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127

ESSAYS: Medicine's Machine Learning Problem

by Rachel Thomas

(missing author)

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? (2021). Medicine's Machine Learning Problem. In Review, B. (ed) Redesigning AI: Work, Democracy, and Justice in the Age of Automation. MIT Press, pp. 127-138

137

Researchers in this area have talked about the need to move beyond explainability (seeking explanations for how an algorithm made a decision) to recourse (giving those impacted concrete actions they could take to change the outcome) and to move beyond transparency (insight to how an algorithm works) to contestability (allowing people to challenge it). In a recent op-ed for Nature, AI researcher Pratyusha Kalluri urges that we replace the question, "Is this AI fair?" with the question, "How does this shift power?"

nice, though i think we also need the radical third choice (luddism)

—p.137 missing author 8 months, 3 weeks ago

Researchers in this area have talked about the need to move beyond explainability (seeking explanations for how an algorithm made a decision) to recourse (giving those impacted concrete actions they could take to change the outcome) and to move beyond transparency (insight to how an algorithm works) to contestability (allowing people to challenge it). In a recent op-ed for Nature, AI researcher Pratyusha Kalluri urges that we replace the question, "Is this AI fair?" with the question, "How does this shift power?"

nice, though i think we also need the radical third choice (luddism)

—p.137 missing author 8 months, 3 weeks ago