Human Experience Baseline (Dataset, n= 1,514)

This dataset constitutes the Human Experience Baseline, a longitudinal reference dataset published by the Human Clarity Institute to capture core dimensions of human experience in digitally mediated environments.It is designed to provide a stable measurement foundation for tracking change over time in how people experience agency, attention, cognitive load, wellbeing, values clarity, meaning, trust, and reliance on digital and AI-enabled systems.The dataset includes:• validated numeric Likert-scale measures (1–7, 0–5, and 0–4 scales)• indicators of personal agency, decision clarity, and perceived control• measures of attention, distraction, and cognitive load in daily digital life• wellbeing and psychological state items suitable for longitudinal comparison• values clarity, purpose, and meaning-related measures• trust in information environments and reliance on automated or intelligent systems• digital exposure variables (hours online, AI tool usage frequency)• demographic variables across six English-speaking countriesData were collected via Prolific from adults (18+) in the United Kingdom, United States, Australia, Canada, New Zealand, and Ireland. Participants provided explicit consent for anonymised open publication.All data were cleaned, anonymised, and processed under the Human Clarity Institute’s machine-readable dataset protocol, including:• canonical snake_case variable naming• validated numeric value ranges• standardised categorical encodings• removal of duplicate submissions• removal of all identifiers and timestamps• full alignment with the accompanying data dictionary• cryptographic checksums for file integrityThis dataset is intended to be updated through repeated data collection waves using a consistent core of measures. Each update is released as a new dataset version while retaining a stable canonical identity, enabling longitudinal analysis and comparison across time.The Human Experience Baseline underpins a broader library of topical datasets published by the Human Clarity Institute, allowing specific human–AI interaction phenomena to be interpreted relative to an established reference baseline rather than as isolated snapshots.