Can your personal data solve the world’s problems?

When I set up my very first smartphone and it asked me to share my location data, my instinct was to say no. After all, who wants to be monitored by a machine? But the first time I got lost, I wished my phone knew where I was so it could help me out. And when I lost that phone, I definitely wanted the new one to keep track of my location. The trade-off now seemed a little more palatable.

The fact is, most of us are willing to relinquish a little privacy if we can see the benefits. That willingness rises in proportion to the amount of good that can be gained by sharing the data. Let’s say you’re unlucky enough to be caught in the middle of a natural disaster, like a flood or a fire. That’s a case when you really want the universe to know where you are. Sometimes, granting others the right to see your digital footprint is a very good thing indeed.

A new digital resource

In my work with the Forum’s Global Agenda Council on Data-Driven Development, we talk about how to unlock the flow of data to help solve humanitarian crises and drive inclusive growth. These are the kinds of stubborn, persistent challenges that require huge amounts of data to solve; world leaders, businesses and NGOs all see the vast potential inherent in this new digital resource. At the same time, we’re committed to being extremely careful about the potential for misusing, or even abusing, that data. There are legitimate concerns about privacy.

So how do we weigh the good against the risks of making data widely accessible? How do we open the taps while ensuring the resulting outpour doesn’t drown us?

Part of the answer lies in moving the questions, not the data, as I’ve argued before. In the age of the cloud, we can let the questions chase the data. Doing so is more convenient and less risky, much like using credit cards can be easier and safer than carrying cash.

A sensitive issue

Another part of the answer lies in parsing the data to separate what’s truly sensitive from what is not. Sensitive data includes things like social security numbers, PINs or other unique identifiers. Non-sensitive data might be something like weather patterns or anonymized lists of all the stuff purchased on Amazon. In most data flows, both types exist.

Using non-sensitive data is still risky, but at the same time the loss of it is not going to shake the earth. To help the developing world, we have to identify where the sensitive and non-sensitive data are travelling together, and untangle them. We must build governance structures to hedge the risk and provide a safe harbour for data, with the litmus test being the question: “What is the purpose of using this data?” The higher the purpose, the more willing we should be to find a way to use it while mitigating the risk.

The Global Agenda Council white paper, Pathways for Progress, addresses the role of governance in managing risk. Big-data analytics play a key role in that governance.

Of course, technology constantly presents new problems for how we coexist in an interdependent world, and as the internet of things (IoT) continues to develop, the question of what is sensitive and what is non-sensitive pivots. In the IoT era, it’s more about what’s relevant according to context. For example, what your Fitbit says about your exercise patterns is really only sensitive in a personal context – but when aggregated to give health experts insights into which policies to recommend, it’s no longer a privacy concern. Likewise, using the data generated by a self-driving car for safety purposes is not sensitive. But using that data to detect your mood certainly is.

In the modern era, your bank knows your spending habits, telecommunications operators know where you are, your self-driving car knows your state of mind. That information should always be private to you. But when your data can help solve a societal problem, the question becomes: how do we anonymize and securely use that data to help many more people? All of us are willing to take on much more risk when it means saving lives. The challenge before us is how to govern the process so that lives aren’t hurt. And that starts with transparency.

Author: Mikael Hagstrom, Executive Vice-President, SAS Institute; Vice-Chair, Global Agenda Council on Data-Driven Development.

Image: Hewlett-Packard ProLiant commercial data servers destined for cloud computing are assembled by workers at a company manufacturing facility in Houston November 19, 2013. REUTERS/Donna Carson