Machine learning in institutional decision-support is reinterpreted as temporally situated compressions functioning as instruments of intervention within coevolving complex adaptive systems, with validity defined by real-world effects and model choices treated as political.
Paul and Cottrell, Allin F
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Machine Learning as Performative Materialist Practice: Thirteen Theses on the Epistemology, Methodology, and Politics of Applied ML
Machine learning in institutional decision-support is reinterpreted as temporally situated compressions functioning as instruments of intervention within coevolving complex adaptive systems, with validity defined by real-world effects and model choices treated as political.