NetworkNewsWire
Editorial Coverage: Police in the United States have used clues
and deductive reasoning to fight crime for more than 175 years.
However, a sea change is occurring as big data and analytics
technology bolster law enforcement efforts in what is known as
“predictive policing.” This isn’t futurist precrime science fiction
from “The Minority Report.” It’s algorithm-based machine
learning/artificial intelligence (ML/AI) software that analyzes
trends to give police an upper hand in crime prevention. Police
departments worldwide are adopting predictive policing technology
in a bid to identify not only perpetrators but victims also.
Knightscope Inc. (Profile) and its
lineup of autonomous security robots ("ASRs") are leading the next
generation of technology-based policing. The company’s
data-collecting robots can use an array of built-in technology to
provide police actionable intelligence to make smarter, faster and
safer decisions. Seeing the demand, companies such as
Axon Enterprise
Inc. (NASDAQ: AXON), Palantir
Technologies Inc. (NYSE: PLTR), International Business Machines Corporation (NYSE:
IBM) and Everbridge Inc. (NASDAQ: EVBG) are
also looking to carve out niches as police forces add predictive
technologies and big data analytics to their arsenal to protect the
public.
- Recognized as a best invention, predictive policing
technologies are increasingly being used by law enforcement and
security forces worldwide.
- Knightscope autonomous robot sentries can collect up to 90
terabytes of data per robot per year, a deluge of data critical to
advancing the future of predictive-policing technologies.
- Comprehensive libraries of data give human officers better
intelligence for prescient, unbiased decisions and strategies.
- Knightscope has the long-term potential for real-time data
uploads for immediate integration into predictive algorithms, a
significant advancement for the technology in stopping crime.
Click here to view
the custom infographic of the Knightscope
editorial.
AdTech Meets Police Tech
Predictive policing made headlines in 2011 when the technology
used by the Santa Cruz California Police Department was hailed by
“Time”
magazine as one of the 50 best inventions of the year. By 2017,
“Time”
detailed how computer programs were used by the Chicago police for
an official police risk score of about 400,000 arrested persons on
a 1-to-500 scale. By this time, many major cities around the
country were using predictive analysis, including with
gang crime
activity in New Orleans.
The concept is simple and akin to other big data analytics
employed with striking reliability, namely advertising. Machine
learning/AI technologies are now commonly used in Adtech to
identify consumer purchasing trends, which are then combined with
location-based technology to precisely target potential customers.
A similar methodology for behavioral trends is evolving to create
policing that is more effective, efficient and proactive, as
opposed to almost always being reactive to crimes.
More Data, More Reliability
Predictive policing is not without its critics, however.
Profiling and discrimination claims have sparked debates about fair
and trustworthy algorithms. Moving forward, the answer is more
data. That’s what Knightscope Inc. brings to the table
with its robot sentries capable of collecting more than 90
terabytes of data per machine per annum.
In an industry where $500 billion is spent globally every year
on public and private security, Knightscope has developed a
game-changing recurring revenue business model for the unrelenting
societal problem of crime. An ideal adjunct to regular protective
details, Knightscope’s autonomous security robots ("ASRs") are a
unique combination of self-driving autonomous technology, robotics
and leading-edge AI that can law enforcement and security
professionals with smart eyes and ears, allowing the humans to do
the decision making faster, smarter, safer, while the machines do
the monotonous, computationally heavy and at times dangerous
work.
Of course, there is a lot more to predictive policing than just
a computer spitting out a probable crime location. Researchers at
RAND, with sponsorship from the National Institute of Justice,
prepared a
research brief detailing some of the intricacies, including a
taxonomy of approaches.
Approaches varied by the amount and complexity of the data
involved.
Knightscope robots have the potential to take security to the
next level. Able to constantly patrol, the robots can collect up to
90 terabytes of data. To lend a little color as to just how much
data that is, consider that a Macbook laptop holds about 1 terabyte
of data and most people never fill that capacity, not even with
phone backups and massive software programs hogging up space.
Furthermore, it is the quality of the data where Knightscope ASRs
truly shines. The robots are loaded with cutting-edge technology
capable of facial recognition, license plate recognition, high
resolution eye-level video, detection of temperature changes and
much more. All of this data is available in real time through the
Knightscope Security Operations Center ("KSOC") user interface that
Knightscope’s clients utilize across the country.
Folding In Real-Time Data
The potential applications for that data represent the resources
that legacy predictive technologies desperately need. Most
solutions today are reasonably good at what they do by using years
of historical data from crimes, combining that information with
other historical data (i.e., socio-economic) and running it through
quantitative algorithms to try to predict locations and times for
potential crimes.
Knightscope provides a unique opportunity to continuously fold
real-time, on-site data into the mix. The result would be much more
powerful algorithms that align with the thesis of RAND on different
approaches based upon volume and complexity of data. Already in use
across the United States, the ASRs are ideally suited for and used
at airports, corporate campuses, hospitals, manufacturing plants,
government facilities, casinos and more. As the company expands,
data sets will become library-esque with the applications for
predictive technologies spanning a broad spectrum from industry
specific to nationwide.
Not Just a Crime Stopper
A deluge of real-time data from Knightscope ASRs could easily
help make decisions that divert crime. It’s not far-fetched to
envision facial recognition and other detection technologies
indicating there is an increased risk of a crime about to happen or
detection of an FBI Most Wanted suspect or an Amber Alert or Silver
Alert. With the upcoming release of the new K7 multi-terrain unit,
the breadth of the predictive domain is only going to get wider.
The possibilities are endless; perhaps one day a Knightscope ASR
could be providing insight on illegal border crossings and drug
trafficking.
Stopping crime in the purest sense isn’t the only thing that can
be realized through AI and predictive policing. Saving innocent
victims at crime scenes certainly is at the top of the list.
Training officers by using patterns recognized through machine
learning that go overlooked by the human eye is another prime
example of a benefit. The valuable data (both input and output) can
also be used to help organizations — a police unit, hospital,
parking garage, etc. — to better manage resources from manpower to
dollars. The data output might suggest it would be a contrary
decision to deploy additional officers to a certain location or
reduce some in another or invest in additional security equipment
or personnel for a vulnerable area with a high probability for
criminal activity. Again, the applications are only limited to the
desire and the data sets to support a reliable recommendation.
Predictive Policing Works — And Is Getting
Better
It’s hard to envisage a day where a band of thieves on a mission
for a bank heist are met in the bank’s parking lot by police, but
the data to date the security sector is moving more in that
direction. Larger compilations of data and technological advances
will continue to improve outcomes and provide authorities with
superior tools to do an incredibly difficult and often thankless
task. Many companies are laser focused on seeing these advancements
become a reality.
Axon Enterprise
Inc. (NASDAQ: AXON), a company formerly known as TASER, ditched
its old name, which pigeon holed it as just a stun gun maker. While
the Axon still sells
its popular defense products along with body and in-car cameras and
sensors, Axon is on a mission to protect life as an innovative
technology company entrenched in AI and ML, utilizing data
collected from its integrated system of connected devices as a
foundation for its product offerings.
Palantir
Technologies Inc. (NYSE: PLTR) is a name synonymous with
software that lets organizations integrate their data, their
decisions and their operations into one platform. What many people
don’t know is that Palantir was
founded with
seed money from the U.S. Central Intelligence Agency’s venture
capital firm. The company has deep roots into the predictive
policing business and was instrumental to the New Orleans Police
Department in apprehending gang members.
International
Business Machines Corporation (NYSE: IBM) is well known for
using its predictive analytics system in law enforcement, offering
its IBM Digital Policing Platform, which leverages the power of
hybrid cloud, artificial intelligence and intelligent workflows to
achieve mission objectives in serving and protecting citizens. As
with Palantir, IBM is a legacy
player in the space, having rolled out Blue CRUSH (Criminal
Reduction Utilizing Statistical History) in 2010 in collaboration
with the Memphis Police Department. Blue CRUSH uses IBM SPSS
predictive analytics software to create multi-layer maps of crime
“hot spots” based on data from various arrests and incidents.
Everbridge Inc.
(NASDAQ: EVBG) is an expert in breaking down data silos with an
enterprise scale unified platform for aggregating risk data,
locating people and assets under threat, initiating action and
managing incidents and analyzing after-action performance. The company is recognized as a global leader in
critical event management and enterprise safety software
applications, having helped manage critical events for more than
5,400 customers worldwide, reaching more than 650 million people in
over 200 countries and territories.
Whether it is critical event management or working directly with
law enforcement agencies, companies are leaning on the power of big
data and AI/ML to improve public safety — and the trend is
building tailwinds. Industry experts expect that AI/ML will
continue to become increasingly integrated as a mainstream part of
public safety, with companies such as Knightscope providing the
invaluable components of data collection and surveillance.
For more information about Knightscope Inc., please visit
Knightscope
Inc.
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