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Negative performance feedback from algorithms or humans? effect of medical researchers' algorithm aversion
Ganli Liao1, Feiwen Wang2, Wenhui Zhu3
1Business School, Beijing Information Science and Technology University, Beijing, China. glliao@bistu.edu.cn.
BMC Medical Ethics
|October 24, 2024
Summary
Negative performance feedback (NPF) from algorithms increases medical researchers' moral disengagement and scientific misconduct compared to human feedback. Algorithmic transparency and human oversight are crucial for mitigating these risks.
Area of Science:
- Behavioral Science
- Organizational Psychology
- Scientific Ethics
Background:
- Institutions increasingly use algorithms for performance feedback, replacing human managers.
- This shift raises concerns about the effectiveness and fairness of algorithmic feedback.
Purpose of the Study:
- To investigate the impact of negative performance feedback (NPF) from algorithms versus humans on medical researchers' attitudes, cognition, and behavior.
- To compare scientific misconduct, moral disengagement, and attitudes towards algorithms based on feedback source.
Main Methods:
- Two scenario-based experimental studies with 660 medical researchers.
- Study 1: Compared NPF from algorithms vs. humans on misconduct, moral disengagement, and algorithmic attitudes.
- Study 2: Examined how NPF from algorithms triggers egoism and algorithm aversion, moderated by transparency, using trait activation theory.
Main Results:
- NPF from algorithms led to higher moral disengagement, scientific misconduct, and negative algorithmic attitudes than NPF from humans.
- Algorithm aversion triggered egoism, and their interaction amplified moral disengagement, increasing scientific misconduct.
- Algorithmic transparency moderated the relationship between NPF and misconduct.
Conclusions:
- While algorithms offer efficiency in performance evaluations, they pose risks of increased scientific misconduct if not designed carefully.
- Addressing the emotional and cognitive challenges of algorithmic decision-making is vital.
- Balancing technological efficiency with moral considerations, human oversight, and transparency is essential for a healthy research environment.
Keywords:
Algorithm aversionAlgorithmic transparencyEgoismMoral disengagementNegative performance feedbackScientific misconductMore Related Videos
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