Oyoon (Dubai city-wide AI surveillance network)

WHAT THE SYSTEM ACTUALLY DOES

Oyoon — Arabic for 'eyes' — is Dubai Police's programme for putting artificial intelligence behind cameras the emirate already had, rather than a single new camera network.

Feeds from cameras at tourist sites, on the Metro and wider public transport, on the road network and at public buildings are pooled into a Dubai Police command centre. Software converts passing faces to templates and compares them against police records, reads vehicle registration plates, and analyses behaviour, raising an alert for a human operator when it believes it has found a wanted person or vehicle.

Dubai Police operate it with partner bodies. Gulf News reporting names the State Security Agency, Dubai Municipality and the Roads and Transport Authority among them, which is what allows cameras owned by transport and municipal authorities to feed a police system.

THE NUMBERS, AND WHERE EACH COMES FROM

The programme was launched in 2018. In March 2019 Gulf News quoted First Lieutenant Ali Al Shehi of the Dubai Police Criminal Investigation Department saying the cameras 'helped arrest 319 suspects in different areas in Dubai through their automatic facial recognition technology' over the preceding year. The same report gave 5,000 cameras in the Metro system alone.

In July 2021 Gulf News reported that Sheikh Mohammed bin Rashid Al Maktoum had been briefed on the programme alongside Lieutenant General Abdullah Khalifa Al Merri, Commander-in-Chief of Dubai Police, and quoted the ruler saying Dubai is monitored by more than 300,000 cameras. The same report attributed a fall in emergency response times, from 6.46 minutes to under three minutes, to the smart system.

The Oxford Institute of Technology and Justice, in a country study current to March 2026, describes Oyoon as using facial recognition and behaviour analysis to identify suspects and track vehicles and licence plates across more than 5,000 cameras covering tourist sites, public transportation and traffic, and records the 2018 arrest figure.

These figures are not one series and should not be read as one. 5,000 is a Metro estate, 300,000 is a whole-emirate figure given by the ruler, and the two are five years apart. The 319 arrests are a single year, 2018, and no later arrest figure has been published.

THE LEGAL POSITION IS THAT THERE ISN'T ONE

The Oxford study states plainly that there is no dedicated legislation in the UAE targeting the use of AI in criminal proceedings. What exists instead is general policy: the Charter for the Development and Use of AI (2024), the AI Ethics Principles and Guidelines (2022), and the AI Adoption Guideline in Government Services (2023). None of these is a statutory authority for police biometric identification, and none creates a route of challenge for a person wrongly matched.

No oversight body specific to the system has been identified, no published watchlist criteria exist, no retention period for face templates or plate reads has been made public, and no accuracy or false-match rate has ever been released. That is a longer list of unknowns than this catalogue records for most comparable networks.

THE CASE FOR IT

Dubai's authorities make an argument that deserves stating rather than dismissing. The emirate has an unusually large transient population — tourists, transit passengers and short-stay workers — and a correspondingly thin base of local knowledge for conventional investigation. A centralised camera network with automated matching is a way of substituting technical reach for that. The published response-time improvement, from 6.46 minutes to under three, is a real operational claim about getting officers to incidents faster, and Dubai's low recorded crime rate is used domestically as evidence the approach works.

It is also a system its operators talk about openly. The ruler's own briefing was publicised; the arrest figures came from a named officer. Compared with jurisdictions that deny operating facial recognition at all, Dubai's willingness to describe the programme is a form of transparency, if a limited one.

THE CASE AGAINST IT

The transparency stops at the point where it would allow scrutiny. Publicity about capability is not the same as publication of the rules governing it, and none of the documents that would let anyone test the claims — watchlist policy, retention schedule, accuracy testing, an audit of the 319 arrests — has been released.

The absence of dedicated legislation means that a face scanned in a Dubai shopping centre is processed under general government AI guidance rather than any law setting conditions or remedies. In jurisdictions that have legislated, the argument has turned on exactly those conditions. Here there is nothing to argue about.

There is also the question of what a network of this scale does to expression and assembly, which in the UAE is already tightly constrained. A system built to identify wanted persons will identify anyone whose face is on a list, and the composition of that list is unpublished.

WHAT IS NOT KNOWN

The supplier is not established; no source consulted names one. The current camera count is not established — the 300,000 figure is from 2021 and refers to the emirate rather than to Oyoon specifically. Whether facial recognition runs live across the whole network or only on selected feeds is not established. Whether any person has been wrongly identified is not established, because no mechanism exists that would make such a case public.

EVIDENCE BASE

No Dubai Police publication was read directly for this record; dubaipolice.gov.ae could not be reached. The record rests on official statements relayed by reputable regional journalism, and on one academic country study. That is a weaker footing than this catalogue prefers, and the gap is recorded here rather than papered over.