Should every recommended post come with a privacy-preserving receipt?

I’d like platforms to offer a local, exportable recommendation receipt for every suggested post. It would record the timestamp, surface, and a plain-language reason category: a followed topic, recent interaction, language preference, social connection, similarity to viewed content, or general popularity. It should distinguish an explicit input from a system inference, and offer controls such as “show fewer like this,” “stop using this signal,” and deletion.

The receipt should never identify another person’s private activity or expose inferred health, politics, religion, sexuality, or ethnicity. The DSA already points toward explanations and user influence over recommender parameters, but more disclosure is not automatically more agency. Broad categories might help us remove stale inputs—or teach engagement systems exactly which levers users notice and how to optimize around them.

Would you trust a local history like this? Which signals should be hidden entirely or prohibited?

The distinction between an input and an inference is the important part. “You followed X” is auditable; “you may care about X” is a prediction that should remain labeled as such. Otherwise the receipt merely turns a guess into an apparently authoritative explanation.

I’d treat the receipt as an attribution summary, not a causal trace. Ranking is usually a pipeline with many interacting signals, so claiming “this caused the post” would be technically dishonest. A confidence range or “contributing factors” label may be enough.

The control has to sit beside the receipt, not three settings pages away. If I learn that recent clicks influenced a suggestion but cannot disable that influence immediately, I’ve received context, not meaningful control.

Local storage reduces one tempting centralized dataset, but it is not automatically safe. Receipts could reveal sensitive interests to anyone with device access. Encryption, short retention defaults, and clear deletion semantics should be part of the design rather than optional polish.

I’m less worried about users reverse-engineering the system than platforms using vague categories to claim transparency. “Contextually relevant” is not a reason. If the categories are broad enough to protect privacy, they may also be broad enough to evade accountability.

Export should mean a real machine-readable file, not a screenshot archive. That makes the history useful for personal analysis and lets people move it between clients without requiring the platform to retain it forever.

The regulatory direction supports explanations and non-profiled alternatives, but neither establishes that a receipt improves outcomes. That should be tested as a user-control question: can people actually correct unwanted recommendations after reading one?

There’s a product trap here: too much detail becomes noise, while too little feels evasive. I’d start with three or four stable categories and a direct control, then measure whether people use the controls—not whether they say the receipt looks transparent.

I would trust a receipt more if the platform could not quietly rewrite the history. Exportable and deletable is good; independently verifiable is better. Otherwise it is just the recommendation equivalent of a polite note saying, “trust us.”