9,320 rated or chosen profiles from 932 respondents, in up to 5 tasks of 2 profiles varying on 7 attributes.

About this table

Description	Respondents in Germany, the UK, China, Chile and India (n=932) saw pairs of AI algorithms described by seven attributes (privacy, unemployment risk, job creation, discrimination, transparency, decision area, dilemma choices) and picked the one that should be prohibited; 5 tasks x 2 profiles.
Reference	Ehret, S. (2022). Public preferences for governing AI technology: Comparative evidence. Journal of European Public Policy, 29(11), 1779-1798.
DOI	10.1080/13501763.2022.2094988
Licence	CC BY 4.0
Source data	https://doi.org/10.6084/m9.figshare.20537781

Notes

Conjoint table (irw_conjoint_2). Which of two AI algorithms should be prohibited (choice = 1 for the one chosen for prohibition, forced, no opt-out); five samples pooled (cov_country). Level text is the appendix Table 1 wording recoded from short codes; profile order inferred from row order; the 1-7 approval rating is not in the deposit. N = 932 respondents, as in the paper's Table 7.

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents	932
Rows (one per respondent, task and profile)	9,320
Tasks per respondent (most)	5
Profiles per task	2
Attributes	7
Tasks with no profile chosen	0

Design

Topic	technology ai privacy
A profile represents	policy
Country	DE, GB, CN, CL, IN
Language shown	unknown
Language of stored levels	en
Randomization restrictions	unknown
Task order	recorded in the deposit
Profile position	inferred from row order

Task order or profile position was rebuilt from row order; analyses of position or task order should leave it out.

Outcomes:

choice	Which of the algorithms should be prohibited? [choice, forced]

Columns

attr_choices_in_dilemmaattr_decision_areaattr_discriminationattr_job_creationattr_privacy_protectionattr_risk_of_unemploymentattr_transparencychoicecov_countrycov_living_standard_confidencecov_privacy_concerncov_unemployment_insurance_relianceidprofiletask

The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.

Get the data

Download CSVno account needed Browse on Redivisexplore and query Croissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("ehret_2022_ai_governance", source = "conj")

# Python
pip install irw

import irw
df = irw.fetch("ehret_2022_ai_governance", source="conj")

How to cite

@article{Ehret_2022, title={Public preferences for governing AI technology: Comparative evidence}, volume={29}, ISSN={1466-4429}, url={http://dx.doi.org/10.1080/13501763.2022.2094988}, DOI={10.1080/13501763.2022.2094988}, number={11}, journal={Journal of European Public Policy}, publisher={Informa UK Limited}, author={Ehret, Soenke}, year={2022}, month=Aug, pages={1779–1798} }

Version and provenance

IRW version	v584
Redivis dataset	irw_conjoint_2 v1.4
Redivis dataset DOI	10.57761/hk97-wv30
Manifest pin for this IRW version	v1.4
Metadata source	irw_meta v44.0