While we know that data science is rapidly becoming a vital strategy in several academic fields, what role does it play in running our government? Last Wednesday, the CDS Lunch Research Seminar heard from Dr. Jaime Anne Earnest, a program analyst and data scientist from the US Department of Defense.
Surprisingly, until former President Barack Obama launched his “Digital Government” directive in 2012, data science played a minor role in constructing governmental policies. It’s not that the data wasn’t there, Dr. Earnest explained, but that it was relatively inaccessible for both governmental staff and the public.
Obama’s directive, however, flung open the doors to the government’s big data through the crucial launch of data.gov, the government’s open repository filled with data on important topics like climate change.
The immediate problem now, Dr. Earnest said, is helping people both within the government and outside of it to use the data. Unfortunately, the data cannot be made sense of by those who have understandably been trained in writing up policies, not to perform statistical analysis or comprehend the complexities of casual inference.
There is an urgent need for more data scientists to work directly within government, particularly because strict policies prevent collaborations between the government and private institutions. But, until more data science experts are recruited, part of Dr. Earnest’s job as one of the few professionally trained data scientists at the DoD is building data science models and visualization frameworks that policy makers can easily navigate to encourage them to create more evidence-based policies, and to encourage the public to use these models, too.
After all, it is not only policy-makers that suffer from a superficial understanding of data science, but the general public at large. We only have to remember the 2016 presidential election to understand what consequences can ensue when non-data science experts use data to make predictions without a strong understanding of the theoretical models that underpin their analytical process.
But it’s not all doom and gloom. After all, as Dr. Earnest stated, trained data scientists have a golden opportunity to make a tangible difference today since they are the ones with expertise and experience to put our nation back on track where data is concerned.
Professors and students of data science alike now face some interesting questions. Should they pursue a cool and lucrative project at a start up? Or should they go on to pursue a doctorate, contribute to a specific area in data science research, and teach the students of tomorrow? Or should they step into the White House, and directly apply their skills to legal policies and matters of national importance? There are a wealth of opportunities to choose from—but which is the right choice?