Critical Race Theory Reading Notes

Introduction

CRT scholars’ work

challenges the ways in which race and racial power are
constructed and represented in American legal culture and, more generally, in
American society as a whole (xiii). 

Already here some of the transdisciplinary themes emerge: The construction and representation of power in disciplinary terms; the relationship between power-within-a-field and power-between-a-field-and-society. In CS, the former conversation is often not regarded as a legitimate part of computer science (instead, it’s often considered more properly belonging to science and technology studies or media studies) and the latter is represented by efforts to define “computational thinking.”

I use trans- intentionally here, in the sense that @stornaiuolo2017 use it, not just multi-, but in relation and moving across. One goal of this project is to use the moving-across from legal studies to legitimize a flavor of CRT in CS. This may become a useful piece of our article, to look at the relationship between computation and the law. There may be some drawing-off of power from the law toward computation (e.g. Uber’s strategy of enacting new transportation regimes as a fait accompli, presuming city-level policy and legal enforcement wouldn’t be able to keep up), but there are also ways in which computation and the law have infiltrated each other.

I think legal studies is a useful analogy because there are many parallels to CS which will be broadly-recognized and will be non-controversial: it’s a discipline concerned with technical skills and the construction and deployment of power. Like computer scientists, lawyers have a job to do, and technical expertise is important. Legal institutions are bound up in broader structures like government and corporations, and play a central role in weilding power. And the law, like computation, is a form of literacy: It is powerful precisely through identification, representation, and transformation. So we can point to the work CRT scholars have done to articulate its importance within legal studies to identify a parallel space in CS.

Two common interests uniting CRT:

The first is to understand how a regime of
white supremacy and its subordination of people of color have been created and
maintained in America, and, in particular, to examine the relationship between
that social structure and professed ideals such as "the rule of law" and "equal
protection." The second is the desire not merely to understand the vexed bond
between the law and racial power but to *change* it.

We may want to organize our article around these themes. In terms of process, I’m thinking it may be valuable to just read-and-respond together to this book, and then to consolidate our notes into an article. We could rely on this text to provide the themes and organizing logic, and we could construct the CS analogy in parallel. one area where I anticipate we might need to do a little more thematic surfacing is in the relationship between the law and its media infrastructure. The law has always been dependent on print text, so there’s some chance this will be taken for granted. That said, there are plenty of places where the semiotic mechanics of language become operationalized and contentious in the law. For example the question of how to interpret the meanings of words is at the heard of legal ideologies like strict constructionism, textualism, and originalism.

In the same way, one frustration I have with some “CS is racist” narratives is that they don’t engage substantially with the computational aspects of the systems they critique, or at least this is how they present in popular representations (I need to actually read @oneil2017, @benjamin2019race, and noble2018!) In the end, what I want is a workable vision of a new comptuer science, not just critiques of current conceptions. One place we might look to is the FatML workshop. Returning to the computational thinking question of how much CS ought to extend into the social meanings and effects of computation, my reading of this workshop has in the past been that they have intentionally turned the conversation inward, addressing fairness in technical terms compatible with mainstream ML research.