AI Ethics and Bias: Exploratory study on the ethical considerations and potential biases in ai and data-driven decision-making in banking, with a focus on fairness, transparency, and accountability

Abstract

The integration of Artificial Intelligence (AI) and data-driven decision-making in the banking industry has ushered in unprecedented opportunities for efficiency, risk assessment, and customer service. However, this rapid adoption of AI technology comes with its own set of ethical considerations and potential biases. This research paper delves into the intricate landscape of AI ethics and bias within the banking sector, with a central emphasis on fairness, transparency, and accountability. In sum, this paper contributes to the ongoing discourse on AI ethics and bias by providing valuable insights into the ethical considerations and potential biases inherent in AI and data-driven decision-making within the banking sector. It underscores the necessity of fairness, transparency, and accountability as guiding principles in the responsible integration of AI technology in banking, while also presenting future research directions for this evolving field.