DJ Patil on the Importance of Interpreting Data

DJ Patil

Husband, dad, data scientist (and former U.S. chief data scientist), public servant and pandemic fighter

What would you say to your older self?
The quote that always sticks with me is by Former Secretary of Defense Ash Carter, about how security is like air and that we don’t value it until we don’t have it. We need to remember why we have worked so hard to ensure our security and keep pushing others to recognize the need to work hard to preserve it.

What makes you feel like a real grown-up?
My kids rolling their eyes at me in the same way that I did when I was their age.

You refuse to give a F about ______People who aren’t willing to engage in constructive conversations and dialogue.

Desperately Seeking Data

I’ve always been fascinated by nature; in particular, the way patterns form, such as how sand dunes form. Using data helped me study nature, and for me, it really began with weather data. Because it was easily accessible on the early internet, I was able to look through it for patterns. Much of my work has been finding those patterns in data and asking interesting new questions that lead to a deeper understanding of the world. And that’s led us to begin to build “products” out of data. For example, the self driving car is really a “data product”: It takes in a huge amount of data via sensors, does a massive amount of computations, and then figures out to speed up or turn left. Data science uses data to solve problems. I believe that it’s a team sport; when we come together we can do powerful things with data.

We often hear phrases like “data-driven” and sometimes conflate data with absolute truth. Data should inform the way we think about the world, but it shouldn’t define the way we think about the world. We have to always question data and realize that we might not be capturing something in it, such as in medical studies, where continuous questioning of data often will iterate us toward the recommended treatment—sometimes completely changing course.

Over my career, I’ve worked on wide-ranging issues, from the threat of bioweapons in Central Asia during the Bush Administration, to post-Ebola data systems as the U.S. Chief Data Scientist in the Obama Administration. For the past 100 days, I have been living in Sacramento as an unpaid volunteer supporting California’s efforts on COVID-19, engaging with city mayors, and consulting with governors. We’ve focused on issues from the need for stay-at-home orders to increasing the sophistication of models, contact tracing apps and more. Epidemiology is fundamentally a math and modeling problem. Vast amounts of data can be used, but most people aren’t likely to realize how it can be used. Part of my job was to use data and technology in novel ways, to give us an edge in the COVID fight. We focused on how to improve the models for what COVID will do, and to develop early warning signals for an outbreak. The challenge is that, all too often, people make decisions without any data. The data is pretty clear-cut about the use of masks and COVID’s infection rate, yet too many leaders refuse to take the necessary steps to dramatically reduce the impact of COVID on their communities.

For people who feel frustrated with COVID information and how to interpret it, I would say I'm frustrated, too. It shouldn't be this hard to get basic information about the spread of a pandemic when we can easily order via shoes online—in stock, in the style, color and size we want—and get them shipped to us the next day. Fundamentally, it’s about measuring what we want to fix. We haven't invested in public health for nearly a decade, and now we're paying for it. That’s why I wrote up my six lessons from working on COVID, to prepare people for a second wave or future pandemic. It's about getting the right data together so we can take action.

It’s eye-opening to watch the fight between county and other elected officials and their public health officers. People take their county-level votes for granted because they don't think they have much impact. Yet now we're seeing that impact. Too many public health officers are being marginalized and threatened. And the result of that is a rise in cases. What people don't see coming is that we're going to need those same public health officers as we think about how to open schools safely. We need to stand up for both data and science to make sure we can manage COVID's wrath.

The other concerning thing is the politicization of data. We have a set of public leaders who are working hard to undermine the trust in systems to manage COVID, because it shows how flawed their leadership has been. I can't stress enough how dangerous this is. Because as significant as COVID is, it’s not even the “big one.” And we're going to need these systems working if we want to stand a chance.