In his award-winning essay, young British science writer Adrian Dredge wrote about the potential pitfalls of AI and policing. The essay won the 2026 Young Science Writer Award, external, chosen each year by the Association of British Science Writers. Here is an edited version of the entry.
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. Experts are calling for the use of AI in policing to be reviewed with greater human oversight.
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. 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.
Anyone following the new map would find themselves stopping at walls that were knocked down years ago and looking for roads that no longer exist. The map-maker hasn't made anything new. They have only copied the old maps.
Now suppose the map-maker is handed a list of past crimes and where they took place, and asked to shade in where the next ones are likely to happen. Police then patrol the shaded areas. More crime is recorded there simply because more officers are there to see it.
Extract — continue reading at the source.
