AI Media & Online Authenticity 2025 (Dataset n = 202)

This dataset is part of the Human Clarity Institute’s **AI–Human Experience 2025** data series. It examines how people judge the authenticity of online content in an AI-saturated environment, including confidence in verification skills, susceptibility to doubt and uncertainty, and the behavioural effects of AI-generated media.<br>The dataset includes:• validated 1–7 Likert-scale items • measures of authenticity judgement, trust in personal verification ability, and uncertainty effects • indicators of behavioural caution, second-guessing, and confidence shifts • multi-select variables stored as canonical semicolon-delimited snake_case tokens • open-text reflections with minimal safe cleaning (trim + newline removal only) • demographic variables across six English-speaking countries • digital life exposure (daily hours online) and AI-tool usage frequency <br>Data were collected on **November 2025** via Prolific from adults in the **UK, US, Australia, Canada, New Zealand, and Ireland**. All data were cleaned, anonymised, and processed under the Human Clarity Institute’s **machine-readable dataset protocol**, which includes canonical snake_case variable naming, validated ranges, standardised multi-select formats, minimal safe text cleaning, alignment with the accompanying data dictionary, removal of Prolific IDs and timestamps, and SHA-256 checksums for all files.<br>This dataset contributes to understanding how AI-generated media shapes human certainty, trust, and judgement, enabling longitudinal tracking of authenticity concerns and the evolving cognitive relationship between humans and AI.