Connecting the Dots: My Journey in Analytics
Eagle Rock near San Jose; photo: Sandip Bhattacharya
Have you ever read a book, or an article, or watched a movie, a documentary, or really consumed some piece of media that, as you look back now, fundamentally changed how you viewed the world?
A few summers ago, I read the book Data Feminism, by Catherine D’Ignazio and Lauren Klein. Great book, by the way, and if you have never heard of the book or read it, I’d recommend it without any hesitation especially to anyone working in the data field but even just anyone curious about how data now affects so many aspects of our day-to-day lives. By this time, I was in the middle of my undergraduate studies in statistics. I’d long been interested in data and working with data, a large part of that due to my interest in sports and sports statistics.
However, my interest in ideas of ethics, social equity, and social justice grew during this time period. I can recall wondering how I began to have deep interests and passions for what superficially seemed such wildly different fields and disciplines. Nothing in my college curriculum seemed to connect the dots; neither did anything in the online news and media that I consumed.
❝My journey begins with Data Feminism, a book personally transformative and eye-opening❞
My journey, therefore, begins with Data Feminism, a book so personally transformative and eye-opening that I felt compelled to document 20 (yes, 20) pages of notes on what I had read and my own thoughts and feelings. (By the way, to my professors, if you are reading this - I’m sorry to report that these notes were longer than some of my notes for actual college courses). I realize in hindsight that a person more connected to topics of data ethics and privacy might have exposed me to these ideas sooner, but this was really the first time I was capable of putting words to thoughts and feelings about the intersection of social sciences, the humanities, and feminist thinking and approaches with technology and data science.
At the core, these topics centered on how factors such as the data that is (or sometimes isn’t) collected, the way data powers certain tools or algorithms or systems and the effects of those systems, and even who controls these data systems in the first place can have powerful consequences, good or bad. Increasingly, these consequences and their manifestations are being felt, observed, and documented: predictive policing and state surveillance, artificial intelligence chatbots, credit scores, voice-powered home devices, you name it. Are these developments good? Are they bad? Who are they good for? Who are they bad for? Should we make these technologies? Why? Why not?
Serendipity
As I look back on my college days, a common thread I often ponder is the serendipity I experienced when things fell in place just at the right time. When I returned to my fall term at school, a month or so after I had finished Data Feminism, we had a new professor in our department, whose interests happened to encompass statistics education and equitable data science. I reached out immediately, and before long, my first steps in working in this area involved a research project to develop coursework that we aimed to include in the introductory course for the statistics program in my college. Our coursework focused on ideas of equitable data visualization; we explored topics like physical data visualization, comparisons of conventional storytelling with visualization and uncovering new stories and perspectives, and applications to real-life data.
Sports analytics may have been my start in this field, but my interest in data science has since expanded
This last part in particular was important to us; as one of the major points from Data Feminism, we considered it important to use and work with data that came about locally and could involve the community in some way. I’ve learned that a powerful means by which communities and people can combat growing power imbalances and data inequity (where corporations and government, for example, wield the majority of power and influence through their countless datasets) is through collective generation and ownership of its data.
I graduated college recently and have since moved cities and embarked on a new postgraduate program. I spent the last several months or so settling into a new home, a new school, and so much more, so I found that I didn’t have the time or bandwidth to find avenues to explore these interests of mine. So, when LA Tech4Good came to present at a seminar for my graduate program, it felt like one of those serendipitous moments.
❝What [we] need is an awareness and a willingness to tackle head-on the many growing problems and issues arising because of the very data we work with and how we choose to work with that data.❞
Core philosophies to guide my missions and my work
I haven’t been at LA Tech4Good for long, but I’ve found a good place with good people where I can now push forward in my exploration of this growing field. As a postgrad student now in the data and analytics sphere, I want my work both in and out of the classroom to no longer merely reflect a passing interest in data ethics and equity. Rather, I want to move forward with these ideas and topics and core philosophies truly guiding and influencing my personal and professional missions as well as my tangible work, no matter where I end up, and no matter what industry or field I choose and may find myself in.
I’ve often been told as I enter the data and analytics workforce that I am a part of the future generation of leaders in probably the most exciting and promising field. But, what good is being a part of that exciting future if that very future features an increasingly unjust world, unjust largely due to how data has been controlled by those in power? Our world as we know it is, and has been for quite a while now, inevitably becoming run by data and, more subtly but importantly, those people, the next generation of data practitioners, who have and control that data. People like me.
And for people like me, soon to be entering the world of the 9-to-5, learning how to wield data equitably doesn’t need to involve taking 20 pages of notes on a book. It doesn’t need to involve reinventing the pedagogical wheel or even just devising a couple of course units for college freshmen.
What it does need is an awareness and a willingness to tackle head-on the many growing problems and issues arising because of the very data we work with and how we choose to work with that data. Among the things I hope to accomplish as I look to the future is to find my place in a growing field of data practitioners who are guided by these principles of ethics and equity. At LA Tech4Good, I’m now on the start of that particular journey; I’m excited for what’s to come, and, regardless of whether or not your occupation is as a data practitioner, I’m excited for you to hop on that journey too.
About the author
Eric Tran is a master's student in UCLA Anderson's Business Analytics program. His academic interests include sports analytics, data equity and ethics, and data visualization. In his free time, he enjoys watching and playing sports, cooking, and spending time at the beach
Learn more about our Leading Equitable Data Practices workshop series here
Read Data Feminism - available here online from The MIT Press.
Data Feminism cover image: Digital visualizations by Christopher Pietsch and Siqi Zhu from Art of the March, an archival project led by Alessandra Renzi, Dietmar Offenhuber, and Nathan Felde, based on posters collected from the 2017 Boston Women’s March.