O’Neil looks out at the land of big data and its various uses in algorithms and sees problems everywhere. Quantitative and statistical principles are badly abused in the service of “finding value” in systems, whether this be through firing bad teachers, targeting predatory loans, reducing the risk of employee turnover by using models that incorporate past mental health issues, or designing better ads to sniff out for-profit university matriculates. Wherever we look, she shows, we can find mathematical models used to eke out gains for their creators. Those gains destroy the lives of those affected by algorithms that they sometimes don’t even know exist.
Unlike treatises that declare algorithms universally bad or always good, O’Neil asks three questions to determine whether we should classify a model as a “weapon of math destruction”:
Is the model opaque?
Is it unfair? Does it damage or destroy lives?
Can it scale?
These questions actually eliminate the math entirely. By doing so, O’Neil makes it possible to study WMDs by their characteristics not their content. One need not know anything about the internal workings of the model at all to attempt to answer these three empirical questions. More than any other contribution that O’Neil makes, defining the opacity-damage-scalability schema to identify WMDs as social facts makes the book valuable.
I just came across a wonderful, short 2007 comment by Bruno Latour titled “Turning around Politics: A Note on Gerard de Vries’ Paper.” Science studies scholars, and Latour in particular, are often accused of having a wonky or non-existent notion of politics. In this essay, Latour goes a long way to clarify what sorts of politics STS scholars have done a good job of exploring, and which sorts they tend to leave by the wayside. Through his reading of de Vries, and his engagements with diverse political traditions from feminism to pragmatism, Habermas to Foucault, Latour identifies five modes of politics, five ways we might mean something is political in a useful sense. All five, he argues, must be part of our study of “cosmopolitics” in Stengers’ useful terminology. Below I reproduce the main chart that summarizes these five modes of politics – of which the first and fifth are often seen as apolitical and which STS and feminist research have made their mission to recast as political (but perhaps, in so doing, lost sight of their distinctiveness from modes 2-4).
I’ll say that I wish I’d read this paper a long time ago, as it provides a much fresher and more synthetic take on “how STS does politics” than Latour’s older (but still wonderful, and totally worth reading), “Give me a laboratory and I will raise the world”, my previous go-to piece for the subject. What do you all think?
Last weekend, Slate announced the use of social scientific tools similar to those used by campaigns themselves to anticipate results over the course of the day. Slate rejects, in editor-in-chief Julia Turner’s words, the “paternalistic” stance of the traditional media embargo on publishing results during Election Day.
Slate is making a bold move by ignoring the embargo, but in doing so they also appear to be ignoring the flaws of data science and a sacrosanct principle of both social science and journalism: skepticism.
Life doesn’t end if you drop out of graduate school. It doesn’t. No matter what anyone says, we don’t shoot, shun, or shade you for dropping out. If anyone does shoot, shun or shade you when you consider withdrawing from graduate school, they were always going to shoot, shun or shade you. Nothing lost.
The brilliant Tressie McMillan Cottom has written up some excellent advice for people considering grad school in sociology and related programs. It’s too late for most of us, but as we advise others whether and how to choose grad school, it is tremendous food for thought.
Over at SocArXiv, two University of Michigan political scientists just posted a wonderful, short comment on my stylized facts paper. In the original paper, I argue that stylized facts are empirical regularities in search of explanation, that the production of stylized facts should be understood as an important component of social scientific practice, and that stylized facts are capable of doing political work even in the absence of well-established causal explanations. In their comment, Crabtree and Fariss (C&F) offer a nice clarification in the context of experimental social scientific research programs.