Data extraction costs fall hardest on the vulnerable under a moralistic blame frame.

Evidence

The principle of seamfulness therefore becomes a potential tool for resisting social worlds that are less accountable, harsher, and characterized by ever higher levels of inequality, mistrust, and despair. It also alerts us to the danger that without seamfulness, the social costs that data colonialism generates will simply be passed down to the most vulnerable, quite possibly on the basis that they somehow “deserve” it, exactly the form of “moral behaviorism” that has for two decades characterized neoliberal societies. — Nick Couldry & Ulises A. Mejias, The Costs of Connection, 608

Categorization

• XREF: The ‘moral behaviorism’ and desert-based blame echoes the reader’s ‘On Sacrifice’ piece themes about rationalizing who bears costs in stratified societies. — connects to: Repairing algorithmic harms requires resources the poor already lack. — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 484; The bad-apples framing deflects blame from systemic causes; Moral ambiguity enables perpetrators to shift blame and deny responsibility. — Albert Bandura, Moral Disengagement: How People Do Harm…, 218
• QUESTION: Where does the punitiveness of ‘punitive data extraction’ show up concretely — debt collection, welfare surveillance, insurance recalibration?

Broader Connections

• The bad-apples framing deflects blame from systemic causes #expands (0.82)
• Moral ambiguity enables perpetrators to shift blame and deny responsibility. #expands (0.75) — Albert Bandura, Moral Disengagement, 218