When looking at developing economies, it’s tempting to pump the breaks on privacy protections. Look at how all this data can help drive innovation, the logic goes. Let’s worry about privacy once we’ve got things up and running.
That’s short-sighted logic, however, and feeds off a couple of pervasive fallacies that are worth debunking.
First, there is this idea that third-world countries don’t have technology to speak of, so why worry about privacy and data protection. Nothing could be further from the truth. Perhaps they’re not brandishing the latest iteration of the iPhone, but mobile-device penetration in developing countries is already profound. According to 2013 research, there are 89 mobile phones for every 100 people in the developing world, and 31 percent of those in the developing world are online.
The types of transactions they’re making with their mobile devices are likely even more personal than those being made in the developed world. They’re making payments and transferring money via SMS. Their phone, with Internet access, might be the only way they get online, so a location point might accompany every single online interaction. If anything, these people need more privacy protections in place, not fewer.
Second is the idea that those in developing economies don’t have the same concept of privacy as those living in the developed world. Perhaps there is wild variance in cultural mores, but all business is based on trust. Information privacy is transactional; the data has value. How are these new and innovative technology solutions to gain traction in developing nations if the prospective users don’t believe in the value proposition or trust these solutions to treat them fairly?
With appropriate and forward-thinking privacy policy in place, consumers have baseline expectations as they enter and expand their presence in the online marketplace.
Finally, with the proper privacy regime in place, we can truly use the data to protect against the kind of unforeseen discrimination that can happen with new data-use models.
Consider the case of Street Bump, a handy little app developed by the City of Boston to automatically identify potholes using the motion tracker capabilities of smart phones. Great idea, right? And it worked. Thousands of potholes were quickly identified and filled. However, by mapping the locations of those potholes against census data regarding income, it soon became apparent that wealthier neighborhoods were disproportionately receiving pothole attention.
Similarly, it was tempting for emergency response workers to use Twitter to try to identify particularly hard hit areas during Hurricane Sandy as it pounded New York. When mapped against a traditional location map of Twitter use in general, however, it became apparent that it wasn’t that Manhattan was harder hit than someplace like Long Island. Rather, Manhattan simply had a bunch more regular users of Twitter.
Which, of course, makes sense. Wealthier people are perhaps more likely to have a smartphone and be aware of such efforts. Manhattan has a denser and more tech-savvy population. However, sometimes it takes a bit of data for us to see the forest for the trees.
In developing economies, the trees are going to pop up fast. As connectivity increases, data will become available that allows policymakers and the business sector alike to quickly see forests developing and rapidly offer solutions to problems that might arise or that have existed for centuries. Just look at the example of iCow in Alec Ross' new Brookings paper "Networking the World for Global Opportunity":
The average farmer using iCow owns just three cows. After 7 months using iCow, the increased production is the equivalent of owning a fourth cow. For every dollar spent on iCow, the average farmer made an additional $77. With this data applying to 11,000 dairy farmers and growing, the impact is not trivial—and it is representative of what happens when applications are developed that respond to local needs leveraging 21st-century telecommunications infrastructure.
We need to create an environment where expectations are set, both sides of any transaction can operate in good faith and the amazing opportunities that big data and connectivity have to offer can be brought to bear. That can only happen with a privacy regime that provides so much of that level setting.
How do we come by such a regime? Not by cutting and pasting some other country’s privacy laws and regulations. However, we are seeing commonality begin to pop up amongst the world’s laws: accountability, privacy by design, higher expectations of privacy around sensitive classes of data like health and financial information. Further, we are seeing commonality around the way that organizations handle data. Privacy professionals are increasingly being put in place to manage data flow, help with product design, and write policy that helps companies create trusted relationships with their customers.
In fact, the great thing about privacy by design is that it works on the micro and macro levels. Developing an app? Make sure you consider privacy as you start your coding. Looking to develop an economy? Consider privacy as you look to use the power of data to make it happen. Similarly, accountability is vital from the lowest levels on up. Just as the app-maker should document data-use decisions and create a feedback engine to make sure only the right data is being collected in the right way, so too must policymakers ensure that the polices they’re putting in place are having the desired effect: a healthy marketplace where consumers are eager to engage.
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