Delegated Action & Responsibility 2026 (Dataset)
Dataset summary: A de-identified open dataset (n=344) examining delegated AI action, monitoring behaviour, intervention thresholds, and responsibility attribution in AI-mediated decision environments across six English-speaking countries.
Measures include validated 1–7 Likert-scale instruments assessing comfort with AI delegation, decision intervention thresholds, oversight behaviour, perceived accountability, and responsibility allocation following negative outcomes, alongside digital exposure metrics, AI usage frequency, and standard demographic variables.
Part of the Human Clarity Institute’s Human–AI Experience Data Series.
Framework
HRL domain(s): Agency & Decision Autonomy, Trust & Epistemic Stability
Registry construct alignment: Agency, Decision dependence, Trust calibration, Responsibility attribution, Risk perception
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. (2026). Delegated Action & Responsibility 2026 (Dataset). Human Clarity Institute. https://doi.org/10.5281/zenodo.18626641
BibTeX
@dataset{hci_delegated_action_responsibility_2026,
author = {Human Clarity Institute},
title = {Delegated Action \& Responsibility 2026 (Dataset)},
year = {2026},
doi = {10.5281/zenodo.18626641},
url = {https://humanclarityinstitute.com/datasets/delegated-action-responsibility-2026/},
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 delegate actions to AI systems, how closely they monitor outcomes, where they intervene, and how responsibility is assigned when AI-mediated decisions produce negative outcomes. The study uses a cross-sectional online survey design and focuses on descriptive patterns in delegated action behaviour, monitoring and oversight, intervention thresholds, and responsibility attribution 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: 344 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.
