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A toolkit of dilemmas: Beyond debiasing and fairness formulas for responsible AI/ML
Approaches to fair and ethical AI have recently fell under the scrutiny of the emerging, chiefly qualitative, field of critical data studies, placing emphasis on the lack of sensitivity to context and complex social phenomena of such interventions.
Addressing contingency in algorithmic (mis)information classification: Toward a responsible machine learning agenda
We conclude by offering a tentative path toward reflexive and responsible development of ML tools for moderating misinformation and other harmful content online.
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