In a world shaped by data, what happens to social justice?
UCLA cluster course draws from humanities, social sciences to examine the impact of statistics and AI
Illustration showing scales of justice, computer devices and data visualizations
February 21, 2024
|Data drives life-changing decisions in every social sector. Statistics, algorithms and artificial intelligence have the potential to rectify inequalities, but also the ability to create or exacerbate them.
For example, research has demonstrated that over-policing and disproportionate incarceration rates in communities of color are part of a cycle largely related to how the justice system uses data: Over generations, inflated crime rates and more severe sentencing patterns have fed large data sets that in turn have been unfairly used to justify increased police surveillance of these communities and harsher punishments for offenders.
These are the kinds of problems examined in “Data, Justice and Society,” a new UCLA cluster course that draws from disciplines in the humanities and social sciences to encourage students to consider what social justice might look like in a world that is increasingly being shaped and defined by datasets.
Cluster courses are immersive, year-long classes that give first-year students an opportunity to foster connections with faculty and fellow students while taking a deep dive into a multifaceted, culturally significant topic.
While data can and often does contribute to inequity, it also can be harnessed to fight injustice, said Munia Bhaumik, program director of UCLA’s Mellon Social Justice Curricular Initiatives and one of the course’s instructors.
“There are ways of mobilizing technology to resist big data,” she said, citing Million Dollar Hoods, a project based in the UCLA Bunche Center for African American Studies. That initiative, which uses data from the Los Angeles Police Department to build a case to end mass incarceration, has demonstrated that Los Angeles’ incarceration budget is largely funneled into a select few communities with an overwhelming racial bias.
In addition to Bhaumik, the course is taught by Juliet Williams, professor of gender studies; Davide Panagia, professor of political science; Ramesh Srinivasan, professor of information studies; and Todd Presner, professor of European languages and transcultural studies.
Throughout the year, the course emphasizes the need to recognize and question the human decisions and narratives that make data such a powerful social force. That human intervention is necessary, Presner said, because data cannot speak for itself; bringing a humanities perspective to the conversation is critical for understanding how to create a bridge from the numerical to the narrative.
“The humanities are creating linkages with disciplines that perhaps were traditionally seen as separate — the hard sciences, physical sciences, the social sciences,” Presner said.
In the course’s first quarter, students examined writings by Aristotle, Thomas Hobbes, Michel Foucault and W. E. B. Du Bois, prompting discussions of how data has historically been used to enact, support or resist power structures of power and oppression.
Du Bois, the historian and civil rights activist who documented the condition of Black Americans during the late 19th and early 20th centuries, also created graphics that illustrated quantifiable aspects of Black American life. First presented in 1900, his “data portraits” helped rebut claims that Black Americans had enjoyed massive progress since the end of slavery and depicted the ways in which they were being held back by ongoing segregation. Du Bois’ graphics have remained a shining example of how data can be harnessed into activism, which is why they were chosen as a springboard for the class’s explorations.
“They are a historical example that lead students into the current world of databases, data visualization and softwares,” Bhaumik said.
The winter quarter is focused on contemporary issues, such as how AI algorithms trained on incomplete or biased datasets can affect data-based decision making, and ethical questions around the technologies that make this level of data collation possible to begin with. In spring quarter, groups of 20 students each will partner with a community organization to put what they have learned into practice.
First-year student Audrey Ohwobete said the course has already convinced her to pursue a sociology major so that she can further engage with those concepts. As part of the curriculum, students watched a documentary about content moderators in the Philippines combing through gruesome content on the internet to make it safe for overseas consumers; Ohwobete said the class has brought that injustice and many others to her attention.
“Big Tech companies tend to focus on the revolutionary aspects of technology, but we’re neglecting that the reason we’re able to invest so much in tech is that we’re standing on the backs of people in developing countries,” Ohwobete said. “Every time I’ve gone into the lecture hall, there is new food for thought.”
The course has turned out to be a learning experience for the professors, too. Williams said working alongside faculty with expertise in other fields could inspire new approaches in her own research and teaching.
“The class allows us all to become students again,” she said. “That’s priceless.”
The course is a part of the Mellon UCLA Data Justice Initiative, which is co-led by Presner and Williams, and is supported by DataX.