Data science and technology fields have long lagged in becoming more inclusive of women and underrepresented groups. The inaugural Data & Tech for All Week, which launches Monday, highlights efforts across UC Berkeley that aim to change this reality.
The week of March 4-8 features a series of events from organizations across campus, bracketed by Monday’s Women in Data Science (WiDS) 2019 Berkeley Satellite Conference hosted by the School of Information and Friday’s Women in Tech Symposium hosted by the Women in Technology Initiative, CITRIS, and College of Engineering. The Division of Data Sciences is presenting a workshop on learning platforms designed to make data science education broadly accessible to students from a range of disciplines.
Professor Cathryn Carson, who leads the undergraduate Data Science Education Program, expressed excitement about advancing Berkeley’s commitment to engaging and respecting the perspectives of those who have historically been excluded. “Data science is one of the most important academic transformations of my lifetime,” she commented, “and I've thrown myself into making it real at Berkeley and shaping it in line with the values I and others hold dear—inclusion, equity, societal consciousness, breadth, depth, and orientation to serving students' needs.”
Data science for all only lives up to its promise if we acknowledge the social inequalities that lie beneath it, have an open exchange about the inequity they have caused, and commit to changing how we practice and teach data science.
-Cathryn Carson, Division of Data Sciences
To ensure we realize these values, Professor Carson said, it’s essential to address past and existing challenges head-on. “Data science for all only lives up to its promise if we acknowledge the social inequalities that lie beneath it, have an open exchange about the inequity they have caused, and commit to changing how we practice and teach data science,” she said. Together with Meredith Lee, Executive Director of the West Big Data Innovation Hub, she will be co-leading a session at Friday’s Women in Tech Symposium entitled Humans + Ethics + AI.
This marks the second year that the School of Information has organized a satellite session of the global Women in Data Science Conference, which is based at Stanford. “At the I School, we are keenly aware of our responsibility to educate and prepare women and other underrepresented groups to go forward to work in the tech world, where an entrenched culture of sexism and gender discrimination is no secret,” said Anno Saxenian, Dean of the School of Information.
It is widely recognized that technology and data science teams truly succeed when each member brings their own training, experience, and perspectives to the table, and that having a diversity of skill sets allows for more creative problem solving. But often that conclusion is not extrapolated further to recognize that a diversity of life experience also strengthens a team. Data scientists and technologists frame the questions that are considered worth exploring through data, algorithms, and models. If data scientists and technologists are homogenous groups with similar backgrounds and interests, it narrows the world that they explore and limits the validity of the insights they produce.
Jennifer Mangold, Fung Fellowship Innovation Coach and Women in Tech Initiative (WITI) Program Manager at UC Berkeley, recalls being the only woman in a 60-person department at Nissan. Now she focuses on building community among students, faculty, and industry along with Jill Finlayson, Director of WITI. She said the WITI symposium, which this year will explore the future of AI (Artificial Intelligence)—particularly policy and equity implications—provides an opportunity to foster broader engagement by nurturing a culture of deepened connections and mentorship. This, she said, is critical to breaking down barriers to entry for female students and postdocs. “if you’re one woman of a few, making those networks is really valuable,” she said, noting the power of “surrounding yourself with positive influences.”
Data & Tech for All Week welcomes the entire campus community to participate in building an inclusive culture in data science and technology fields. While similarity bias is embedded in human nature, our awareness of it is the first step toward combating it and supporting those whose talents have historically been overlooked.
Join the events of this special week of making data and technology truly for all!