Breaking Bad Data: Fightin’ Crime On Four Fronts


Walter White’s death in the Breaking Bad’s series finale may have some heroic note to it.  He saved Jesse Pinkman, his estranged meth partner, from the neo-Nazis, managed to set up a trust fund for his kids, and he killed The Tattooed Lady.  Some were disappointed that Walt died in the end, calling it cliché – bad guy seeks redemption before he dies.  Some say it was not the ending he deserved, some wanted him to live and expand his meth empire – the comments just go on and on.

Though many viewers fell in love with the cold-hearted Heisenberg, we shouldn’t forget that he’s one of the bad guys after all, and all bad guys deserve their comeuppance…

So what does this have to do with technology, specifically Big Data?  Well, if you weren’t interested in Big Data before, then maybe this will catch your attention: law enforcement the world over is now using data analytics in a big way to catch the bad guys.  While Breaking Bad’s Walt was able to dodge the hands of justice with his heroic death, most real life bad guys aren’t gonna be nearly as lucky…

Predictive analytics


Authorities in major US cities such as New York, Rochester, Las Vegas, Memphis, Los Angeles, and Charleston, have been using Big Data and predictive analytics, with the aid of IBM to “augment its officers’ years of experience and knowledge and provide them with a more in-depth method of looking at crime trends by centralizing previously disparate information including patrols, types of criminal offenses that are trending, time of day, day of week and even weather conditions.”

What this means is that Big Data is being utilized to predict crime hot spots in US cities. By doing this, the authorities remain one step ahead of the bad guys, and more often than not they’ll be there lying in wait to catch them red handed.  The down side is, criminals can just as easily pick new locations when they feel the authorities have homed in on them.

Abandon ship!


In this day and age, you’d think that pirates no longer exist right?  Or if they do, you think of them as someone quirky like a certain captain from a Disney movie about pirates.  But piracy is alive and well – in fact, the ‘business’ had never been healthier until very recently, costing the shipping industry more than $11 billion in 2011, along with the lives of 35 sailors who were killed by pirates in that same year.

Astoundingly, international piracy has declined by 54 percent since 2011 and we’ve got Big Data to thank for it.  Big shipping companies have turned to software firm Esri which provides an advance mapping system.  Esri’s software is able to pull large amounts of data from different resources to help users create maps that illustrates things they want, such as information on pirates’ locations and the routes they’ll be taking.  With that information, ships can plot alternative routes to avoid pirate hot spots, while navy ships can use the same information to track them down and arrest them. Besides this, Esri’s software can also help authorities predict pirate behavior, such as when they will attack, with the data it collects.

Taking down terrorists


Using facial recognition to catch the bad guys seems like something that would only happen in movies or crime scene investigation-based TV shows.  But with the Boston Bombing earlier this year, we saw how technology has evolved to help bring down the bad guys.  Admittedly, social media and ‘crowdsourcing’ caused a bit of chaos, with netizens disseminating the wrong information. But in the end, images uploaded by people at the scene of the bombings were used by investigators to build up a picture of the events during the Boston Marathon back in April, and more importantly, to finally nail the identity of the suspected bombers.

Investigators used software called CrowdOptic, which allowed them to extract compass information from the EXIF data in images, then use algorithms to pinpoint different “points of focus” within those photos, to mine metadata from the photos gathered from different sources.  This led to the authorities releasing the correct image of the suspects which led to their identification and finally, their arrest (at least one of them anyway!).



Big Data isn’t only useful in putting the bad guys behind bars – it’s also helpful in deciding which ones should be let out again. In one of the most recent example of how authorities are using Big Data analytics to protect the public, the state penitentiary is using special software to determine which inmates should be granted parole.

Using a program called Compas, the New York State Board of Parole is able to determine which inmates are most likely to be repeat offenders, which are most likely to land their asses back in jail, and which (if any) are able to become a productive member of society once again, when they get paroled.

While some might believe that anyone sent to prison should remain in lockdown forever, many believe that convicts deserve a second chance.  But is this method foolproof?

Before, factors such as the severity of a crime and whether the perpetrator showed any remorse in committing the crime played a huge role on whether or not an inmate will be paroled.  With Compas, the chances of getting paroled are determined by inmate interviews and biographical data, such as age the person was when first arrested, and patterns in their behavior that may predict whether or not the convict will likely be a threat to the community.

Big Data’s stealing the show


Big Data is playing a huge role in our lives whether we are aware of it or not.  Some of us encounter it everyday when we open our computers, log on to our favorite sites and suddenly, we’re presented with topics we are actually interested in.  We can expect Big Data to become more and more upfront as technologies evolve.

If you didn’t catch the Breaking Bad finale, or you haven’t watched the whole series and want to know what the buzz was all about, Get Your Breaking Bad Fix Here.

And as for how this piece will end, I’ll be channeling Pinkman on this one:

Watch your six, bitch!