“At the D-Lab, we’re committed to building diversity in data science, addressing inherent prejudice in data sets, and fighting for social justice, so we created a program that would focus both on the power and opportunity of data science to create social impact, and that would also address the potential harm problematic datasets and algorithms can cause.” Claudia von Vacano, Ph.D., Founding Executive Director and Senior Research Associate of D-Lab. Dr. von Vacano is speaking specifically about D-Lab’s new Data Science for Social Justice Workshop developed in partnership with the Graduate Division. Set to begin with its second iteration this June, the 8-week cohort-based online program provides a scaffolded, project-based learning environment — designed within a social justice framework — giving current Berkeley graduate students the ability to apply data science skills and tools in their individual fields of study whether they’re coming from public health, education, law, public policy or any discipline across campus. Applications will be accepted beginning March 1 through April 15, 2023 with decisions released May 15, 2023. The Workshop runs June 12 – August 4, 2023. For more details and to apply, visit the workshop webpage. Dr. Claudia von Vacano The Data Science for Social Justice Workshop intentionally focuses on graduate students from underrepresented and marginalized backgrounds and strives for a diversity of representation. The 24 students in the first cohort spanned 19 different departments, including both Master’s and Ph.D. students, with over 70% self-identified as students of color, and roughly 70% self-identified as women, non-binary, or genderfluid. Dr. von Vacano acknowledges that within UC Berkeley, we need to increase diversity. Thus, it is essential that workshop instructors represent a diversity of backgrounds including Latinx, queer, and women of color. “It was hugely important that students in the program not only see themselves reflected in the instructional staff but also see a diversity of different ways they can inhabit a data science career,” she explains. Arlyn Moreno Luna Arlyn Moreno Luna, a first-generation immigrant and low-income graduate student, underscored the importance of diverse representation among both faculty and peers. “It took me 8 years of my higher education career before I was able to have my first Latina professor,” she reveals. “I was never seen as a college student when I was in high school; this reflects how students are labeled based on their identities or the demographics they represent.” [Read more about Arlyn’s data science journey in this Q & A.] Workshop participants are connected with current D-Lab Data Science Fellows and core staff to broaden the pipeline into data science and diversify the data science field. A highly supportive environment is essential to this effort. Soliver Fusi “The D-Lab really operates from the space of ‘it’s okay not to know’ — we’ll meet you where you are and help you get to where you want to be,” explained Soliver Fusi, a Ph.D. candidate in environmental engineering who was part of the first cohort and is now a Data Science Fellow. “I was kind of taken aback by how much support there was — they gave us a lot of their time, a lot of structure, but also a lot of freedom. That was very appealing and why I’ve stuck with the D-Lab since then. Knowing I have that support gives me the confidence to go into a more data science-driven series of projects.” The inaugural 2022 Data Science for Social Justice Workshop not only proved its success through deep engagement and positive feedback from participants. Like Soliver, many in the first cohort have also continued on with D-Lab becoming D-Lab consultants, instructors, and/or Data Science Fellows. Feedback from the first workshop has led to improvements in the upcoming 2023 program, including expanding the program from six weeks to eight to allow more time for students to get started and ramp up, and increasing the stipend from $2000 to $3000. “One of the things that surprised me was the struggles that our graduate students are facing. The amount of extra labor that students of color and underrepresented populations put in to be able to support their graduate studies is something that most mainstream students can’t even fathom,” shared Dr. von Vacano. ”Arlyn Moreno Luna is just one example of maintaining a grueling workload to support her undergrad and graduate studies.” The Curriculum: Data Science Methods Through a Social Justice Lens Immersion in the academic field of critical approaches to data science, including fairness in machine learning and artificial intelligence, is core to the workshop. The merging of disciplines — combining data science methods with social science and critical analysis about intersectionality, gender, race, sexuality, gender expression, and socioeconomic disparities — is what makes the program so highly valuable and relevant, and is in keeping with Berkeley’s unique interdisciplinary approach to graduate education. The workshop initially immerses students in Python, the prominent programming language in data science, in order to become conversant in data science methods. Students then select a project and are followed throughout the entire process including data curation, data cleaning, research question development, and interrogating a data set using data science methods. “Being introduced to Python, but specifically Natural Language Processing, was the skill, but being introduced to those data science skills through a social justice lens is what is meaningful and influences how you look at a topic and what you’re able to do with it,” explains Soliver Fusi. An example of the types of investigations workshop participants may undertake include delving deeply into social media data using Natural Language Processing. Both YouTube and Reddit provide rich datasets because such a large swath of the population engages with these channels. The Data Science for Social Justice Workshop has planted a seed that portends a flourishing ongoing collaboration between D-Lab and the Graduate Division. Dr. von Vacano concludes, “We’ve never been closer to the Graduate Division than now, where we are envisioning a future together, of moving forward and together developing this program and other programs. It’s a tremendous partnership, so we’re very excited about it.”
“At the D-Lab, we’re committed to building diversity in data science, addressing inherent prejudice in data sets, and fighting for social justice, so we created a program that would focus both on the power and opportunity of data science to create social impact, and that would also address the potential harm problematic datasets and algorithms can cause.” Claudia von Vacano, Ph.D., Founding Executive Director and Senior Research Associate of D-Lab. Dr. von Vacano is speaking specifically about D-Lab’s new Data Science for Social Justice Workshop developed in partnership with the Graduate Division. Set to begin with its second iteration this June, the 8-week cohort-based online program provides a scaffolded, project-based learning environment — designed within a social justice framework — giving current Berkeley graduate students the ability to apply data science skills and tools in their individual fields of study whether they’re coming from public health, education, law, public policy or any discipline across campus. Applications will be accepted beginning March 1 through April 15, 2023 with decisions released May 15, 2023. The Workshop runs June 12 – August 4, 2023. For more details and to apply, visit the workshop webpage. Dr. Claudia von Vacano The Data Science for Social Justice Workshop intentionally focuses on graduate students from underrepresented and marginalized backgrounds and strives for a diversity of representation. The 24 students in the first cohort spanned 19 different departments, including both Master’s and Ph.D. students, with over 70% self-identified as students of color, and roughly 70% self-identified as women, non-binary, or genderfluid. Dr. von Vacano acknowledges that within UC Berkeley, we need to increase diversity. Thus, it is essential that workshop instructors represent a diversity of backgrounds including Latinx, queer, and women of color. “It was hugely important that students in the program not only see themselves reflected in the instructional staff but also see a diversity of different ways they can inhabit a data science career,” she explains. Arlyn Moreno Luna Arlyn Moreno Luna, a first-generation immigrant and low-income graduate student, underscored the importance of diverse representation among both faculty and peers. “It took me 8 years of my higher education career before I was able to have my first Latina professor,” she reveals. “I was never seen as a college student when I was in high school; this reflects how students are labeled based on their identities or the demographics they represent.” [Read more about Arlyn’s data science journey in this Q & A.] Workshop participants are connected with current D-Lab Data Science Fellows and core staff to broaden the pipeline into data science and diversify the data science field. A highly supportive environment is essential to this effort. Soliver Fusi “The D-Lab really operates from the space of ‘it’s okay not to know’ — we’ll meet you where you are and help you get to where you want to be,” explained Soliver Fusi, a Ph.D. candidate in environmental engineering who was part of the first cohort and is now a Data Science Fellow. “I was kind of taken aback by how much support there was — they gave us a lot of their time, a lot of structure, but also a lot of freedom. That was very appealing and why I’ve stuck with the D-Lab since then. Knowing I have that support gives me the confidence to go into a more data science-driven series of projects.” The inaugural 2022 Data Science for Social Justice Workshop not only proved its success through deep engagement and positive feedback from participants. Like Soliver, many in the first cohort have also continued on with D-Lab becoming D-Lab consultants, instructors, and/or Data Science Fellows. Feedback from the first workshop has led to improvements in the upcoming 2023 program, including expanding the program from six weeks to eight to allow more time for students to get started and ramp up, and increasing the stipend from $2000 to $3000. “One of the things that surprised me was the struggles that our graduate students are facing. The amount of extra labor that students of color and underrepresented populations put in to be able to support their graduate studies is something that most mainstream students can’t even fathom,” shared Dr. von Vacano. ”Arlyn Moreno Luna is just one example of maintaining a grueling workload to support her undergrad and graduate studies.” The Curriculum: Data Science Methods Through a Social Justice Lens Immersion in the academic field of critical approaches to data science, including fairness in machine learning and artificial intelligence, is core to the workshop. The merging of disciplines — combining data science methods with social science and critical analysis about intersectionality, gender, race, sexuality, gender expression, and socioeconomic disparities — is what makes the program so highly valuable and relevant, and is in keeping with Berkeley’s unique interdisciplinary approach to graduate education. The workshop initially immerses students in Python, the prominent programming language in data science, in order to become conversant in data science methods. Students then select a project and are followed throughout the entire process including data curation, data cleaning, research question development, and interrogating a data set using data science methods. “Being introduced to Python, but specifically Natural Language Processing, was the skill, but being introduced to those data science skills through a social justice lens is what is meaningful and influences how you look at a topic and what you’re able to do with it,” explains Soliver Fusi. An example of the types of investigations workshop participants may undertake include delving deeply into social media data using Natural Language Processing. Both YouTube and Reddit provide rich datasets because such a large swath of the population engages with these channels. The Data Science for Social Justice Workshop has planted a seed that portends a flourishing ongoing collaboration between D-Lab and the Graduate Division. Dr. von Vacano concludes, “We’ve never been closer to the Graduate Division than now, where we are envisioning a future together, of moving forward and together developing this program and other programs. It’s a tremendous partnership, so we’re very excited about it.”