Unfair treatment by automated computational systems



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.
Date made available19 Aug 2022
PublisherKing's College London

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