With their ability to depict hundreds, thousands, and sometimes even millions of relationships at a single glance, visualizations of data can dazzle, inform, and persuade. It is precisely this power that makes it necessary to ask: Who is creating these visualizations? Who are they created for? Whose interests are they serving? By whose values are they informed? These are some of the questions that emerge from data feminism, a way of thinking about data and their visualization that is informed by the past several decades of feminist activism and critical thought.
Data are undeniably powerful. Thanks to devices like the FitBit and the Apple Watch, individuals can track their own data in order to eat less, exercise more, and generally improve their lives. Those same data are also often aggregated by corporations like Google, Facebook, Amazon, Microsoft, and Apple in order to customize client advertising and maximize their own profit. In business and in government, data are increasingly valued in order to make data-driven decisions. In short: data are powerful because they are financially lucrative and valued by the powerful. But they are not distributed equally, nor are the skills to work with them, nor are the technological resources to store and process them.
This is where data feminism enters in. Data feminism exposes how the people who work with data-- or, at least, the ones who get credit for it-- are not representative of the general population. It also reveals other forms of labor, like data entry and image transcription, that go into data work. Data feminism challenges what (and who and how) we count and measure. And confronts the inequities associated with hierarchical classification systems, both in data science and in the datasets themselves. Finally, it can encourage designers, data scientists, and viewers to work towards justice.
The works in this exhibition showcase a variety of feminist approaches to data visualization, bringing together ethics with aesthetics in order to challenge the unequal distribution of power and privilege that exists in the world today . In some cases, what is most urgent is to use data creatively (and humorously!) to depict gender inequalities, as in Annina Rüst's A Piece of the Pie Chart. This robot creates edible pie charts about gender differentials that gallery patrons can proceed to eat (dismantling the patriarchy one bite at a time. As it were.) Other works deploy the authority of data visualization to highlight and reclaim stolen territory. For example, Margaret Pearce worked with more than twenty First Nations groups to create Coming Home to Indigenous Place Names in Canada – a map of contemporary Canada with only First Nations names. Still others highlight biases in the data ecosystem, such as the institutional and corporate bias in what data we collect (and don't collect) in Mimi Onuoha's Missing Data Sets.
The goal of the exhibition is to provoke timely questions about data and power, as well as to showcase more emancipatory and ethical ways to use data visualization. The most vibrant innovations in data visualization today are not being developed at Facebook or Google, as one might expect, but rather led primarily by women, people of color, indigenous groups, and communities out front.