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Title:Game based training as a model for skill enhancement in bias mitigation efforts
Author(s):Narayanan, Sundar
Subject(s):bias mitigation
skill enhancement
machine learning
social informatics
Abstract:Organizations which are developing or deploying machine learning models, have an inherent need to enhance their bias mitigation systems to minimize harms that their models may contribute to. Currently, in organizations, bias mitigation is undertaken by addressing data quality, streamlining process, and structuring appropriate performance metrics for models. However, these approaches do not contribute to the skill enhancement specifically with reference to bias perception, understanding and treatment for people working in developing or deploying machine learning models. To that end, the paper proposes, game based intuitive method to complement and enhance the skills of people.
Issue Date:2021-10-29
Citation Info:Narayanan, S. (2021). Game based training as a model for skill enhancement in bias mitigation efforts. In Proceedings of the 17th Annual Social Informatics Research Symposium and the 3rd Annual Information Ethics and Policy Workshop at the 84th Annual Conference of the American Society for Information Science and Technology (ASIST 2021), October 29, 2021, Salt Lake City, Utah, USA.
Series/Report:Proceedings of the 17th Annual Social Informatics Research Symposium and the 3rd Annual Information Ethics and Policy Workshop
Genre:Conference Paper / Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/111786
Date Available in IDEALS:2021-10-29


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