C. Thi Nguyen: Metrification

AI is based on data. And data is frequently collected with the intent to be quantified, understood, and used across context. That’s why we have things like grade point averages that translate across subject matters and educational institutions. That’s why we perform cost-benefit analyses to normalize the forecasted value of projects—no matter the details. As we deploy more AI that is based on a metrified world, we’re encouraging the quantification of our lives and risk losing the context and subjective value that creates meaning.

In this interview, we talk with C. Thi Nguyen about these large scale metrics, about objectivity and judgment, about how this quantification removes the nuance, contextual sensitivity, and variability to make these measurements legible to the state. And that’s just scratching the surface of this interview.

Thi Nguyen used to be a food writer and is now a philosophy professor at the University of Utah. His research focuses on how social structures and technology can shape our rationality and our agency. He writes about trust, art, games, and communities. His book, Games: Agency as Art, was awarded the American Philosophical Association’s 2021 Book Prize.

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