Challenging Objective Data: A Myth?

The idea that machines allow us to see true has long been outmoded. The interpretive flexibility that pervades data collection has been especially well described in the sciences. The problem lies with our continued reliance on two-cultures dichotomies, in which objectivity and subjectivity can be neatly separated and human messiness can somehow be avoided in data collection performed by humans. When we imagine that datasets of properties like step counts speak for themselves, we negate the responsibility we hold for determining which properties will be expressed as data, in what form, and with what parameters.