Data Feminism by Catherine D’Ignazio and Lauren Klein exists within a network of similar texts, sometimes explicitly and sometimes implicitly. The text operates in conversation with other books like Viral Justice by Ruha Benjamin, The Digital Closet by Alexander Monea, Automating Inequality by Virginia Eubanks, and Algorithms of Oppression by Safiya Umoja Noble. Each of the texts deals with the way that technology impacts our relationship to sex, gender, race, and politics. Moreover, Data Feminism (like Automating Inequality) focuses on how data is used to manipulate real-world, tangible politics.
The unfortunate thing for D’Ignazio and Klein is that they are late to my reading party; I’ve already read several related books prior to their contribution to the discourse. As a result, a lot of the information presented here isn’t exactly new or revolutionary. Some of the examples are even pulled from texts I’ve already read and so it left me feeling a little bit lukewarm.
I thought some of the language they added into the conversation was valuable. First was the idea of “privilege hazard”---essentially that one’s entitlement in society creates dangers for others, often in the form of blind spots when collecting and presenting data. That term seems useful to me for conceptualizing oppression without it necessarily assigning a particular blame and without assigning a foregone conclusion. It’s a hazard—something to consider, but also something that can be avoided or minimized. Also, something that is a hazard to us even when it is unintended. On the cheekier side, D’Ignazio and Klein use the term Big Dick Data to describe a masculinized approach to data, and I thought that was an amusing characterization.
Another layer of the book I found compelling was their discussion of data visualization and the debates which surround it. Common opinion is to present data as being value-neutral and being presented in as clear and concise a manner as possible, without even icons to suggest emotion. However, as we know, data is never neutral. Even the decision of what to include is rooted in values. So, D’Ignazio and Klein discuss the idea of data sensationalism. They describe some interesting projects with how data gets presented. For example, they describe a death-by-gun-violence map blocking out entire sections of neighbourhoods or showing a tally of “stolen years” from children that have died by gun violence. They also talk about a presentation where people read the alphabetized names of all the artists in (if I remember correctly) the MET? The Smithsonian? MOMA? Anyway, they read the names out and it becomes a wave of Marks, Jasons, Jameses, Andrews, and so forth. It cascades like a wave and then every once in a while, there is a joyful insertion of a woman’s name and the presenters change their demeanour for that brief instant. It’s a way of presenting data in such a way that the implications are immediately obvious. Exploring those creative means of presenting data to give a particular point of view were especially interesting.
In any case, the book is pretty good, if not really ‘new for me’. If you’re exploring the discourse for the first time, it would be well worth it to start here.
Happy reading!
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