Delegated Action & Responsibility 2026 (Dataset)
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.
DOI and Repository Links
This dataset is archived in GitHub, Zenodo, and Figshare for long-term preservation.
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}
}
Licence
Creative Commons Attribution 4.0 International (CC BY 4.0)
You are free to share, adapt, and build upon this dataset for any purpose, including commercial use,
provided appropriate credit is given to the Human Clarity Institute.
Full licence text: https://creativecommons.org/licenses/by/4.0/
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 six English-speaking countries. Participants provided explicit consent for anonymised open publication as part of HCI’s open research programme.
Sampling & participants
- Final n: 344
- Countries: United Kingdom, United States, Canada, Australia, New Zealand, Ireland
- Eligibility: Adults aged 18+ from six 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.
The cleaned dataset, variable dictionary, and reuse terms are publicly available through the HCI dataset repository: Delegated Action & Responsibility 2026 Dataset →
Data integrity
All percentages reported on this page are calculated from valid responses in the cleaned dataset (n = 344). 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 (slightly agree, moderately agree, or strongly agree).
Where percentages refer to categorical response distributions (such as intervention thresholds or responsibility attribution), the wording on the page makes that explicit. Distributions reflect the share of respondents selecting each option.
Participant IDs, timestamps, and direct identifiers were removed before publication as part of the anonymisation process.
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.
This dataset is released as open research to support transparent analysis of delegated action behaviour, monitoring and oversight, intervention thresholds, responsibility attribution, and the human experience of acting with AI systems.
