Our desire for privacy is part of what makes us human. None of us likes to have our privacy invaded, whether from someone reading over our shoulder or a data breach. Every day we read stories about foreign government hacks and ads that follow us across the Internet and devices, raising our collective eyebrow. The recent revelation of the Equifax data breach is just the latest and most significant worry to focus Americans’ attention on Internet privacy.
No longer science fiction themes, software and bots are becoming more capable, building a greater understanding of us every day. This rise of machine learning — not just harvesting data but machines analyzing it to draw an increasingly accurate picture of all aspects of our lives — is taking concerns over data privacy to new heights.
Most of us probably think of privacy primarily in terms of protecting sensitive personal information — data like Social Security numbers, credit card numbers, and health records. However, there is data that is increasingly more concerning. This is data that Professor Michael Kearns of the University of Pennsylvania calls “intimate data.” These are things about you such as where you shop; what you buy; how much you exercise; your attitudes, beliefs, moods, and opinions. Kearns believes that private traits and attributes are predictable from digital records of human behavior — and, if predictable, they’re analyzable and saleable, as well.
With machines making inferences about us from our behavior across the web, it’s becoming easier to unknowingly give away valuable information, via email, social media, navigation systems, and more. For instance, geolocation might shed light on an individual’s health — whether they go to a hospital or clinic frequently — that might not be information someone would want to share.
And the explosion of data continues, with cascading secondary effects.
Can algorithm bias lead to higher rates for loans for specific groups? Are insurance rates now set more by drivers’ experience or by socioeconomic and geolocation data on where one drives to measure riskiness?
People care about privacy, as the rise of ad blockers indicates. A Pew survey in 2016 reported that 74% of people believe it is “very important” to have control over who gets information about them. The good news is that technology is beginning to respond to this surge of consumer interest. The switch to apps that do not support cookies is one indicator. Apple has even included Intelligent Tracking Prevention in its latest operating system. Technology must be considered part of the solution, not just the problem.
The forthcoming adoption of the General Data Privacy Regulation in Europe, which flips the default model to “opt-in,” also provides an opportunity for the US to look at online privacy. We should preserve privacy without being too prescriptive. In the ever-changing online world, the best way to ensure online privacy will be to level the playing field. Do so will mean that Internet Service Providers (ISPs), search engines, social media, publishers and other “edge” providers are subject to the same rules, with a single regulator rather than a patchwork of state regulations that makes no sense for the Internet, the ultimate borderless technology.
The federal government has a role to play, but we must streamline the process. Consumers and companies need to know who the referee is and what the rules are. Having multiple agencies govern Internet privacy leads to the kind of confusion that puts everyone at a disadvantage. It’s time to initiate a serious, national conversation about creating a flexible system for online privacy that doesn’t leave us a step behind. Giving consideration to the FTC’s general approach and legal standard – stopping unfair or deceptive practices – is an excellent place to start.
