This article proposes using court-ordered constructive data trusts as an equitable legal remedy to address systemic privacy violations and data exploitation. Rather than relying on voluntary governance models or simple fines, this approach strips corporations of ill-gotten gains derived from massive data hoards. By reframing data governance through a reparative lens, it transforms data protection from a defensive stance into a tool for restoring extracted value directly to affected communities.
Legal Doctrine Repurposing. The proposal applies the traditional legal mechanism of a "constructive trust" as a mandatory court-ordered remedy for data exploitation, rather than relying on a voluntary management scheme.
Algorithmic Reparative Framework. The model shifts focus from compensating individual privacy violations to dismantling structural, systemic inequities and stripping corporations of ill-gotten gains.
Community Restoration. This approach moves data governance from a defensive model of "protection" to a proactive model of "reparation," restoring the value of extracted data hoards back to affected communities.
McNealy, J. (2026). Constructing a remedy for data hoards. Big Data & Society, 13(2).
