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The systemic propagation and entrenchment of inaccurate or corrupted personal data across interconnected digital or bureaucratic ecosystems, resulting in material, social, or psychological harm to the affected individual.
In essence, data blight describes how a falsehood, once digitized and networked, acquires bureaucratic immortality. It exposes the fragility of “truth” in algorithmic governance, where records outrank lived reality.
This phenomenon occurs when erroneous information originating in one data source is automatically replicated, shared, or revalidated by other institutions—often through automated data exchange, identity verification, or algorithmic matching—creating a self-reinforcing web of falsehoods. Like biological blight, it spreads through interdependence, exploiting weak governance, poor data hygiene, and the absence of effective correction mechanisms.
Example: An error in one government database—such as misrecording a single person as a married cohabitant—can cascade through banking, taxation, and utilities systems, effectively rewriting the individual’s administrative identity and generating real-world consequences including denial of services, legal misclassification, or reputational harm.
The systemic propagation and entrenchment of inaccurate or corrupted personal data across interconnected digital or bureaucratic ecosystems, resulting in material, social, or psychological harm to the affected individual.
In essence, data blight describes how a falsehood, once digitized and networked, acquires bureaucratic immortality. It exposes the fragility of “truth” in algorithmic governance, where records outrank lived reality.
This phenomenon occurs when erroneous information originating in one data source is automatically replicated, shared, or revalidated by other institutions—often through automated data exchange, identity verification, or algorithmic matching—creating a self-reinforcing web of falsehoods. Like biological blight, it spreads through interdependence, exploiting weak governance, poor data hygiene, and the absence of effective correction mechanisms.
Example: An error in one government database—such as misrecording a single person as a married cohabitant—can cascade through banking, taxation, and utilities systems, effectively rewriting the individual’s administrative identity and generating real-world consequences including denial of services, legal misclassification, or reputational harm.
That error in the Electoral Register has come up again. I'm data blighted and my bank has frozen my accounts.
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