Digital Trust 2025 (Dataset, n = 505)

This dataset is part of the Human Clarity Institute’s <b>AI–Human Experience 2025</b><b> </b>data series. It examines digital trust, authenticity judgement, and uncertainty in an AI-saturated information environment, including perceived manipulation risk, confidence in detecting synthetic content, and behaviours triggered by doubt or ambiguity.The dataset includes:<br>• validated 1–7 Likert-scale items<br>• measures of trustworthiness assessment, uncertainty effects, and detection confidence<br>• behavioural indicators of verification habits, caution, and avoidance<br>• multi-select variables stored as canonical semicolon-delimited snake_case tokens<br>• open-text reflections with minimal safe cleaning (trim + newline removal only)<br>• demographic variables across six English-speaking countries<br>• digital life exposure (daily hours online) and AI-tool usage frequencyData were collected on 25 November 2025 via Prolific from adults in the UK, US, Australia, Canada, New Zealand, and Ireland.<br>All data were cleaned, anonymised, and processed under the Human Clarity Institute’s machine-readable dataset protocol, which includes:• canonical snake_case variable naming<br>• validated numeric ranges<br>• standardised multi-select formats<br>• minimal safe text cleaning<br>• full alignment with the accompanying data dictionary<br>• removal of Prolific IDs and timestamps<br>• SHA-256 checksums for all filesThis dataset contributes to understanding how people judge trustworthiness and navigate uncertainty in an AI-shaped digital ecosystem, supporting longitudinal tracking of authenticity perception, online doubt, verification behaviour, and the evolving cognitive relationship between humans and AI.