete projects, real projects used in training that have been applied or are underway. I have seen a range of projects that really were stunningly specific and useful – in forensics and the general training of police officers. 

Productivity

You walk away from such events knowing that AI could result in massive savings in productivity, especially as policing is a text-laden process, the bit no-one likes – the paperwork. Using AI to create, improve and just do administrative tasks not just faster but better would be straightforward. 

Transcription

Transcriptions alone could save millions. Throughout the police investigation process, and in courts, statements are taken and proceedings recorded. This is a massive opportunity for automated transcriptions. 

Translation

Translation in police stations and out on the streets is another. Using real translators is expensive and difficult logistically. Real time translation to and from a massive range of languages is now possible.

Training

But it is in training where they have most to gain. These are people with increasingly complex and difficult jobs who could do with all the help they deserve. From learner engagement through learner support, content creation, personalised learning, feedback, formative and summative assessment, along with performance support, almost every aspect of training could use AI.

The police have a tough job that requires a LOT of training. They have to deal with aggression, violence, abuse, mental illness, drugs, alcohol, murder, even death. This requires an astonishing array of knowledge and skills. 

Simulations and scenarios

AI could help alleviate that problem with a focus on scenario-based learning, using AI to design and build lots of good dialogue-based scenarios. This is the real interface between the police and the public. I’m told that new recruits are often ill-prepared for the situations they find themselves in, unable to talk things down, too ready to reach for the pepper spray. This type of training can be done well through lots of exposure to scenarios that give pre-training before you hit the streets.

Performance support

I had several interesting conversations afterwards around the use of simulations for driver training, 3D mixed reality projects using VR in forensics, and the possibility of AI improving administrative productivity. The one topic I felt was most interesting was the idea that AI can be used for performance support. Policing is all about being out there, doing things in the real world, difficult things. It needs a wide array of skills, a fundamental and accurate knowledge of the law, high-level interpersonal skills (especially de-escalation), physical handling skills, high-level driving skills, communication skills, medical skills… I could go on but you get the idea.

The one thing that is missing in the current model is performance support for training out there, in police stations, in cars wherever. There can be no doubt that most police officers and back-office staff learn a lot on the job from colleagues and more experienced staff. This seems like the perfect context for an AI-driven performance support system. It could deliver, for example, usable advice, whether needed in the field, on the law, processes, procedures and so on, as real checklists, job aids and support. We have been working on suc systems in healthcare, the military and the Police in Europe.

Federal problem

One of the problems the police face is the federal and fragmented nature of their organisation. The United Kingdom has a total of 45 territorial police forces. This includes 43 forces in England and Wales, the Police Service of Northern Ireland (PSNI), and Police Scotland. Additionally, there are several special police forces that operate across the UK, such as the British Transport Police, the Ministry of Defence Police, and the Civil Nuclear Constabulary, among others. However, these special forces have specific jurisdictional responsibilities rather than geographic ones. This makes communal and well-funded projects difficult. There is a real need for a mechanism for at least sharing or projects that can be centrally funded by all, then distributed back out to save time and money.

Conclusion

I wished I had had more time with these people. They know about the need for good training. What they need is help in delivering that training more effectively, lifting themselves out of classroom PowerPoint, into more realistic training that results in real transfer to the job on the street.