Published on 01 January 2022

Unfair treatment by automated computational systems

View Dataset
van Nuenen, Tom;Such, Jose M.;Cote, Mark

Description

This dataset describes the results from a prescreened survey of 663 participants describing their experiences with unfair treatment caused by automated computational systems. After cleaning, the dataset contains a list of 620 participant quotes and their demographics in an Excel spreadsheet.
The data describes experiences by users who are faced with automated decisions, strategies for harm reduction, and perceptions of fairness and discrimination. The data also includes questions on participants' self-perceived technical literacy, and several demographic questions. Participants have been anonymised.
Participants were recruited through research recruitment platform Prolific, and oversampled for "at-risk characteristics" (see paper). The data excludes 9 participants who failed at least one attention check, and 24 participants who did not finish the survey.
The DOI of the accompanying research paper is https://doi.org/10.1145/3555546.
The dataset can be shared on request for 12 months after the end of the study (30 June 2022) in accordance with participant consent and EPSRC guidelines.

Citations (1)

Mentions (0)

Metrics

Dataset Index

0.6

FAIR Score

13%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

King's College London

Assigned Domain

Subfield

Health

Field

Social Sciences

Domain

Social Sciences

Confidence Score

40%

Source

Scholar Data Model

Keywords

Fairness, accountability, transparency, trust and ethics of computer systemsHuman-computer interaction

Normalization Factors

FT

15.38

CTw

1.00

MTw

1.00