Automated Decision-Making Systems for Behavioral Regulation: Understanding Perceptions and Behavioral Reactions

Automated decision-making systems for regulating human behaviors are increasingly deployed around the globe. This project investigates people's perceptions of and behavioral reactions to automated decision-making systems used for behavioral regulation; first, in experimentally replicated social scoring systems, and second, in survey-based studies on the Chinese Social Credit System (SCS). The objective of this project is to understand the overall legitimacy of these systems, the sources of harm stemming from these systems, and to identify future areas of research necessary to determine whether these systems can be ethically justified.

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Publication Details

Journal
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Published
2025-01-22
DOI
https://doi.org/10.1609/aies.v7i2.31901
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
0.00
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article

Automated Decision-Making Systems for Behavioral Regulation: Understanding Perceptions and Behavioral Reactions

Carmen Loefflad
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Mental Health Research Topics
article

Automated Decision-Making Systems for Behavioral Regulation: Understanding Perceptions and Behavioral Reactions

Carmen Loefflad
article en

Abstract

Automated decision-making systems for regulating human behaviors are increasingly deployed around the globe. This project investigates people's perceptions of and behavioral reactions to automated decision-making systems used for behavioral regulation; first, in experimentally replicated social scoring systems, and second, in survey-based studies on the Chinese Social Credit System (SCS). The objective of this project is to understand the overall legitimacy of these systems, the sources of harm stemming from these systems, and to identify future areas of research necessary to determine whether these systems can be ethically justified.

Proceedings of the AAAI/ACM Conference on AI Ethics and SocietyVol. 7(2)
Technical University of Munich (DE)
Openalex Percentile: Top 99%
Mental Health Research Topics
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