Due to the proliferation of social, mobile, cloud and connected technologies, many organizations have begun adopting big data as a means for collecting, analyzing and making strategic decisions. This has become a powerful way to unlock actionable insights across your business, but it also brings with it some concerns about big data ethics that need to be addressed.
Because accessing and storing data is so easy, some organizations "collect everything and hang on to it forever," says Ira Hunt, chief technology officer at the Central Intelligence Agency (CIA) in The Huffington Post. He adds, "The value of any piece of information is only known when you can connect it with something else that arrives at a future point in time."
It is not just the CIA collecting data like this. Major grocery store chains, investment banks and even the U.S. Postal Service have a predictive analytics function with the sole purpose of collecting and analyzing data in order to predict buyer behavior.
But what if all this data collection takes a negative turn? What if, for example, an organization could predict which employees were looking for a new job by using data from social sites, job boards and internal communications systems, and then terminate those employees? Would this use of data be ethical?
Jonathan H. King, head of cloud strategy at Ericsson, and Neil M. Richards, law professor at Washington University in St. Louis, don't think so. They raise several questions about big data ethics in Radar, asking "Who owns all that data that you're analyzing? Are there limits to what kinds of inferences you can make, or what decisions can be made about people based on those inferences?" King and Richards lay out several ethical issues, such as privacy, data ownership and transparency, that organizations must consider when creating big data initiatives.
Data Privacy and Ownership
According to King and Richard, securing private data through big data initiatives is not an all-or-nothing issue. The data collected is not necessarily secret and can still be confidential, meaning that it doesn't have to be shared with outside parties. However, creating policies that address what data your organization is collecting and how it will be used can help preserve values and prevent future complications. An important principle to consider when creating these policies is data ownership and whether or not individuals should be able to control the data that can be used. Allowing an individual to choose what information is collected creates transparency and allows the individual to be in control of the data they share.
As reported in The Guardian, Tim Berners-Lee, inventor of the World Wide Web, said that the data we create about ourselves should be owned by the individual, not by the large organizations that harvest and use it. This sounds simple enough in theory, but difficult to enforce in practice. As technology advances to include an ever-expanding pool of collectible data, the lines are increasingly blurrier between data created by an individual and data created by an enterprise. Organizations should address these questions by establishing clear data ownership policies.
Transparency of Data Use
One of the messages from Ira Hunt, CTO at the CIA, is that organizations don't know how the data will be used until connections are made, so organizations collect any information they can get. However, this can raise ethical issues since employees are not always aware that their information is being collected. For example, an organization that uses employee data to predict retention rates is not doing anything wrong, per se, but their employees could have mixed feelings about the practice if HR leadership is not upfront about the data collection process and its intended purpose. A good way to stay ahead of this concern is to practice transparency when collecting and analyzing data.
Because the future of big data is so bright, organizations using it now or planning to in the future would be smart to include big data ethics as an important part of creating policies, procedures and guidelines to govern the use of the wealth of data collected. Big data technologies will continue to evolve over time, so it's critical that your guidelines follow suit.
To see what the three-step success model is for turning people data into business impact, check out the Better decisions start with HR insights guide.