Ethical Considerations in Ai - Ml Adoption in Financial Institutions: A Literature Review

Abstract

Purpose: The research paper "Ethical Considerations in AI - ML Adoption in Financial Institutions: A Literature Review" aims to explore the ethical dimensions surrounding the integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies within the financial industry. The primary purpose is to identify and analyze the various ethical concerns and challenges that arise from the widespread implementation of AI and ML systems in financial institutions.

Theoretical framework: The study is grounded in a comprehensive theoretical framework that encompasses ethical theories, principles, and guidelines relevant to AI and ML technologies in the financial sector. It draws upon the works of prominent ethical scholars and existing literature in the fields of AI ethics and financial regulation to provide a well-rounded examination of the subject matter.

Design/methodology/approach: The researchers conducted a systematic literature review to gather and analyze relevant academic articles, conference papers, and industry reports. They employed rigorous inclusion and exclusion criteria to ensure the selection of high-quality sources. By utilizing a systematic approach, the paper offers a well-structured and in-depth analysis of the ethical considerations related to AI and ML adoption in financial institutions.

Findings: The literature review presented in the research paper reveals a range of ethical considerations associated with the use of AI and ML in the financial sector. These findings cover diverse areas, including data privacy, transparency, fairness, accountability, bias, interpretability, and potential job displacement. The authors examine how the rapid adoption of AI and ML technologies can have both positive and negative impacts on customers, employees, and the overall financial ecosystem.

Research, Practical & Social implications: This literature review paper holds several critical implications for various stakeholders. From a research perspective, it provides an essential foundation for future studies exploring the ethical challenges in the context of AI and ML adoption in financial institutions. Practically, it offers valuable insights for policymakers, financial regulators, and industry leaders to develop robust ethical guidelines and governance frameworks to ensure responsible and sustainable AI usage in finance. On the social front, this research sheds light on the potential societal consequences of AI implementation, urging for responsible AI development and deployment.

Originality/value: The originality of this research lies in its comprehensive synthesis and analysis of the existing literature pertaining to the ethical aspects of AI and ML adoption in financial institutions. By consolidating and critically examining diverse perspectives, the paper provides a valuable resource for academics, practitioners, and policymakers interested in understanding the ethical challenges associated with AI - ML integration in the financial domain.