Facial recognition
Fit for purpose?
Sam Fenwick discusses a variety of potential benefits and issues if public safety
agencies adopt the use of facial-recognition technology across the board
The use of technology often falls into two
categories. The first is using it to improve the
efficiency and speed at which we carry out
certain tasks. The second, and potentially far
more interesting approach, is to use it to do
things that were previously impossible.
In retrospect, one of the most profound examples of the
latter in policing was the introduction of speed cameras. For
the first time, people in large numbers started to be fined,
and in some cases stripped of their driving licences, based on
evidence that was recorded automatically.
The key point here – for reasons that I’ll get to – is that
the trigger to gather the evidence (and indeed determine that
a crime has happened in the first place) was also automatic.
With that in mind, given the rise of both facial recognition
and the Internet of Things (IoT), the obvious question is
to what extent is it desirable and practical to extend this
approach within policing?
Jaywalkers beware!
Last year, news broke that traffic police in Shenzhen, China
were working to add functionality to their facial-recognition
system. This was to name and shame jaywalkers, as well as –
potentially – automatically fine such offenders.
It is therefore easy to imagine this being extended to other
crimes, possibly in combination with additional metrics and
data sources such as gait analytics, mobile phone data and so
on. At the same time, the dispatching of a drone to gather
footage at different angles for more serious offences could also
be an option. These could include public order and criminal
damage offences, along with anti-social behaviour.
Clearly, this approach has many potential benefits. For
instance, the perpetrator of a crime that might have otherwise
gone either unwitnessed or unreported could be identified
and punished automatically.
This would require little in the way of police resources, as
no police officers would need to be physically present, while
a minimum of investigative work would also be required
(obviously depending on the severity and complexity of
the offence).
There is also the potential to use video analytics to detect
patterns of suspicious behaviour to detect pick-pockets, drug
dealers and so on. Artificial intelligence is good at gradually
learning what constitutes ‘normal’ behaviour, and then
reporting when deviations from it occur.
Of course, all this is far easier said than done from a
technological point of view. What’s more, shifting in this
direction would have huge implications for society as a whole,
particularly in relation to the criminal justice process. It
would also – in the UK at least – need to be considered in the
shadow of the core Peelian principles of policing by consent.
With that in mind, such systems would need to be
implemented in such a way that police officers’ compassion
and discretion are not designed out of the equation.
Neighbourhood policing is of course also core to the British
policing model.
At the same time, it is also important to bear in mind the
corrosive effect of small offences going unpunished due to a
Facial-recognition
and video analytics
are challenging
at both a
technological and
a societal level
20 www.criticalcomms.com July 2019
Adobe Stock/metamorworks
/www.criticalcomms.com