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Why Data Science Is a Profound Threat for Queer People


In the magazine Real Life, tech and gender theorist Os Keyes argues that data science is fundamentally inimical to the safety and recognition of queer lives. This is because, writes Keyes, data science requires the conversion of raw reality into numbers, and queer lives resist quantification, since they cannot be easily slotted into existing categories like “male” or “female.” Here’s an excerpt:

So: trans existences are built around fluidity, contextuality, and autonomy, and administrative systems are fundamentally opposed to that. Attempts to negotiate and compromise with those systems (and the state that oversees them) tend to just legitimize the state, while leaving the most vulnerable among us out in the cold. This is important to keep in mind as we veer toward data science, because in many respects data science can be seen as an extension of those administrative logics: It’s gussied-up statistics, after all — the “science of the state” …

For me, my ethics of care says that we should be working for a radical data science: a data science that is not controlling, eliminationist, assimilatory. A data science premised on enabling autonomous control of data, on enabling plural ways of being. A data science that preserves context and does not punish those who do not participate in the system.

How we get there is a thing I’m still working out. But what you can do right now is build counterpower: alternate ways of being, living, and knowing. You can refuse participation in these systems whenever possible to undercut their legitimacy. And you can remember that you are not the consumer but the consumed. You can choose to never forget that the harm these systems do is part of the point.

Image: From ‘pU#*c’ by Tony Oursler. Via