Professor Benjamin Mako Hill will present a talk for those those of us who teach code to non-coders.

Abstract: The current model of data science—professional data scientists mining online communities for the benefit of their employers—is only one possible vision for the future of the field. What if everybody learned the basic tools of data science? What if the users of online communities collected and analyzed data about themselves? What if they used data to understand themselves and communicate with each other? I will describe and discuss a multi-year experimentation around data science education that attempts to explore one set of answers to these “what if?”  questions. First, I’ll describe a set of four-day workshops called the “Community Data Science Workshops” that have taught hundreds of individuals with no programming experience how to use Python to build datasets by querying web APIs and how to use the data they collect to answer their own questions. Second, I’ll present a system called “Scratch Community Blocks” that has been used by hundreds of children (mostly 8-16) to write block-based programs to analyze data about their own participation and communication in the Scratch online community. In both cases, I’ll describe the theory, goals, and design of the effort and present examples of outcomes. Finally, I’ll reflect on the challenges and trade-offs that these experiments in building a more popularized vision of data science suggest.

Benjamin Mako Hill is an Assistant Professor in the Department of Communication at the University of Washington. Hill has a Masters degree from the MIT Media Lab and a PhD from MIT from the Sloan School of Management and the Media Lab. Hill has also been a leader, developer, and contributor to the free and open source software community for more than a decade as part of the Debian and Ubuntu projects. He is the author of several best-selling technical books, a member of the Free Software Foundation board of directors and an advisor to the Wikimedia Foundation.