I grew up in suburban Pittsburgh, Pennsylvania, and spent the bulk of my early life doing sporty things and exploring the outdoors. I was fortunate to have two teachers for parents, which meant we all got summers off to travel around. By 19, I had set foot in all 50 U.S. states and canoed or backpacked in most.

I was initially attracted to science in general, and, being pretty stoked on the outdoors, decided to pursue biology. I wanted a career of service, and the natural world seemed to be particularly in need. Along the way, I noticed two things that led me to modify my goals. First, there is little lack of information about how we need to amend our relationship with air, water, biodiversity, etc. Several clear solutions like abandoning fossil fuels have been in front of our faces for decades. The crucial work on this front is now the province of business, media and policy makers, so the necessary changes are social if anything. Secondly, I noticed computers are pretty sweet, and that mastery over data confers more power than I could ever wield as an ecologist.

A concern remains, which is that data science as a field focuses relatively little energy on social and environmental progress, and a lot of energy on tricking people into clicking on ads. I assume the available career opportunities follow suit. So changing my path could present some moral dilemmas if I fall short of my ideals, but DSSG is a promising first step. I hope my team and I develop a deeper understanding of machine learning this summer and create a tool Seattle can use to reduce traffic. Ultimately, I want to specialize in deep learning, get a PhD in the same, and eventually study AI risk and control methods at the Future of Life Institute, The Center for the Study of Existential Risk, or the Open Philanthropy Project.