AI Decision Dependence & Cognitive Caution 2025 (Dataset)
Dataset summary: A de-identified open dataset (n=201) capturing how AI-assisted decision-making influences confidence, reliance, self-doubt, cognitive caution, and perceived influence of AI on personal judgement.
Measures include AI-decision reliance, confidence shifts when using AI tools, second-guessing behaviours, perceived influence and persuasion of AI suggestions, feelings of independence when deciding without AI, digital life exposure, clarity on what matters most, trust in AI systems, values participants believe AI should reflect, and demographic variables across six English-speaking countries.
Part of the Human Clarity Institute’s Human–AI Experience Data Series.
Framework
HRL domain(s): Agency & Decision Autonomy
Registry construct alignment: Agency, Decision dependence
Listed constructs reflect longitudinal, registry-mapped item alignment and do not represent the full thematic scope of this dataset.
Dataset Availability
Participant-level dataset downloads are temporarily unavailable while the Human Clarity Institute completes an independent privacy and data governance review.
This reflects our ongoing commitment to responsible data stewardship, contemporary de-identification standards, and participant privacy.
Study methodology, summary findings, benchmark statistics, and citation information remain publicly available through this website and the permanent Zenodo record.
Researchers, universities, and organisations interested in accessing a dataset or discussing research collaboration are welcome to contact info@humanclarityinstitute.com.
Citation & Dataset Record
The Zenodo DOI provides the permanent scholarly record for this dataset, including version history, metadata, and citation information.
Citation
APA
Human Clarity Institute. (2025). AI Decision Dependence & Cognitive Caution 2025 (Dataset). Human Clarity Institute. https://doi.org/10.5281/zenodo.17772518
BibTeX
@dataset{hci_ai_decision_dependence_cognitive_caution_2025,
author = {Human Clarity Institute},
title = {AI Decision Dependence \& Cognitive Caution 2025 (Dataset)},
year = {2025},
doi = {10.5281/zenodo.17772518},
url = {https://humanclarityinstitute.com/datasets/ai-decision-dependence-cognitive-caution-2025/},
license = {CC-BY-4.0}
}
License
Creative Commons Attribution 4.0 International (CC BY 4.0)
You are free to share, adapt, and build upon publicly available HCI datasets for any purpose, including commercial use, provided appropriate credit is given to the Human Clarity Institute.
Full license text: https://creativecommons.org/licenses/by/4.0/
Data Summary
Explore the key findings and behavioural signals from this dataset.
Methodology
This dataset forms part of the Human Clarity Institute’s Human–AI Experience research programme, examining how people use AI in decision-making, how AI affects confidence and judgement, where independence still matters, and where caution about over-reliance begins to emerge. The study uses a cross-sectional online survey design and focuses on descriptive patterns in AI-assisted decision behaviour, perceived influence on thinking, decision confidence, autonomy, trust in AI systems, and cognitive caution in digitally mediated life.
Data were collected via the Prolific research platform from adults across the United Kingdom, United States, Canada, Australia, New Zealand, and Ireland. Participants provided informed consent for their de-identified survey responses to be publicly released for research purposes.
Sampling & Participants
- Final sample: 201 participants
- Sampling countries: United Kingdom, United States, Canada, Australia, New Zealand, Ireland
- Eligibility: Adults (18+) in English-speaking countries
- Recruitment platform: Prolific
The resulting dataset should be interpreted as a non-probability convenience sample and is not intended to represent national populations.
Data Integrity
All percentages reported on this page are calculated from valid responses in the cleaned dataset. Percentages are rounded to the nearest whole number for readability. Unless otherwise stated, summary percentages combine respondents selecting 5–7 on the 7-point agreement scale.
Public release datasets undergo structured de-identification prior to publication. Direct identifiers, participant IDs, timestamps, geographic variables, and participant free-text responses are removed or transformed where appropriate to reduce re-identification risk while preserving research utility.
This dataset is exploratory and descriptive in nature. It does not support causal inference and results should be interpreted as observed patterns within the survey sample.
Data use and reuse terms are outlined in our Data Use & Disclaimer.
Related Research
Explore further analysis on Human Clarity Insights, or browse the full collection of Human Clarity Institute research reports.
