Abstract and Keywords
This chapter assesses the concepts of fairness and bias in artificial intelligence research and interventions. In considering the explosive growth, emergence of, and investment in high-profile AI fairness and ethics interventions within both the academy and industry—alongside the mounting and proliferating calls for the interrogation, regulation, and, in some cases, dismantling and prohibition of AI—it contests and questions the extent to which such remedies can address the original concerns and problems they are designed to address. Indeed, many community organizations are organizing responses and challenging AI used in predictive technologies—facial-recognition software and biometrics technologies—with increasing success. Ultimately, the canon of AI ethics must interrogate and deeply engage with intersectional power structures that work to further consolidate capital in the hands of the elites and that will undergird digital informational systems of inequality: there is no neutral or objective state through which the flows and mechanics of data can be articulated as unbiased or fair.
Keywords: artificial intelligence research, AI ethics interventions, predictive technologies, AI ethics, power structures, inequality, AI fairness interventions
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