CONCEPT
Epistemic Justice (AI)
The fair treatment of communities as knowers—requiring AI systems to recognize diverse knowledge forms without testimonial or hermeneutical violence.
Epistemic justice, adapted by Ramesh Srinivasan from philosopher Miranda Fricker's framework, demands that technology treat people fairly as producers and holders of knowledge. Testimonial injustice occurs when AI training data systematically excludes or discounts the knowledge of marginalized communities—indigenous agricultural practices absent from models trained on Western scientific literature, for instance. Hermeneutical injustice occurs when AI's conceptual categories cannot accommodate non-Western ways of organizing knowledge—when relational knowledge systems must be forced into taxonomic structures that strip away the connections constituting their meaning. The AI age intensifies both forms at global scale.
In The You On AI Field Guide
Miranda Fricker's 2007 Epistemic Injustice identified two forms of unfair treatment of people as knowers. Testimonial injustice occurs when prejudice causes a hearer to assign deflated credibility to a speaker's word. A doctor dismissing a Black patient's pain reports because of racial stereotypes commits testimonial injustice. Hermeneutical injustice occurs when a gap in collective interpretive resources prevents someone from making sense of their own experience—as when sexual harassment had no name and women lacked the conceptual