Pre-Analysis Plan for Preferences on the use and regulation of algorithms in the context of self-driving cars and ADM
收藏Mendeley Data2024-03-27 更新2024-06-27 收录
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https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/LZ5TFM
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As part of a bigger research project on the social embeddedness of autonomous systems, this study explores attitudes and preferences of individuals regarding the use and regulation of algorithms and algorithmic systems, using original data from representative online surveys administered in Germany, Japan and the United States. The first part of the study uses a conjoint experiment to provide evidence for the effect of multidimensional regulatory designs on mass support for the regulation of self-driving cars, and test the relative importance of different regulatory features. In a second step, we conduct a framing-experiment to understand the effect of different policy-frames on regulatory acceptance for self-driving cars. To explore the circumstances under which individuals accept algorithmic decision-making over human decision-making, third, we will analyze the societal acceptance of ADM in the context of hiring decisions, using a factorial vignette-experiment.
创建时间:
2023-06-28



