I was left with a nagging thought post our last LPA class – ‘If life truly is curvilinear, at what point does it curve? Specifically, how can one identify and control when ‘people-data’ curves from good-use to misuse.
Serendipitously, the next morning I met Professor Caroline Buckee, a top epidemiologist at Harvard T.H Chan school of Public health and learnt of her recent article in the New Yorker which questioned if Americans would allow mobility data tracking for better management of COVID-19 or disallow it claiming privacy concerns? The article took the reader through both the good and the dark side of using mobility data for public health surveillance – while some believed that it was our moral obligation to use this data if it could minimize harm, others argued that rights once surrendered, would be impossible to roll-back.
I share here my insights from the article, and recommendations moving forward both for public health and for each one of YOU – the creators of mobility data.
What is mobility data and who owns it? Mobility data tracking tracks people movement through cell-phone apps, which emit a constant trail of longitude and latitude readings, making it possible to follow consumers through time and space. Google and Meta lead data collection in this space, but dozens of data-brokers buy and share this data. Is it fair to allow such data to be brokered? Can we ever completely turn off such data?
How can we use this data in public health? When paired with other metrics, such as the number of new infections or mortality rates, the data can help academics understand the spread of a disease and policymakers’ action out policies to contain the spread. What about representativeness of the data? What if we are missing inputs from a crucial population pivotal to our decision-making?
Can we maintain data privacy (if we wish to)? Yes! If we aggregate, anonymize, and create enough noise to disallow unmasking of the data, it can be useful for public health researchers and policy makers, while not violating privacy. Then what about malign actors who wish to track and target vulnerable communities using this data?
Who should be the gatekeeper for such data to avoid misuse? It is very concerning to me that, today, such personal data is being brokered through private organizations with at best poor regulation and no laid down rules for data sharing. It is interesting to note that academics currently serve as gatekeepers of mobility data, deciding who gets access and who doesn’t. Are academics the right gatekeepers? What is the role of the government in regulating use of such data? Can regulation bring down a 200 billion USD industry which thrives on brokering such data?
What does this mean for public health going forward? I believe COVID-19 has transformed public health forever. The landscape has leap-frogged from one where incomplete contact tracing data was used to create a static snapshot of disease spread to one where real-time movement across the globe is being used to monitor and contain disease spread. To me, an unsolved piece of the puzzle is to bridge the gap between private sector and public health academia. How well we can do this will dictate the impact big-data will have on public health. I disagree that select academics from premiere research institutions should lead gatekeeping of this data. Instead, I urge governments to create a ‘safe pipeline’ for data sharing, one which binds private players such as Google and Meta to collect data, however, defines its use against a solid governance framework build on accountability, ethics, and impact.
What does this mean for YOU? The next time you hit ‘Accept All Cookies’ on an app, know that you have supported collection of mobility data – data which could help combat crises and protect your loved ones, while maintaining your anonymity. However, it is also true that if you aren’t paying for the product, you are the product. It is you who has the right to demand anonymity and the power to create a movement to bring governance and regulation to ensure that we strike the perfect balance on the curve and data for good is made even better!