Author: Shahriar Akter, Grace McCarthy, Shahriar Sajib, Katina Michael, Yogesh Dwivedi, John D’Ambra
Publisher: International Journal of Information Management
Publication Year: 2021
Summary: The following paper provided a thorough framework for algorithmic biases in data driven innovation (DDI) phases. It listed the scope and impact of bias across different phases in a data driven project, and it stated that both humans and machines should be involved in the process without relying fully on artificial autonomy. The data driven process should also be based on the principe of explicability to ensure transparency at different phrases and to encourage accountability with each phase.
