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  1. What Bias Management Can Learn From Change Management? Utilizing Change Framework to Review and Explore Bias Strategies.Mai Nguyen-Phuong-Mai - 2021 - Frontiers in Psychology 12.
    This paper conducted a preliminary study of reviewing and exploring bias strategies using a framework of a different discipline: change management. The hypothesis here is: If the major problem of implicit bias strategies is that they do not translate into actual changes in behaviors, then it could be helpful to learn from studies that have contributed to successful change interventions such as reward management, social neuroscience, health behavioral change, and cognitive behavioral therapy. The result of this integrated approach is: current (...)
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  • Egocentric Bias and Doubt in Cognitive Agents.Nanda Kishore Sreenivas & Shrisha Rao - forthcoming - 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), Montreal, Canada, May 2019.
    Modeling social interactions based on individual behavior has always been an area of interest, but prior literature generally presumes rational behavior. Thus, such models may miss out on capturing the effects of biases humans are susceptible to. This work presents a method to model egocentric bias, the real-life tendency to emphasize one's own opinion heavily when presented with multiple opinions. We use a symmetric distribution, centered at an agent's own opinion, as opposed to the Bounded Confidence (BC) model used in (...)
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  • Emotion-specific recognition biases and how they relate to emotion-specific recognition accuracy, family and child demographic factors, and social behaviour.Anushay Mazhar & Craig S. Bailey - forthcoming - Cognition and Emotion.
    The errors young children make when recognising others’ emotions may be systematic over-identification biases and may partially explain the challenges some have socially. These biases and associations may be differential by emotion. In a sample of 871 ethnically and racially diverse preschool-aged children (i.e. 33–68 months; 49% Hispanic/Latine, 52% Children of Colour), emotion recognition was assessed, and scores for accuracy and bias were calculated by emotion (i.e. anger, sad, happy, calm, and fear). Child and family characteristics and teacher-reported social behaviour (...)
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  • Human’s Intuitive Mental Models as a Source of Realistic Artificial Intelligence and Engineering.Jyrki Suomala & Janne Kauttonen - 2022 - Frontiers in Psychology 13.
    Despite the success of artificial intelligence, we are still far away from AI that model the world as humans do. This study focuses for explaining human behavior from intuitive mental models’ perspectives. We describe how behavior arises in biological systems and how the better understanding of this biological system can lead to advances in the development of human-like AI. Human can build intuitive models from physical, social, and cultural situations. In addition, we follow Bayesian inference to combine intuitive models and (...)
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  • From Cognitive Bias Toward Advanced Computational Intelligence for Smart Infrastructure Monitoring.Meisam Gordan, Ong Zhi Chao, Saeed-Reza Sabbagh-Yazdi, Lai Khin Wee, Khaled Ghaedi & Zubaidah Ismail - 2022 - Frontiers in Psychology 13.
    Visual inspections have been typically used in condition assessment of infrastructure. However, they are based on human judgment and their interpretation of data can differ from acquired results. In psychology, this difference is called cognitive bias which directly affects Structural Health Monitoring -based decision making. Besides, the confusion between condition state and safety of a bridge is another example of cognitive bias in bridge monitoring. Therefore, integrated computer-based approaches as powerful tools can be significantly applied in SHM systems. This paper (...)
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  • Complex Decision-Making in Paediatric Intensive Care: A Discussion Paper and Suggested Model.Melanie Jansen, Katie M. Moynihan, Lisa S. Taylor & Shreerupa Basu - forthcoming - Journal of Bioethical Inquiry:1-11.
    Paediatric Intensive Care Units (PICU) are complex interdisciplinary environments where challenging, high stakes decisions are frequently encountered. We assert that appropriate decisions are more likely to be made if the decision-making process is comprehensive, reasoned, and grounded in thoughtful deliberation. Strategies to overcome barriers to high quality decision-making including, cognitive and implicit bias, group think, inadequate information gathering, and poor quality deliberation should be incorporated. Several general frameworks for decision-making exist, but specific guidance is scarce. In this paper, we provide (...)
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