How data discriminate
The embedding of prejudice and the animation of classification
The discriminations of data
The broad field of critical data studies can be difficult thing to keep up with. It moves at quite a pace. One book that recently caught my attention across was Wendy Hui Kyong Chun’s new book Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition. It’s just been published by MIT Press.
It reads to me like a book that will make quite a big intervention into the field. It’s a direct exploration of the way that data are part of discrimination, extending and building on some existing texts in the field. Chun’s book brings out four key concepts for thinking in broad terms about how discrimination now functions.
The book’s discussion of the relations between data and authenticity struck me as particularly important in this. Also, as I discuss in the review, Chun develops an argument about ‘reverse hegemony’ that could be important. In the review I look at how the notion of reverse hegemony fits with Chun’s vision of a more structural form of power. There seemed to me to be something to explore here in how ideology works in a context of personalisation. Chun makes some interesting arguments in this regard. More broadly though the book directly tackles the issues around prejudice and discrimination in data and also in the process, systems and practices surrounding those data. I explain this a bit more in the review.
A few weeks ago I got an email from an editor at The Conversation. They wondered if I could write something about algorithms and the popularity of the Netflix show Squid Game. It was the biggest launch so far of a show on Netflix. I hadn’t watched it, but it did seem like an opportunity to reflect on how attention is organised within platforms. However, I also thought it might be good to think about how it isn’t just about the algorithm.
For about a decade I've been trying to get to grips with the way that culture is classified. With the expansion of access to culture and content in general, all sorts of new classificatory systems have emerged. In my book Popular Culture and New Media: The Politics of Circulation I tried to develop the concept of the classificatory imagination as a way of thinking about the expansion of ways that this categorisation of content was developing. When the email came in about Squid Game I thought it was a bit of an opportunity to revisit those ideas, especially as I think in many ways it is the use of a vast grid of categories that is as important as the algorithm in grasping what is happening within streaming.
It turned out to be a tough thing to write a short piece on. It was hard to condense this bigger issue into about 700 words. The complexity of cultural classification and their implications made it difficult to manage. And some of the bigger issues inevitably had to get brief treatment. I’m not sure I’ve quite managed to get the ideas across, but it is always interesting to try to cut things down to the core ideas to see what happens. I ended up spending very little space on Squid Game but instead using that as an example to think about how trends work and how collective attention can be channeled in personalised media spaces.