Last month, Las Vegas marked one year since the tragic and unforgettable mass
shooting that targeted an enormous country music festival and became the
deadliest in modern US history. On Sunday, October 1, 2017, gunman Stephen
Paddock opened fire on a crowd of concert-goers at the Route 91 Harvest Music
Festival. A massive 58 people were killed, including 36 women and 22 men.
Another 851 were injured, both by gunfire and during the panic that
resulted in the crowded space on the Las Vegas Strip, even though the shooting
occurred in a short ten-minute span, from 10:05 to 10:15 PDT.
Paddock, a 64-year-old
who was once an auditor and real estate businessman, had little interaction
with law enforcement, except for traffic citations. He was, reportedly, a heavy
drinker and a solitary soul who, as a high-stakes gambler, placed bets at a
high enough level to generate free benefits such as rooms and meals. He had
lost a significant amount of his wealth in the two years leading to the
tragedy, due to his familiarity with casinos in Las Vegas. His exploits and his
background quickly became the stuff of Twitter tweets and Instagram and
Facebook posts and was widely proliferated, even without the assistance of an
engagement service like Social Gone Viral.
What can the Las Vegas
tragedy teach us?
Such tragedies have,
unfortunately, become more commonplace than we might like to admit. The
question is, in the absence of changes to gun control regulations, are there
alternative solutions to thwarting potential acts of domestic terrorism and
large-scale safety threats? Is there a way that governmental agencies can
immediately assess and subsequently respond to potential issues? What if
surveillance efforts at large-scale events were made safer and easier through
the use of intelligent image searches and facial recognition
software that allow for improved
safety measures?
From sporting events to
casino surveillance, from entering a music event to crossing the threshold of a
hotel, biometric analysis can recognize distinct faces in a crowd and help law
enforcement identify suspect individuals as soon as they enter an area or a
building. Utilizing the expertise of artificial intelligence designers and
security specialists, technology is allowing a one-to-many facial recognition
process that will provide consistent, on-demand, and real-time service to
governments, law enforcement agencies, and others.
Not only can facial
recognition software help prevent catastrophic events, but it may also help
investigators catch criminals after the fact. As the use of facial
recognition software becomes more prevalent, the hope is that potential
criminals, knowing that the chances of getting away with it are becoming more
and more limited, won’t attempt any wrongdoing in the first place. But even if
a tragedy occurs, a facial recognition system can save law enforcement
countless hours of manual video and comparative analysis. It can capture and
evaluate as many as 100 facial profiles in a single image, speeding up
investigatory procedures. These facts indicate that artificial intelligence is
easily leveraged for both governmental and security needs.
Where might facial
recognition be used?
Facial recognition
technology is more common than many realize and when used widely and wisely, it
is capable of protecting innocent individuals and deterring would-be criminals.
Banks, for example, could easily benefit from the implementation of cameras in
physical locations that would allow investigators to apprehend criminals if
robberies occur and to discourage them.
Facial recognition can
also be used online in a mobile banking capacity, allowing transactions to be secured at a
glance rather than through a more traditional format. In this way, imposters
attempting to access consumer accounts or assume someone else’s identity will
be unable to complete fraudulent transactions, even if they have the customer’s
credentials such as account numbers or passwords or PINs. The analysis systems
will scan faces, turn them into a code, and determine the validity of a
person’s identity based on factors such as eye shape, eye width, jaw shape and
size, and nose position.
Casinos, too, have found
value in the use of facial recognition software. In places where significant
amounts of money exchange hands and flow easily, criminals can be found en
masse. In gambling cities like Las Vegas where criminals like Stephen Paddock
lurk, Casino.org reports that many types of crimes, including burglary, robbery,
assault, arson, and murder are prevalent. Traditional cameras may capture some
events, but facial recognition software can help detect individuals who have
cheated casinos before or who frequent them regularly. Installing systems in
areas like these can deter crimes like theft or assault if criminals are aware
that they are more likely to be caught- not only on tape that can be analyzed
manually but by the use of sophisticated software that examines and evaluates
hundreds of faces quickly and easily.
Do you feel that such
tragedies warrant the use of facial recognition software in public places?
Share your opinion here.
