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Automating Critical Environments
Are you tired of hearing about Artificial Intelligence
(AI) yet? Did people in the 19th century grow tired
of hearing about the wonders of the combustible engine,
and how it would surely revolutionize modern
life… until it actually did? One can imagine that they,
those skeptical of the combustion engine’s positive effects, soon experienced
the force-multiplying benefits of traveling from point A to
point B more efficiently—and with wind in their hair to boot. The
goal of AI is not to replace humans, but to enhance human agency,
helping us to accomplish more, better and faster.
While, admittedly, the fervor over AI can be a bit much, but the
more reasonable and measurable expectations around improving security,
safety and efficiency through AI should not be understated. It
strikes me as odd that as we rush to replace traditional vehicles with
autonomous ones, there is a reluctance to automate the critical spaces
and environments that we find ourselves spending most of our waking
time within—work, education, and the various enterprise campus
or facility settings.
On average, people spend 100 hours a year commuting to and from
work, compared to nearly 2,000 hours spent at work. Is it possible that
the way we currently perform important tasks within critical environments
will, once AI solutions have been implemented, make about
as much sense as choosing to ride horseback from San Jose to San
Francisco rather than driving (or being driven there autonomously)?
Where to Begin with AI
As key stakeholders look to implement AI into their workflow, many
find that security and safety is a commonsense place to begin. There
are three areas currently saturated by humans engaged in manual
processes that, when augmented by AI, provide immediate results
and quantifiable data from which to further justify large-scale AIcentric
deployments. The first, and most visible form is that of a security
guard observing streaming security monitors. While the optics
of a security guard attentively staring at multiple screens may convey a sense of security, and provide a nominal amount of enhanced perimeter
security, in reality a human’s ability to perform this mundane,
but critical, task is severely limited.
A study done by the UK Police Scientific and Development
Branch (PSDB) concluded that a person tasked with monitoring
multiple video screens, with the goal of identifying a person holding
an umbrella on a busy street, had accuracy scores of 85 percent, 74
percent, 58 percent and 53 percent when viewing one, four, six and
nine monitors, respectively. The study also found that the person was
extremely less-likely to detect an object of interest in the background
area of the field of view.
Even more alarming is how humans fare when tasked with manually
reviewing collected video in post-event situations. While each investigator
in the areas of public safety and law enforcement spends
an average of 1.5 hours/week reviewing video, which equals a whole
month of their annual salary, it’s been found that after only 22 minutes
of sustained video review humans lose 95 percent of our visual
acuity. Basically, a literal red herring could pass by the screen and a
human wouldn’t notice. When corporate security professionals are
attempting to resolve employee, guest, or vendor related incidents,
this fact alone could seriously hinder the time-to-resolution in critical
situations.
Finally, access management is the next logical place to implement
AI-powered solutions. The threats to a physical place in human form
are various. People are fired from or quit their jobs every day, and
sometimes the parties are not parting ways amicably. As we’ve seen
far too often, those individuals may wish to return to their place of
employment with ill-intent. Maybe it isn’t a former employee, but a
third-party vendor, a scorned lover, or a rogue individual with imagined
political differences to avenge—the list can go on. When the termination
is complete, HR then sends a notice to the security team,
who then creates a physical BOLO report and... will keep a vigilant
eye out for that person?
Augmented Intelligence
Security cameras, whether fixed or mobile, augmented with AIpowered
solutions can provide the crucial first step in mitigating
overwhelming physical risks and financial losses that accompany unwanted
access by bad actors, through biometric verification, like face
recognition, coupled with badge-access safety protocols. In addition
to keeping critical assets, like employees, safe while inside the walls of
the premises, when someone is leaving work late at night, their face
should trigger an auto-response from security to provide offer an escort
to the person’s car. It should be automatic, effortless. Similar to
driving from point A to point B.
It is far too easy to bypass security measures at points of entry
and egress by either swiping a stolen ID badge, waiting for a door
to be opened and slipping in, or using a more sociable technique—
simply greeting the familiar security guard like one wasn’t just fired
the day before. Instead, AI augments a security team’s effectiveness
through automated Watchlists, BOLOs and Blocklists that work 24/7
and never tire or look away from the monitor. There is no judgement
call made on the part of a security guard, because the person was
nice, the AI only knows to do what it’s told: alert security when the
person face is detected.
Securing entryways through AI-powered solutions like video
analytics gives the security team an unparalleled control over access
points. Currently, the manual process involved in each of these
scenarios is fraught with inefficiencies. Even something as seemingly
harmless as tailgating, or piggybacking (the act of entering a secure
entryway without badging-in correctly) can lead to obvious safety
concerns and, according to one survey of enterprise security executives,
cost the company anywhere from $150,000 to “too high to measure”
in losses.
Frictionless, face recognition-powered access management not
only speeds the process, but eliminates the vast majority of accessrelated
security and safety issues.
Where to Begin?
Returning to the autonomous vehicle comparison, the parallels in
production and safety, were we to augment human agency and automate
our critical environments through AI, are myriad. According to
research done by Business Insider, if 90 percent of cars on roads were
autonomous, accidents would plummet from 6 million to 1.3 million,
annually. Thanks to better, more efficient driving, CO2 emissions
would decrease by 300 million tons per year. And finally, commuters
would get to their destinations faster because of less traffic congestions,
resulting in 1 billion hours, every day, that could be repurposed
for higher-level, more productive activities.
Safer, more productive, and a higher quality of life—for 100
hours of the year. By automating critical spaces with AI, stakeholders
in charge of these spaces will reap the same benefits and produce
the same types of results.
So how does one dive in? Start small and with reasonable expectations.
As covered, deploying AI-powered solutions to better secure
perimeters, improve investigations, and shore up access management
security protocols provides immediate results and data from which to
evaluate the efficacy of the investment. AI-powered solutions should
not just be another line item on the budget, but be a force multiplier
for security, safety, and productivity now and in the future. What follows
are three considerations to keep in mind when evaluating solutions
to best fit your needs:
Extensibility of tech. Will the solution work with all of the components
of a security stack? In the case of video analytics, one must ensure
that the tech will work on the different types of cameras currently
in use, plus any cameras that may be added to the stack—drones,
wearables, dash cams, etc. As mobile cameras become the new norm,
being able to extract actionable intelligence from every sensor available
is a no-brainer.
Control over the AI. Many AI deployments fall flat in the long
run, and end up causing more user headaches than triumphs, as a
result of the limitations of out-of-the-box AI-solutions. While the
standard offerings may be powerful, it is important for each customer
to be able to create case-specific algorithms that truly meet the varied
needs you may encounter. Solutions that are powered by deep learning
AI are able to offer the customer unparalleled control over their
outcomes.
Policy and privacy. Protecting the privacy and rights of those affected
by the AI-solution is of utmost importance to all key stakeholders.
A company should have in place a use-policy for biometric
data that can be easily accessed by all employees. In addition, partnering
with companies that are committed to training their algorithms
with unbiased data sets, and that have clear trust and privacy policies
in place, will ease the transition to automating the environments that
people inhabit on a daily basis.
By adding AI to security and safety processes, it is possible
to automate the critical environments of our
workplaces, schools, and facilities while simultaneously
increasing existing human agency in
order to get more done, more efficiently, and
with better results.
This article originally appeared in the March 2019 issue of Security Today.