Big data privacy is a bigger issue than you think
If you’re in the big data business, there’s a huge privacy issue that isn’t addressed as often as it should be.
The hottest privacy topic to make the headlines is the embarrassment your company will suffer if there’s a data breach. Other privacy topics that get a lot of coverage are the risk of discrimination (i.e., your algorithms show a discriminatory and illegal bias), inaccurate analysis due to fake news, and identity reverse engineering (i.e., basically undoing anonymization). While I agree these are significant issues that are exacerbated by big data, a bigger concern is what I call oracular responsibility.
Big data analytics has the power to provide insights about people that are far and above what they know about themselves. And, as Stan Lee says, “with great power there must also come—great responsibility.” Such is the responsibility of the oracle—thus, oracular responsibility. In fairness, this problem existed before big data, but it wasn’t a huge risk until big data analytics gave us the tools and techniques to be highly accurate with our predictions.
Let’s consider the DIKW (Data, Information, Knowledge, Wisdom) Pyramid. When most people talk about data privacy, their biggest concerns are actually with data, as it would be defined in the DIKW Pyramid. My social security number is probably sitting in multiple databases out there and if one of those databases is breached, I’ll have a huge problem.
The next level of the pyramid is information; this is where we start making actionable inferences about the data. When you’re looking into understanding users’ behaviors, this is going to freak people out even more. It gets worse.
The next level up is knowledge, which is where you start connecting the dots from different areas of a user’s life—their interests, shopping habits, political views, religious views, associates, professional development.
The most sophisticated practitioners of big data analytics go all the way up the pyramid to wisdom, where this knowledge is tracked over time and curated into a very personal profile. Breach or not, most people would feel very uncomfortable knowing that someone or something knows that much about them. I consider this the biggest privacy issue faced by those practicing the dark arts of big data analytics.
It’s important to be fully transparent with the subjects that you study. They might be your actual customers, or they might not be. You might be analyzing one group of people for the benefit of another group of people. In any case, it’s important to be upfront with the people you study and analyze. Cathy O’Neil, former Wall Street quant and author of Weapons of Math Destruction, explains the high risks of a big data cocktail containing opacity, scale, and damage. This poison is neutralized with transparency, which clears up the opacity.
