Recognizing Privacy Harm: Progress and Pressing Questions
Résumé
This contribution deepens the conceptual distinctions introduced in The Privacy Fallacy between privacy loss, privacy harm, and consequential damages. Building on Cofone’s argument that modern data practices produce harms at the informational level long before any concrete injury appears, the text emphasizes how legal standards anchored in material harm fail to capture the realities of contemporary data ecosystems.
It identifies three challenges that emerge when applying Cofone’s framework beyond conventional commercial contexts. First, institutional surveillance—such as that deployed in schools or healthcare settings—often serves protective rather than profit‑driven aims, complicating harm models rooted in exploitation. Second, contexts involving multiple stakeholders exhibit clashes of privacy values, making norm‑based adjudication difficult. Third, algorithmic exclusion generates harms that operate invisibly: opportunities are never shown, paths are quietly closed, and victims cannot perceive what has been denied. These forms of harm expose the limits of ex post liability and highlight the need for new conceptual tools capable of addressing hidden, systemic, and inferential injuries.
Mots-clés
Algorithmic exclusion – Consent illusion – Data inference – Informational exploitation – Institutional surveillance – Normative conflicts – Privacy harm