Entrepreneurial Perspective of AI Bias: A Preliminary Investigation

Artificial Intelligence (AI) technology is becoming increasingly pervasive in our daily lives, facilitating a wide range of tasks. However, the expanded deployment of AI also broadens the spectrum of potential problems that can impact both individuals and organizations. In this paper, we present a multiple case study based on semi-structured interviews to explore entrepreneurs’ perceptions of AI bias within the solutions designed and developed by their firms. Our results reveal two distinct interpretations of bias: the first based on technical (computational) bias and the second based on societal (systemic) bias. In particular, a coding analysis of such empirical evidence is provided. Then, drawing on these assumptions, we propose a matrix useful to assess the potential negative outcomes that different types of bias (technical vs social) can have at various decision levels. This work contributes to research by providing insights and practical tools for understanding and mitigating AI bias and a lens of analysis to foster more equitable and effective AI implementations in organizational contexts.