Diversity, Equity, and Inclusion

The Division is committed to making Data Science inviting, engaging, and respectful for people of diverse identities, backgrounds, experiences, and perspectives. In our vision, equity and inclusion are essential elements of educating a rising generation of students, building a collaborative presence across campus, and serving society as a whole. Data Science raises fundamental issues of justice and participation in the ways it engages with human beings as sources of data, as analysts, and as people affected by its products. In everything the Division does, we are invested in working with our partners to shape this new field to be equitable and inclusive from the start.

In education, the Division strives to create inclusive curricula, collaborate with a diverse group of faculty, create a welcoming community that expands opportunity for students from all areas of campus, and create a pipeline of programs (such as SEEDS Scholars and Berkeley Unboxing Data Science) to expose K-12 students to data science. In research and service, the Division seeks to work with partners and to serve populations that may have been left out of Data Science in the past. We aim to co-create programs with the widest possible set of stakeholders, and we are committed to constant improvement. It is our belief that in engaging broadly, the Division of Computing, Data Science, and Society can do justice to the full diversity of the Berkeley campus and our larger society, and have ripple effects out into the world.

Our approach:

BIDS Diversity and Inclusion Working Group

The Diversity and Inclusion Working Group focuses on increasing diversity and inclusivity in data science by supporting and promoting the diverse perspectives and identities of Berkeley’s active data science research community.

Berkeley Unboxing Data Science

Berkeley Unboxing Data Science (BUDS) is a new Computing, Data Science, and Society (CDSS) summer program that immerses high school students in the world of data science and research. It aims to teach students not only how to perform data analysis, but also how to critically examine the data and technology in their daily lives.

Code of Conduct

The Division of Computing, Data Science, and Society is drafting a code of conduct[7]  to govern our interactions as a community. We are committed to enabling a diverse community of students, staff, faculty, and community members to participate in the Division’s programs with respect and safety. The Principles of Community for UC Berkeley are rooted in the campus mission of teaching, research, and public service. The University of California’s Statement of Ethical Values and Standards of Ethical Conduct commits everyone in the UC community to the highest ethical standards in furtherance of the University’s mission of teaching, research, and public service. It identifies the University’s core ethical values as integrity, excellence, accountability, and respect.

Data 8 and Connectors

Our curriculum starts with an entry-level gateway course, Foundations of Data Science (Data 8), that is designed to be inclusive and supportive. The class offers a strong conceptual foundation while minimizing barriers to entry. It has no prerequisites and is taught using a pedagogical platform that makes computing and data manipulation easy and natural. It offers additional modes of help and support to meet different learning styles, gives attention to culturally inclusive content, and is coordinated with a spectrum of Connector courses embedded in programs across campus. Data 8 draws in female and underrepresented students at a rate approaching that of the Berkeley campus at large, as well as a broad range of majors (over 60 majors in the Fall 2018 offering).

Data Scholars

The Data Scholars program was established even before the Division was formed, in order to address underrepresentation in Data Science classes from the ground up. A welcoming and supportive community, it has grown to involve a series of dedicated seminars, advising, and direct connections to research opportunities. Data Scholars operates with strong support from D-Lab, the Social Sciences Data Laboratory. This article describes the program.

Discovery Program

Data Science Discovery Projects create opportunities for students to experience sustained teamwork on projects with high potential for collaborative impact. Diverse teams of students with different backgrounds, interests, and levels of experience are supported in working together. Collaboratives explicitly foster students’ work on long-term projects oriented toward societal impact.


The Division supports and collaborates in events designed to encourage people with a variety of experiences, talents, and backgrounds to participate in data science, such as Data & Tech for All Week, and the Women in Data Science Datathon Collaboration Day.

Human Contexts and Ethics

Our students study the Human Contexts and Ethics of Data as a required part of the major. These courses critically investigate how data science can amplify societal biases or ameliorate them, depending on the diversity of those included in framing the questions and collecting and using data. As part of our larger Human Contexts and Ethics program, our classes explicitly integrate equity, inclusion, and diversity into ethical decision-making and foster students’ capacity to develop their own individual perspectives and agency. Human contexts and ethics are incorporated into technical courses as well.

I School Equity Advisor

The School of Information Faculty Equity Advisor ensures that diversity and equity are considered in all aspects of the School’s academic mission. The faculty member in this service role works with staff, faculty, and students to ensure that the School’s policies, practices, and procedures foster a friendly, fair, and professional environment. This includes participating in strategic planning, faculty recruitment, graduate student admissions, and fostering a climate of equity and inclusion. The I School Faculty Equity Advisor is supported by the MIDS Equity & Inclusion Advisor and the MIDS Gender Equity Advisor, who address related issues for the online MIDS degree program.


Our Modules program seeks to broaden the demographics of students at UC Berkeley who get their hands on data, by developing unique and accessible digital learning materials for use in existing classes across over several dozen domains. Through our collaboration with the American Cultures program, we have encouraged hundreds of students who may not have otherwise experienced data science to do so.


The Division works with partners from across campus to share knowledge, information, and resources to help foster a welcoming environment and broad participation. Partners include the Division of Equity & Inclusion, The American Cultures CenterD-LabWest Big Data Innovation Hub, the departments of Electrical Engineering and Computer Sciences and Statistics, and a variety of student groups through our Data Science Nexus. We welcome your partnership. Join us!

Student Teams and Culture

The Division’s student teams recruit from disciplines all across campus to give undergraduates opportunities to lead, form connections, and shape the Berkeley Data Science community. Teams take on projects in curriculum, internal operations, analytics, and more. Team structure changes semester to semester based on where students see opportunities for the Division to grow. A holistic, codified application review process helps teams prioritize potential members with passion for the field and a belief in a growth mindset over pure technical skills and experience.

Women in MIDS

The Women in MIDS initiative hosts focused discussions for women in the program — including faculty, students, and alumni — about their experiences in the program and their respective fields/professional domains. The group hosts regular online meetings as well as a designated discussion channel on Slack.