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A simulation-based approach for measuring the performance of human-AI collaborative decisions

  • Despite the widespread adoption of artificial intelligence and machine learning for decision-making in organizations, a wealth of research shows that situations that involve open-ended decisions (novel contexts without predefined rules) will continue to require humans in the loop. However, such collaboration that blends formal machine and bounded human rationality also amplify the risk of what is known as local rationality, which is when rational decisions in a local setting lead to globally dysfunctional behavior. Therefore, it becomes crucial, especially in a data-abundant environment that characterizes algorithmic decision-making, to devise means to assess performance holistically, not just for decision fragments. There is currently a lack of quantitative models that address this issue.

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Author:Ganesh Sankaran, Marco Palomino, Martin KnahlGND, Guido SiestrupGND
Parent Title (English):The journey to sustainable supply chains : proceedings of the 26th International Symposium on Logistics (ISL 2022) : 10-13th July 2022, University of Nottingham, UK
Publisher:Centre for Concurrent Enterprise
Place of publication:Nottingham
Document Type:Conference Proceeding
Year of Completion:2022
Release Date:2023/01/16
Tag:Simulation modeling; Supply chain planning; System dynamics
First Page:47
Open-Access-Status: Open Access 
Licence (German):License LogoUrheberrechtlich geschützt