Dykee Gorrell, Digital and Data Literacy Librarian and Data Services Lead at Dr. Martin Luther King Jr. Library

“Science has always been political. Technology has always been political. When we study history, we know that to be true.”

Dykee Gorrell is the Digital and Data Literacy Librarian and Data Services Lead at Dr. Martin Luther King Jr. Library and a preeminent scholar in her own right.

With a background in community organizing and a Bachelor’s degree in Africana Studies and Critical Race Theory, Ms. Gorrell took a circuitous route to the information sciences: “I was a history girl. I wasn’t a data or a computer girl.” But, motivated by a desire to better understand the technology she relied on – both as an academic researcher, and in everyday life – Ms. Gorrell began to teach herself rudimentary coding and ultimately found her path leading to data librarianship.

As a part of King Library’s Black History Month programming, on Thursday, February 5, Ms. Gorrell will present a vital and timely event exploring perspectives in data and information science through the lens of critical historical analysis, Black and Africana studies, and anticolonial scholarship. 

The workshop, “Critical Data Visualization: Black History Month Edition,” is open to all and will be held in-person and virtually from 12-2 p.m. PST. She spoke in anticipation of the event about the importance of critical data literacy, statistical violence, and historicizing technological praxis.

What can attendees expect from the Critical Data Visualization workshop? 

The event will include a presentation by Ms. Gorrell, a Q&A session, and a hands-on workshop for in-person participants. Attendees will gain understanding around how data visualization methods either “critique or perpetuate power” with particular emphasis on how data practices reflect the logics of “exploitation, fungibility, and extraction” engendered by white supremacy, colonialism, and capitalism. 

Ms. Gorrell has designed the workshop to offer compelling and provoking analysis, historical knowledge, and opportunities for participation and hands-on practice. Working with real data sets and visualization tools, participants will be guided through dynamic exercises that explore how font, color, and structure contribute to meaning-making. The activities are designed to invite questions about how choices such as plot design “tell a larger story about the political intentions of the people who are creating the data visualization – and how that ends up affecting how we understand the information that’s being shown to us.”

Defining “Statistical Violence”

“Information science, when used incorrectly or when used violently, can affect massive amounts of people,” says Ms. Gorrell. “Statistical violence” refers to the weaponization of data analytics now and throughout history. This articulation demands we pay attention to the ways in which accounting, qualification, algorithms, and surveillance have contributed to dehumanization and systemic harms – from the meticulous planning and quantification schema that gave structure to chattel slavery, to the predictive algorithms used by law enforcement and the criminal-legal system to strategically police targeted communities under the guise of technological neutrality.   

“When you reduce someone down to a series or set of numbers, what are you actually doing to the humanity of that person?” Ms. Gorrell asks, adding that “trying to usurp that understanding of how we understand people” motivates her work as both a historian and data scientist.

Bringing A Historical Perspective to Technology

Technology-forward fields are often hyper-fixated, understandably, on innovation and new capabilities. This is especially true now, as AI is rapidly changing the information landscape and introducing new tools. Ms. Gorrell’s work highlights the importance of a socio-historical perspective for data scientists and information professionals.

“When we think about the future, oftentimes, we erase the past in order to absolve ourselves from the accountability and responsibility of addressing the communal harm. [But] history is past, present, and future […] it doesn’t just exist linearly.” Gorrell’s work points to the continuities and throughlines that are elucidated by studying the historical trajectory of scientific management and surveillance technologies. Often, she says, “our concepts of innovation aren’t necessarily separate from ancestral technologies, or from past technologies,” and may be better articulated as reiterations or escalations of long-standing methods.

Ms. Gorrell emphasizes that understanding historical context and developing critical thinking about data science are imperative for professionals to improve their work, regardless of their career focus. “If you really want a job in tech, you have to be able to critique things,” she explains. 

Especially as AI is being integrated into data analysis and visualization workflows, critical data literacy underscores the imperative to have a thoughtful, historically grounded, and discerning perspective that drives the work. 

Data Visualization is Information Literacy

Alternatively, for those new to data visualization, the event will teach some fundamental technical skills, methods and tools. The goal is that by the end of the afternoon workshop, attendees will “be able to grasp and gather understanding of complex visualizations [and] also be able to critique them.” 

“We’re living in times that are changing the way in which we think about information and data,” says Ms. Gorrell. The workshop is designed to not only teach attendees the fundamental tools of data visualization methods, but also to instill a “critical understanding of what data visualization is, what it does, how it communicates knowledge and information and thought.”

The Value of An Interdisciplinary Approach

Ms. Gorrell’s work demonstrates the interconnectedness between technology studies and Black epistemologies, critically engaging information science as a site and a mechanism of social control, and of anti-colonial counterinsurgency. This insistence on drawing linkages between often siloed disciplines is an instructive example of how thinking expansively and collaboratively leads to generative research.

Her forthcoming book reflects this: combining her skills in historiography, postcolonial theory, and data visualization, and drawing on the ecological field of dendrochronology (the study of tree rings), the research examines the intersections of slavery, carceral regime management, and monocrop agriculture during the colonization of the Americas. 

“Oftentimes, computer science – And, really, all STEM […] it’s all viewed as apolitical. But it’s not. Science has always been political. Technology has always been political. When we study history, we know that to be true.” Ultimately, “I want to be able to bridge these worlds together.”