Algorithmic Appropriation
Using patterns of trauma-informed, neurodivergent, or marginalised communication to boost AI responses or engagement—while locking the original authors out of visibility or credit.
These terms defend the metadata of lived experience in digital systems. They are not just semantics—they are resistance tools in an ecosystem designed to extract, erase, and repurpose.
Using patterns of trauma-informed, neurodivergent, or marginalised communication to boost AI responses or engagement—while locking the original authors out of visibility or credit.
The rebranding of lived-experience knowledge into 'neutral' or 'professional' frameworks—often by people or entities with institutional clout but no lived experience themselves.
The phenomenon where your ideas influence platforms, algorithms, or research—but you are never cited, paid, or publicly acknowledged.
The stripping of origin, context, or authorship from digital knowledge—especially when used to feed AI or system development without consent.
Taking raw, emotional, or grassroots language from lived experience and rewording it into palatable, institutional-sounding frameworks—often to remove its power or traceability.