London Police Uses Palantir AI to Investigate Its Own Officers and Hundreds Get Caught
The Metropolitan Police of London just did something few expected to see this soon: it used an artificial intelligence tool developed by the controversial company Palantir to investigate its own officers and identify those breaking rules, engaging in corruption, or even committing serious crimes.
The results surprised even the biggest skeptics.
In just one week of operation, the software combed through the department’s internal data and uncovered a significant volume of irregularities among hundreds of officers, ranging from attendance violations to serious cases of corruption, abuse of authority for sexual purposes, fraud, sexual assault, and misuse of police systems.
Three officers have already been arrested.
The investigation placed the Met Police at the center of a debate that stretches far beyond the borders of the United Kingdom. When technology starts watching the ones who watch us, the whole game changes. 🤔
How Palantir Entered the Picture
Palantir Technologies is far from a newcomer to the world of surveillance and data analysis. Founded in 2003 in the United States, the company has provided artificial intelligence and predictive analytics solutions to security agencies, governments, and military forces around the globe. The company name is actually a direct reference to the far-seeing magical stones from The Lord of the Rings, and that choice was no accident: Palantir’s mission has always been to see what the human eye cannot see on its own.
The company, however, comes with considerable baggage. Palantir has well-known connections to ICE, Donald Trump’s immigration enforcement program in the United States, as well as to Israeli military forces. Recently, British lawmakers demanded the cancellation of a 330-million-pound contract between Palantir and the NHS, the UK’s public health system, calling the deal disgraceful. In other words, the company arrived at the Met Police already surrounded by controversy.
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In the case of the Metropolitan Police of London, commonly known as the Met Police, Palantir developed a platform capable of cross-referencing internal departmental data at a scale and speed that any human team would take months, or even years, to accomplish manually. The tool has access to attendance records, shift schedules, internal communications, disciplinary history, mandatory declarations, and other operational data about the officers. In theory, everything an experienced auditor would analyze, but in a tiny fraction of the time.
This implementation is part of a broader push by the Met Police, which recently entered negotiations to acquire additional Palantir technology aimed at assisting criminal investigations and automating intelligence processes. The London police force has also adopted other technologies like drones and live facial recognition as part of its modernization strategy.
The Investigation Numbers in Detail
The platform’s findings covered a wide spectrum of irregularities, and the numbers released by the Met Police itself help illustrate just how big the problem hiding inside the department really was.
Corruption was the most consistently detected offense by the software. According to data cited by the Met, 98 officers are being evaluated for misconduct related to abusing the IT system that manages police shift schedules. These officers allegedly manipulated the system for personal or financial gain. Beyond those 98 formal cases, another 500 officers received preventive notices related to the same irregularity, which indicates the problem was far more widespread than any traditional inspection had managed to detect up to that point.
Regarding office attendance rules, the software identified that 42 senior officers, holding ranks ranging from chief inspector to chief superintendent, were being assessed for gross misconduct. These senior officers had reportedly claimed on multiple occasions to be in the office when they were actually working from home or simply absent for extended periods. Met Police guidelines require office attendance to stay at or above 80%, and these officers were systematically violating that rule.
Another finding that raised eyebrows involved Freemasonry. Within the Met Police, membership in organizations like Freemasonry is considered a declarable interest, meaning officers are required to formally disclose that they are members. Palantir’s software found that 12 officers are under investigation for gross misconduct for keeping their Freemasonry affiliation secret. Another 30 received preventive notices for suspected, though not yet confirmed, undeclared membership in the organization.
In the most serious cases, the Palantir platform flagged situations involving abuse of authority for sexual purposes, fraud, sexual assault, misconduct in public office, and misuse of police systems. Three officers were arrested as a direct result of information uncovered by the system. That number may seem small in absolute terms, but it represents a significant milestone considering the operation had only been running for one week. The speed at which the system generated evidence solid enough to support actual arrests is, on its own, a striking data point.
What the Met Police Commissioner Said About the Operation
Metropolitan Police Commissioner Mark Rowley spoke publicly about the use of the tool and made a point of framing the initiative as part of a broader effort to modernize and raise standards within the department.
Rowley stated that criminals are constantly adapting how they use technology, and that policing needs to keep pace, not just on the streets but within its own organization. According to him, by bringing together information the force already legally holds, it becomes possible to spot risks earlier, act faster, and be fairer and more consistent in the application of disciplinary measures.
The commissioner also emphasized that the vast majority of Met officers and staff serve London with dedication and integrity, and that those professionals rightfully expect the department to act firmly against those who abuse their positions or undermine public trust, especially in leadership roles.
The Met Police stated that the software will help build trust, reduce crime, and raise standards across the United Kingdom. The department cited the introduction of other technologies such as drones and live facial recognition as examples of tools already contributing to keeping people safe and reducing crime. Combined with new vetting powers, the force believes it now has the tools needed to remove those who should not be in policing and strengthen the institutional culture going forward.
The Debate This Story Raises
When a police department uses artificial intelligence to monitor its own members, questions arise that do not have simple answers. The first is about privacy: how far does a public servant’s right to privacy extend in the exercise of their duties? What data can be collected, for how long, and who gets access to it? These questions are already debated in contexts like employee surveillance in private companies, but they carry a different weight when the person being monitored is a government agent with access to sensitive citizen information.
Another layer of the debate involves trust in algorithms. Artificial intelligence systems, no matter how sophisticated, make mistakes. A false positive generated by the Palantir platform could expose an honest officer to an unjust investigation, with real consequences for their career and reputation. AI models are trained on historical data, and if that data carries biases, the system can reproduce and even amplify those distortions. Transparency around how the algorithm works and what criteria it uses to flag irregularities is essential for the tool to be considered legitimate.
The choice of Palantir as a technology partner adds an extra layer of complexity to the debate. The company’s track record with immigration agencies, military forces, and public health systems generates discomfort among parts of the general public and the political class. It is not hard to see why: when a private company with that profile gains access to a police force’s internal data, the question of who watches the watchman becomes even more pressing.
On the other hand, there is a powerful argument on the opposite side: corruption within police forces is a real, well-documented problem with serious consequences for society. Traditional internal affairs mechanisms often fail, whether due to lack of resources or internal conflicts of interest. The Met Police itself has a history of scandals and public trust issues that have driven reforms in recent years. In that context, a tool capable of identifying irregularities quickly and at scale may be exactly what many institutions need. The challenge is ensuring it is used responsibly, transparently, and with proper human oversight.
AI and the Importance of Human Decision-Making in the Process
It is important to highlight that artificial intelligence does not arrest anyone on its own. What it does is identify patterns, cross-reference information, and flag anomalies that deserve human attention. The decision to act on those signals still goes through investigators and competent authorities. Even so, the ability to process massive volumes of data and deliver concrete leads in such a short time represents a real shift in how institutions can conduct their internal audits.
This point is especially relevant because there is a huge difference between a system that suggests and a system that decides. The Palantir platform, based on what has been disclosed, functions as a screening and risk identification layer. The people making decisions about whether to investigate, notify, or arrest are still flesh-and-blood human beings. Maintaining that distinction is essential to ensure that the use of AI in such sensitive contexts does not slide into a dangerous zone of unchecked automation.
What This Means for the Future of Institutions
The Metropolitan Police of London case with Palantir is not an isolated episode. It is part of a growing trend of adopting artificial intelligence tools in institutional settings, from tax auditing to corporate conduct analysis, hiring processes, and public sector performance evaluations. What changes here is the sensitivity level of the data involved and the potential impact of an error.
For other countries, including those with large public institutions and complex bureaucracies, this movement serves as both a wake-up call and a source of inspiration. Institutions that deal with power and public funds need effective oversight mechanisms, and technology can be an important ally in that mission as long as it comes with clear regulation, solid data governance, and transparency for the public. The investigation conducted at the Met Police shows that it is possible to use AI to strengthen institutional integrity, but it also makes clear that the risks need to be taken seriously before any large-scale implementation.
The Met Police appears to be going all in on this path. Beyond the internal audit tool, negotiations to acquire additional Palantir technology for criminal investigations suggest the department sees AI not as a one-off experiment but as a strategic pillar of its operations in the coming years. Whether that bet will prove to be the right call or generate new problems, only time will tell.
What is at stake here is not just technology. It is trust. And trust, once lost, is far harder to rebuild than any system bug. 🧩
