Does big data have a dark side?

Big Data is seen as a savior for small companies, massive corporations and governments. However, drawing from massive datasets to obtain a better understanding of human behavior does have a potential dark side.

Technology is only as good as the people using it. Whether it’s intentional or not, Big Data has a tendency to be abused, and raises some serious ethical questions about whether it’s responsible to collect so much data.

Knowledge Is Power

Big Data is a powerful tool for some of the world’s biggest companies. American Express, for example, is harnessing the power of it to collect actionable information on its customers’ tendencies and habits. Now, the credit card company can reportedly predict 24 percent of the accounts that will be closed in the next four months.

Meanwhile, some human resource departments are using Big Data to discover who would be the best person to hire. By utilizing a number of different factors, some companies believe they can find the perfect fit for their company. Xerox has used this kind of analytical technique to lower its attrition rate in call centers by 20 percent.

The private sector isn’t the only one embracing the power of Big Data, with governments also getting involved. While it is something of a recent buzzword, the U.S. government has been using this technology since the 1980s to optimize its welfare programs.

A somewhat scarier use of Big Data comes from the U.S. military. Armed forces stationed in Iraq and Afghanistan have collected biometric identification from 4.4 million people living in those countries. This widespread collection of data has reportedly identified 3,000 enemy combatants.

Knowledge is power, and the people holding the most data have the potential to be the most powerful.

Correlation vs Causation 

A writer for The Guardian wrote:”Big Data is data that is one bit too much for you to be comfortable.” That’s an apt definition, because, although it can undoubtedly be used for good, it also has the potential to be seriously misused.

There’s the societal belief in “innocent until proven guilty,” but Big Data doesn’t always follow that rule. There can be some serious pitfalls to utilizing Big Data, as it uses data to come to the conclusion whether someone is “guilty” or possible to act in a certain way. This isn’t particularly troubling for fast food restaurants trying to use algorithms to determine prices, but it’s definitely a problem for governments trying to make the most of it.

The White House is cognizant of this problem. While Barack Obama’s tenure as president has seen rapid technological developments and a heightened use of technology, the administration sees the flaws of Big Data. In a May 2016 report titled “Big Data: A Report on Algorithmic Systems, Opportunity, and Civil Rights,” the potential benefits of data are championed. However, the real possibility of misusing Big Data to “perpetuate, exacerbate, or mask harmful discrimination” are also warned against.

The White House is right to be concerned. Data can be useful, but it also has the potential to be completely misread. The collection of data is the easy part, but meaningful analysis is the real challenge. A Rutgers University study explored this problem by analyzing bulk social media data concerning 2012’s devastating Hurricane Sandy. Researchers found that, if governments used Big Data to make their emergency decisions, they would often have come to a completely wrong conclusion.

A Balancing Act

The same White House report that warned about how Big Data can perpetuate discrimination and biases also stressed that these tools can be used to lessen discrimination. The subtle divide between what’s working and what isn’t is sometimes hard to distinguish when it comes to Big Data, yet it’s totally essential. Privacy concerns about data collection are wholly legitimate, so companies and governments need to work around that while becoming more efficient and accurate.

And then, of course, there’s the economic effect that the misuse of data can have. We’re talking about a truly massive scale here: cyber threats cost the global economy an estimated $375 billion each year. Besides balancing privacy and security, we must now throw economic solvency into the mix, further muddling an already complicated debate.

With all this in mind, Big Data analysts have to make the tough call when it comes to best practices. It’s important to adhere to proper security measures when collecting an storing data. While mass quantities of data and data calculation have the ability lead to great breakthroughs,

it is easy to abuse or misrepresent data that information.

Analysts must be cautious of how they approach their data collection and analysis to make sure they portray the numbers in the best possible way, instead of manipulating the information to serve their own benefit.  By recognizing the danger of Big Data, governments can create a strategy and guidelines for businesses to follow that protect citizens and allows for knowledge growth.