Hello. My name is Britney Johnson and today, I'll be presenting our paper titled
"Exploring Approaches to Data Literacy Through a Critical Race Theory Perspective."
Thank you so much for joining me.
In this paper, we describe and analyze a workshop developed for a work training
program called DataWorks. In this workshop, data workers chose a topic of their interest,
sourced and processed data on that topic, and used that data to create presentations.
Drawing from discourses of data literacy; epistemic agency and lived experience;
and critical race theory, we analyze the workshop's activities and outcomes.
Through this analysis, three themes emerge: the tensions between epistemic agency
and the context of work, encountering the ordinariness of racism through data work,
and understanding the personal as communal and intersectional.
Finally, critical race theory also prompts us to consider the very
notions of data literacy that undergird our workshop activities.
From this analysis, we offer a series of suggestions for approaching designing data literacy activities,
taking into account critical race theory.
During this presentation, I will cover the sections outlined in this overview: the background, context, methodology, research questions,
key findings, implications, and acknowledgements.
Beginning with the background of our work, we have recognized how
the consideration of race and racism within technology is growing and HCI researchers are beginning to become more
attuned to the issues of race in their work. However,
the increased engagement with race has also prompted researchers to examine how this engagement occurs
and how race is embedded in technology through critical race theory, also known as CRT.
We also use CRT and its tenants as a way to frame our reflections on what it means
to support equitable computing and data practices in the context of everyday work.
The context of this research is DataWorks, a workplace training program housed within the university
where people from historically minoritized and underrepresented communities
are employed and learn basic data skills such as cleaning, formatting, and labeling datasets.
This approach draws from other training programs that aim to increase individual data skills,
such as bootcamps and virtual courses; however, our program differs in its design to specifically
engage underserved communities in data work through an authentic work environment instead of
through formal coursework. Through DataWorks, we aim to foster unique approaches to data literacy and data work.
The methodology we leveraged for our research involved ethnographic methods
and participatory design workshops. We used data collected through audio, video, and photographs;
as well as semi-structured interviews and focus groups to conduct our qualitative analysis.
This analysis was conducted by four of the authors, who read the transcriptions
and watched videos to identify themes and patterns. These themes and patterns were refined by the
research team through several discussions.
The PD workshops developed were scaffolded into a four-step process to guide each activity.
These four steps included 1. specify a problem, 2. find applicable data,
3. analyze and organize this data so that it can be shared with a broader audience,
and 4. communicate this data to other people.
The conception of these workshops were to examine two key research questions in more detail. These questions ask: How do the
data workers develop and practice data skills while addressing a problem of interest to them?
And how does the lived experiences of the data workers impact the data work they engage in?
Out of the key findings that emerged from our analysis, one of these findings presents
the tensions between epistemic agency, critical data literacies, and the work context.
Our hypothesis was that the Data Workers would develop their own personal approaches to data work,
but we did not find evidence of this in our findings nor did we find that the data workers
brought their critical perspectives to the data they gathered. However, we argue that this is
not the fault of the data workers and should not be interpreted as a lack of engagement with the
data process or the exploration of the data. Instead, if the data workers were empowered to
be skeptical of the process and develop critical perspectives of data then epistemic agency would have been demonstrated.
This directs us to the implications we present in our work,
one of which is the need to critically engage the context of work.
K-12 education programs and community engagement events are contexts that are often already critical. However,
the context of work involves power dynamics and cultural context, and is uncritical in itself.
CRT prompts us to examine our own liberal biases that may cause us to expect the data workers to
develop a critical perspective to data or the data process in the context of work. If we want
to pursue critical data literacy in the context of work, then the context of work must itself be
approached as an environment and process open to critique and refiguration.
Thank you so much for joining me during this presentation. We'd like to extend our sincere thanks
to those who have provided generous support for our work and feedback on our paper.