The Big Data Gray Area: Dos and Don’ts
I’ll be the first to admit it: If you’re looking for a perfect answer to the big data ethics dilemma, you’re not going to find it in this article — or any other article, for that matter. That’s because there is no perfect answer. If there were a perfect answer, an obvious answer, or an easy answer, we wouldn’t be facing a dilemma — there would be no gray area.
Perfect solution or not, in business, as in life, there are certain things we should and shouldn’t do. There are certain general standards to which we should hold ourselves and our companies, regardless of the fact that there may be no laws requiring us to do so, or that the principles behind them may not apply 100 percent of the time. There may be no perfect solution, but it is our responsibility to try nonetheless.
Big Data Ethics Dos and Don'ts
With that in mind, and with the full understanding that these recommendations are anything but perfect, here are what I believe to be the dos and don’ts of big data ethics:
Do work hard to become a data-driven organization. Considering the technological advances that have made it both possible and (perhaps more importantly) affordable to more easily and efficiently manage, integrate and analyze data, there’s really no reason for any organization not to embrace a data-driven culture. Large or small, organizations that wish to remain competitive in the modern business world must have a willingness to share information and to allow decision-making to be guided by the insights and behavioral patterns hidden within big data.
Don’t always assume data is right. As we just established, there’s no question that it’s time for businesses to start embracing the power of big data analytics. But that doesn’t mean that logic and intuition should be cast aside completely, and it most certainly doesn’t mean that companies no longer need to exercise common sense about what is and isn’t ethical when it comes to big data. Just because you have collected and analyzed data, you needn’t follow those findings blindly. Any number of issues, including poor data quality, a lack of metadata or an unreliable data model, can cause data to steer you in the wrong direction. To ensure no ethical lines are crossed, develop a culture in which analysis and intuition both have a place at the table.
Do secure explicit consent before adding people to your prospect database and delivering them content or promotional offers. The good news is that most companies that actively market to prospects with content and promotional offers are already doing this, if only because they’re usually required to by law.Andy Taylor, Author