We browse, therefore we’re data
Chances are high you got here from a link on Facebook or Twitter. Or maybe you recently ordered a holiday gift from Amazon. If you’re like me, you use these social media platforms and web services with a hint of resign and possible distaste for the way your data is tracked, stored, and commodified. For example, I know Facebook “follows” me around the internet, builds up ghost profiles of friends and family such that even those who choose not to be “on” it become, unwittingly, another line in Facebook’s giant ledger of data. The algorithms to capture and use data are so good that some people, I learned from a recent episode of the Reply All podcast, are convinced Facebook is actually listening to them through their smartphone microphone. (Hint – they’re not, but that doesn’t make the tracking much less invasive.)
We benefit, so we put up with it
Why do I and so many others keep using these services, knowing how we’re tracked and commodified? Mainly through self-examination, I’ve come to believe it’s for the convenience. Amazon’s analysis of my past purchases occasionally helps me find a product I find rather helpful and enjoyable. Facebook allows me to easily stay in touch with a large network of family and friends. Twitter links me to interesting and timely content about both personal and professional interests. Sure I’m trading a fair amount of privacy, but in the micro-transactions of my daily browsing and meanderings online, it seems worth it.
DNA as data commodity
The transactional nature of trading our data for convenience, or perhaps trading it for entertainment (hello, Netflix), has a parallel in direct-to-consumer (DTC) genetics. While DTC genetics has been going strong for over a decade, it’s only been in the past year that privacy issues seem to have really grabbed the popular consciousness. AncestryDNA had a public kerfuffle when a consumer protection attorney wrote about how the company’s terms of service grants them “the broadest possible rights to own and exploit [customers’] genetic information.” In late November, Senator Chuck Schumer voiced concerns about the opaqueness of DTC-GT companies uses of customer data and called on the Federal Trade Commission to investigate companies’ privacy policies.
I don’t know how often the typical DTC customer considered privacy implications in the past, but given the recency of these more public debates I find it unlikely they would be completely unaware of privacy implications now. So why do DTC customer numbers keep growing by the millions? (See, for instance, here and here.) I suspect for the same reason we keep using the aforementioned online services. For DTC testing, it’s often entertaining to learn about genetic ancestry and to connect with relatives. Even much of the health and wellness trait information can seem “recreational” if taken lightly enough: “I have an increased chance of restless leg syndrome? That’s why I’m always fidgeting!” or “How silly, they say I likely have hazel eyes when in face mine are brown….”. We have a vague sense our DNA sample is being stored and perhaps sold, but what we get in exchange seems, again, “worth it.”
Implications for research
While I research DTC genetics, I work in genetics research. So I also think about how these data transactions are changing the way genetic research occurs. When we exchange personal data (genetic or otherwise) for individual gain, that is fundamentally different from how research has traditionally operated. Researchers ask people to join studies not for their own personal benefit, but to benefit society at large. To increase knowledge and improve human health, not the individual participants’ knowledge or health. How can researchers continue to attract participants if they’re not offering a data transaction with direct individual gain?
The answer may be that they can’t. I’ve argued that researchers should consider offering individual data back to participants, if they hope to attract participants at a rate even comparable to DTC companies. Some academic groups are adopting a hybrid model, where they collect genetic data for research while returning to the participant a DTC-like report of personal information (e.g., Gencove, DNA.land). A new start up DNAsimple is offering individuals $50 each time a researcher wants to use their data for a new project. There are and surely will be many more examples like this, where academic researchers leverage data transactions where the individual consumer/user/participant directly benefits in exchange for their contribution (sometimes more knowingly than others) to a larger dataset.