AN EXPLORATORY STUDY: Implications of Machine Learning and Artificial Intelligence in Risk Management

Technology implementations should strive to be impartial, unbiased, and neutral when applied to risk management. Risk management is a critical component within every organization and will always be a crucial component in maintaining the balance between business goals and their impact on society. The aim of this study was to explore ideas around issues including biases, discrimination, privacy, risk thresholds, moral decision-making, and business benefits that challenge beliefs and foundational values when implementing Artificial Intelligence (AI) and Machine Learning (ML) technologies in risk management. A qualitative exploratory study used a phenomenological approach with a constructivist’s worldview to understand the lived experiences of the 15 participants; allowing insights into how to identify and prevent ethical and privacy concerns in the implementation of AI and ML within risk management.

DISSERTATION