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Transparency for whom? Assessing discriminatory AI

Research output: Contribution to journalArticle

Original languageEnglish
JournalCOMPUTER
Accepted/In press6 Jun 2020

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Abstract

AI decision-making can cause discriminatory harm to many vulnerable groups. Redress is often suggested through increased transparency of these systems. But who are we implementing it for? This article seeks to identify what transparency means for technical, legislative and public realities and stakeholders.

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