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Users may perceive algorithmic systems as unjust even when they meet formal fairness criteria, risking trust and acceptance.
Counterfactual explanations can mislead by masking critical upstream decisions that shape model outputs, challenging their normative legitimacy in AI justification and recourse.
Existing German algorithm registers fall short of transparency goals, revealing critical gaps that could undermine public trust in AI systems.
