there’s a lot of potential in collaborating to illuminate the systems that create data

there’s a lot of potential in collaborating to illuminate the systems that create data. Part of that potential, I think, will be realized by leveraging the different epistemological assumptions behind our respective approaches. For example, there is unquestionable value in using statistical models as a lens to interpret and forecast sociocultural trends—both business value and value to growing knowledge more generally. But that value is entirely dependent on the quality of the alignment between the statistical model and the sociocultural system(s) it is built for. When there are misalignments and blind spots, the door is opened to validity issues and negative social consequences, such as those coming to light in the debates about fairness in machine learning. There are real disconnects between how data-intensive systems currently work, and what benefits societies. — https://www.epicpeople.org/data-science-and-ethnography/
    Next → → design can be directly weaponised by the design team itself https://flowingdata.com/2018/08/30/weaponised-design/ ← Previous → TYE: We touched on data provenance earlier, but I want to come back to it from the perspective of quantitative data https://www.epicpeople.org/data-science-and-ethnography/
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