There are two lazy ways to talk about AI in policing.
The first is to say it is obviously sinister. Surveillance. Minority Report. Shadowy tech firms. A giant glowing database deciding who gets nicked next.
The second is to say it is obviously necessary. Crime is complex. Data is overwhelming. Police are drowning in demand. Technology can help. Stop being dramatic.
The annoying truth is that both sides have a point.
That is what makes the row over the Metropolitan Police and Palantir interesting.
London mayor Sadiq Khan has blocked a proposed £50m deal between the Met and Palantir, the US data analytics company. The Met reportedly wanted to use Palantir’s AI technology to automate intelligence analysis in criminal investigations. City Hall raised concerns about procurement, value for money, legal risk, ethics, reputation, and the fact that Palantir appeared to be the only supplier seriously considered.
That is not just a procurement story.
It is the future of public-sector AI arriving in the most British way possible: through a row about process, paperwork, public trust, and whether anyone remembered to make it look legitimate.
Policing does need better tools
Let’s start with the uncomfortable bit.
The Met is not wrong to want better technology.
Modern policing runs on data. Crime reports, intelligence logs, phone downloads, CCTV, ANPR hits, digital evidence, custody records, case files, officer statements, safeguarding referrals, social media, financial records, body-worn video, call logs, risk assessments, disclosure schedules — endless oceans of information, usually spread across systems that look like they were designed during a hostage negotiation with Microsoft Access.
Officers are not short of things to read.
They are short of time, clarity, and usable intelligence.
That matters. Because buried inside all that admin sludge are patterns, risks, suspects, victims, links, timelines, locations, and warning signs. AI could help find them faster. It could reduce duplication. It could surface connections that humans miss. It could help investigators spend less time wrestling databases and more time actually investigating.
That is not sinister.
That is sensible.
A well-designed AI system in policing could be genuinely useful. Maybe even transformative. Not because it replaces judgement, but because it helps organise chaos.
And policing has plenty of chaos to organise.
But “we are busy” is not a governance model
The problem is that usefulness does not cancel out legitimacy.
This is where public bodies often go wrong with technology. They start from a real operational problem, find a tool that might help, get excited, and then treat scrutiny as an inconvenience.
That will not work with AI.
Especially not in policing.
The police already hold serious powers over the public. They can stop you, search you, arrest you, seize your property, access your data, build intelligence pictures, and make decisions that can change the direction of your life.
So when a police force wants to plug powerful AI/data analytics into that system, the answer cannot simply be:
“Trust us, it’ll be useful.”
No.
Show the public the safeguards. Show the audit trail. Show the procurement process. Show the bias testing. Show the human oversight. Show who owns the data. Show who can access it. Show what the system is allowed to do. Show what it is forbidden from doing. Show what happens when it gets things wrong.
Because it will get things wrong.
Every system does.
The question is whether the failure is visible, challengeable, and accountable — or whether it disappears into the comforting fog of “operational sensitivity.”
Palantir brings baggage
Palantir is not just any software company.
It is a major US tech firm with deep links to defence, intelligence, public-sector data projects, and controversial government work. It already has significant UK public contracts, including with the NHS and Ministry of Defence. Critics have also raised concerns about its work connected to immigration enforcement and military uses abroad.
That does not automatically mean Palantir should be banned from public contracts.
But it does mean the process has to be cleaner than clean.
If you are a controversial company selling powerful analytics into policing, you cannot rely on the pitch being “our tech works.” That is not enough. Public trust is not just about technical performance. It is about democratic consent.
And democratic consent is difficult when the public only hears about the deal once politicians, journalists, campaigners, police leaders, and the company itself are already scrapping over it.
That is the problem.
By the time everyone is arguing, the trust has already gone.
The vendor-lock-in problem
One of the concerns reportedly raised by City Hall was the risk of becoming locked into Palantir’s technology.
That may sound dull.
It is not.
Vendor lock-in is one of the quiet dangers of public-sector technology. A system is introduced to solve one problem. It becomes embedded. Staff are trained on it. Workflows start depending on it. Data moves into it. Other systems connect to it. Then, a few years later, changing supplier becomes expensive, disruptive, and politically painful.
At that point, the supplier is not just providing a tool.
It has become part of the machinery.
That is a big deal in policing.
Because once a private company becomes deeply embedded in how intelligence is analysed, how risk is surfaced, how misconduct is spotted, or how investigations are prioritised, it is not merely selling software.
It is shaping judgement.
That deserves more than a hurried business case and a few reassuring words about innovation.
AI aimed at officers is still surveillance
There is another layer here.
Reports also say the Met had trialled Palantir technology to identify corrupt or poorly performing officers, with examples including dishonesty around computerised systems and undeclared associations. LBC reported that the Metropolitan Police Federation criticised that use of AI, saying it would damage officer trust and morale, while the Met said the trial identified unacceptable behaviours.
This is where the debate gets awkward.
Most people want corrupt police officers found and removed.
Most police officers want corrupt police officers found and removed.
But using AI to monitor staff behaviour still raises serious questions. What data is being analysed? What thresholds are being used? Who reviews the outputs? Can officers challenge the conclusions? Are innocent patterns being misread? Is the system detecting misconduct, or just building suspicion from fragments?
AI does not need to be malicious to be dangerous.
It only needs to be persuasive.
A flagged pattern can become a suspicion. A suspicion can become a PSD referral. A referral can become a career-changing process. And even if the AI is wrong, the human brain has already been nudged.
That is why “human oversight” has to mean more than someone looking at a dashboard and nodding.
This is not anti-AI. It is anti-bullshit.
The lazy response is to frame this as pro-police technology versus anti-police politics.
That misses the point.
AI in policing could be excellent.
It could help solve crimes, link offences, reduce admin, spot risk, identify vulnerable victims, manage disclosure, and make investigations less chaotic. Used properly, it could give officers back time and give the public a better service.
But if the police want AI powers, they need AI legitimacy.
That means open competition where possible. Clear rules. External scrutiny. Public explanation. Proper data governance. Independent testing. Human accountability. And honesty about what the tool does and does not do.
Not because everyone is paranoid.
Because policing depends on consent.
And consent does not survive secrecy, shortcuts, and “don’t worry, we’ve got this” energy.
The real lesson
The Met’s argument is understandable: policing needs to modernise. The data burden is too big, the demand is too high, and old systems are not good enough.
City Hall’s objection is also understandable: powerful AI in policing cannot be waved through on a questionable procurement process with a controversial supplier and vague reassurances about public safety.
That tension is not going away.
In fact, it is probably the future.
Every public service will face the same problem. Hospitals, councils, schools, courts, benefits systems, immigration, defence, policing. AI will offer real gains. It will also concentrate power, create dependency, and make decisions harder to understand.
The question is not whether AI belongs in policing.
It probably does.
The question is whether policing can introduce AI in a way that earns trust rather than demands it.
Because “trust us” is not a strategy.
It is a warning sign.
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