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Paper Type
panel
Paper Number
1810
Description
This panel will discuss the issues of implementing AI algorithms in organizations as they pertain to bias and fairness as complementary aspects. The panel will first put forth key problematic points and issues with regard to biases that arise when AI algorithms are applied to organizational processes. We will then propose a socio-technical approach to bias mitigation. We will further share proposals for companies and policymakers on improving AI algorithmic fairness within organizations and bias mitigation. The panel will bring together scholars who examine different social and technical aspects of bias and its mitigation, from the perspective of information systems, ethics, machine learning, robotics, and human capital. The panel will end with an open discussion of where the field of information systems can step in to guide fairness in AI algorithms in the upcoming years.
Recommended Citation
Tarafdar, Monideepa; Teodorescu, Mike; Tanriverdi, Hüseyin; Robert, Lionel Peter; and Morse, Lily, "Seeking Ethical use of AI Algorithms: Challenges and Mitigations" (2020). ICIS 2020 Proceedings. 1.
https://aisel.aisnet.org/icis2020/panels/panels/1
Seeking Ethical use of AI Algorithms: Challenges and Mitigations
This panel will discuss the issues of implementing AI algorithms in organizations as they pertain to bias and fairness as complementary aspects. The panel will first put forth key problematic points and issues with regard to biases that arise when AI algorithms are applied to organizational processes. We will then propose a socio-technical approach to bias mitigation. We will further share proposals for companies and policymakers on improving AI algorithmic fairness within organizations and bias mitigation. The panel will bring together scholars who examine different social and technical aspects of bias and its mitigation, from the perspective of information systems, ethics, machine learning, robotics, and human capital. The panel will end with an open discussion of where the field of information systems can step in to guide fairness in AI algorithms in the upcoming years.
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Comments
21-Panels