Towards Bias-Free AI-Supported Decision-Making: Exploring Organisational and Technology Characteristics for Algorithmic Bias Mitigation

Abstract: With the growing adoption of data analytics and powerful algorithms in organisational decision-making, the ethical concerns surrounding algorithmic bias have become increasingly apparent. This research aims to explore the extent to which organisational characteristics (e.g., laws, policies, norms, and standards) and technology characteristics (e.g., transparency, user control, and auditability) address algorithmic bias, examining their potential impact, and associated challenges and limitations. In order to achieve this aim, the study involves a comprehensive literature review to gather existing knowledge on the subject, followed by semi-structured interviews to collect insights and perspectives from relevant participants. Although the study findings have revealed that organisational and technology characteristics are crucial in addressing algorithmic bias, particular challenges and limitations have been shown to hinder the effectiveness of its mitigation. This study calls for further research on strategies for mitigating algorithmic bias and improvement upon the challenges and limitations identified.