Datafied discrimination is opaque to subjects and operators alike, so uncorrected

Evidence

New forms of injustice inevitably result: even accidental discriminations remain opaque to subjects and system operators alike and so are likely to go uncorrected. But datafication also provides the perfect cover for older forms of inequality and discrimination to be reproduced and amplified. — Nick Couldry & Ulises A. Mejias, The Costs of Connection, 580

Categorization

• XREF: Echoes Cathy O’Neil’s ‘Weapons of Math Destruction’ on opaque algorithmic scoring, and the attention school’s claims about hidden platform architectures. — connects to: Data’s core function is differentiation, which compounds existing social discrimination. — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 125; Early statistical discrimination was visible and contestable because few variables were in play. — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 379