User Interaction Dataset for CHI 2023 paper "Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems."
DOI:10.4121/96010177-46e8-4967-9a49-fe38f0bace4e.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
DOI: 10.4121/96010177-46e8-4967-9a49-fe38f0bace4e
DOI: 10.4121/96010177-46e8-4967-9a49-fe38f0bace4e
Datacite citation style:
He, Gaole; Kuiper, Lucie; Gadiraju, Ujwal (2025): User Interaction Dataset for CHI 2023 paper "Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems.". Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/96010177-46e8-4967-9a49-fe38f0bace4e.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Software
Licence CC BY 4.0
This repo contains all code and data associated with the paper "Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems." In our study, we conducted a tutorial to mitigate the Dunning-Kruger effect. Our task is logical question answering. We provide statistical analysis to show the impact of tutorial interventions across two batches of tasks.
History
- 2025-02-06 first online, published, posted
Publisher
4TU.ResearchDataFormat
table/csvAssociated peer-reviewed publication
Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems.References
Code hosting project url
https://github.com/RichardHGL/CHI2023_DKEOrganizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Software Technology, Web Information Systems GroupDATA
To access the source code, use the following command:
git clone https://data.4tu.nl/v3/datasets/bb173377-8b33-434b-b005-0508490919cb.git "CHI2023_DKE"
Files (14)
- 5,901 bytesMD5:
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README_data_CHI2023.md - 50,922 bytesMD5:
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all_valid_data.csv - 8,264 bytesMD5:
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analysis_DKE_new.py - 12,951 bytesMD5:
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analysis_H1_new.py - 9,525 bytesMD5:
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analysis_H2_new.py - 26,538 bytesMD5:
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analysis_H3_new.py - 16,922 bytesMD5:
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analysis_H4_new_anova.py - 5,455 bytesMD5:
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analysis_time_new.py - 15,550 bytesMD5:
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analysis_trust_new.py - 7,958 bytesMD5:
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descriptive_statistics_new.py - 2,568 bytesMD5:
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explanation_usefulness.py - 4,185 bytesMD5:
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normal_distribution_analysis.py - 26,342 bytesMD5:
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selected_samples.csv - 23,567 bytesMD5:
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util.py -
download all files (zip)
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