Beth

That's right.

The research examining 40 years of CCTV implementation provides very clear evidence of a deterrent effect.

Across all categories, video surveillance leads to an overall average crime reduction of about 13%.

It depends very heavily on the context.

For instance, in high target areas like parking facilities, which are often targets for vandalism and theft, the studies show a significant reduction of 50% in theft-related crimes.

50.

And in specific monitored high traffic areas of London, you see reductions in general theft and property crime ranging from 30 to 40 percent.

The cameras are a visible deterrent.

They cause criminals to shift their activity elsewhere, protecting the monitored zone.

It provides the indisputable, non-perishable evidence that police need to identify suspects, reconstruct complex events, and secure convictions.

I mean, take the example of the Chicago Police Department's network of over 30,000 surveillance cameras.

The sources confirm this network has been a critical investigative aid in over half of all their homicide investigations.

It does.

And we can't ignore the idea of predictive policing, these AI models that aim to step in before the crime even happens.

Right.

Machine learning models analyze these massive data sets, everything from historical crime maps to weather, school schedules, local events.

And they predict high risk areas and times with very high precision.

This allows law enforcement to deploy their resources much more efficiently.

That's a great question.

AUC stands for area under the curve, and it's basically a measure of prediction accuracy.