That was the first thing I thought when I saw the BBC article (at https://www.bbc.com/news/articles/ckpdg4pl7pgvo) with there title ‘Police using AI risks making discrimination worse, researchers warn’, the article itself was three days old, but I have had a few things on my plate, it is not the greatest excuse, but it happens to be the truth. We are given “The growing use of AI in policing risks increasing discrimination against minority groups, researchers have warned. Studies suggest that predictions of future crime hotspots may be based on biased data, which can magnify existing prejudice and create a dangerous feedback loop.” I couldn’t have said it better myself and but it is also based on settings that are more true than anything the truth could bring, because (as I have said over and over again) AI does not (yet) exist. It is mere predictive analytics and that requires data moreover it requires validated and verified data, the outcome in any different setting is what we call the GIGO law (Garbage In, Garbage Out) and that pretty much spells inaccuracy, bias and outright discrimination. And we are given “This would involve checking the data that forces use to find and remove any bias, according to Dr Carolyn McKay, an associate professor and researcher in digital justice at the University of Sydney Law School.
“The public functions of state policing ought to be subject to human oversight and scrutiny,” she says.” This could be the start, but until the data is thoroughly scrutinized the outcome of these predictive models are at best debatable and in the worst case a mere blanket of discrimination, although the policing parties will cover this with ‘Mister X’ looked at the data and we believe it is accurate and when the first case comes where we validly can deny the truth of it, the class actions will come calling. Leave it to any lawyer to see the business end of wrongful convictions and as I see it, that is the only path that will be seen as merit. The article gives it in a different shape, but it is the same outcome, here we see “The problem, according to McKay, is that AI systems are trained on data that already contains human bias, and this can lead to self-fulfilling prophecies. Think of AI as a map-maker asked to draw a map of a city they have never visited. They are locked in a windowless room and can’t go outside. All they have are maps that are 50 years old.” Take one mere consideration “London police corruption in the 1980s was defined by deep-seated internal networks, ties to organized crime, and systemic cover-ups within the Metropolitan Police and City of London Police” and anything connected data that is used is mere gap fillers for a bias and discrimination in London alone. Now we get back to the village of Sydney (the one in NSW, Australia) where we see “Police corruption in Sydney during the 1980s was a systemic and deeply entrenched feature of the New South Wales (NSW) Police Force, particularly within vice, drug, and detective squads in areas like Kings Cross” now these two villages were not sanitized over a day (or even in years) that means that any documentation is tainted with ‘accidental’ inaccuracies and this goes on for close to two decades. Consider that tainted data to be the beginning of predictive analytics and you have yourself a massive amount of class actions and personally hit people demanding representation and even if there is human oversight. How can that person rely on any data he/she sees?
And I am merely pushing two obvious places in the foreground. Take a harbor town like Rotterdam (Netherlands) or even Antwerp (Belgium) or Paris (France) and these are harbour cities, as such there are many parties who ‘disregarded’ and ‘adjusted’ reports and data, the entire setting is drenched in ‘obliging’ failure. But not to worry, the legal system will proceed and defend the damaged parties and their bills will not be cheap (they need a cushy life too) and this setting (as I speculatively see it) will give these lawyers thousands of hours and these players go for roughly $750 an hour, now take that times 50,000? Is anyone seeing the outcome of that failure?
And that is before you see the outcome of class actions that might reach an easy billion in punitive damages. And I have been making sure that the settings of validation and verification was clearly mentioned in most of my ‘fake AI’ articles. And whilst we consider that and in TechCrunch via a writer called Anthony Ha (in LinkedIn), we see ‘AI delivers ‘zero financial payoff’ to most companies, Apollo economist says’ where we see “AI hasn’t benefited the bottom line of any big corporations outside the tech industry, according to a note recently published by the chief economist at Apollo Global Management (the private equity giant that used to own TechCrunch). Apollo’s Torsten Slok focuses on what he calls the S&P 493 — the S&P 500, minus Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla — finding that profit margins and revenue per worker appear to be flat, with no evidence that AI is improving productivity.
“Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech,” Slok said.” Now take that equation to what some call a failing police force with tools that make things harder, less reliable and legally expensive. That is the setting these police forces are seeing. So whilst ‘some’ made statements, the one that reverberated in my mind was “Masayoshi Son, the chairman and CEO of SoftBank Group, has been the primary SoftBank executive speaking out about the AI bubble. He asserted that global AI infrastructure will require roughly $5 trillion annually and argued that AI will eventually transform the economy to generate massive profits.” The fun part for me was $5 trillion annually and ‘AI will eventually transform the economy to generate massive profits’ but as I see it, AI is 15 years away (at the very least), so who is paying for the $75 trillion? And what profits will be gotten? And the issues of data validity and data verification will not go away and they better start today if they want their boat comes in in 15 years, because unverified and unvalidated data is still junk data. (Punters might call that CCC data) so it is worth less than nothing. So how exactly are profits coming in? Because as I see it, the police will be using that same junk data and the money is gone and no one knows where to find it and to give you an example Reuters gives us “STAR50 Index Collapse: China’s main AI and semiconductor stock index, the STAR50, plunged by 40% in under four months, erasing about $480 billion in market value.” As I see it, hardware is the first to fall and the mentions of “Western markets have experienced milder pullbacks—such as a roughly 6% drawdown on the Nasdaq—as major tech firms and chip giants continue to draw heavy capital inflows and massive infrastructure spending” is as I believe it to be false creations. They merely hide it better and the 5 large investors are covering each other and investing in each other, so when that bubble burst (I personally believe it is already bursting) they make claims of tax write offs and pay no tax for a few years (a speculated view by me).
So in this atmosphere you want the police to use fake AI whilst it is predictive analytics and I am not against predictive analytics, it is a good tool if the data is reliable and that is in too many cases seemingly not the event we are hoping for.
So you tell me, where is my thinking wrong? I worked in data analytics since 1992. I saw the rise of predictive analytics, but the people never trusted this, so someone came and called is AI, but it is not AI, not even close. And no one is thoroughly investigating data validation and data verification, because these two settings is where it all goes wrong, horribly wrong.
So you all have a great day and don’t let my words make it sound gloomy, the news won’t tell you this, but that is them. They are now all about the digital dollars. And the start of this article was given to you by young British science writer Adrian Dredge wrote about the potential pitfalls of AI and policing. The essay won the 2026 Young Science Writer Award, chosen each year by the Association of British Science Writers. A man I do not know, but he was awarded the honour by people who know things, so that is seemingly good enough for me.
