Reminds me of the thesis in James Scott's Seeing Like A State. This is where the effort to make things legible (easier to count, to measure) lead to standardiza

Reminds me of the thesis in James Scott's Seeing Like A State. This is where the effort to make things legible (easier to count, to measure) lead to standardizations which on turn shaped policies. For example, old growth forests were strategic assets (masts for wind-powered warships). To make then easier to count, trees were replanted in neat rows (which had the unintended sideeffects of losing eco diversity for a healthy forest). Big Data and AIs are an extension of that idea. And while the machine learning doesn't require as rigid of a classification scheme, resulta will still be understood through the lens of what can be made legibile. For example, classifying cars to estimate socioeconomic status assumes that most people within the population owns and drives cars.