Human Involvement in AI Systems: Implications for Bias in Financial Decision-Making
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Ashley De La Rosa-Hanlon
College:
College of Business and Public Management
Major:
Accounting
Faculty Research Advisor(s):
Huaibing Yu
Abstract:
The introduction of artificial intelligence (AI) into financial systems marked a new era of efficiency and innovation. However, these developments raise concerns about the possibility of embedded biases in AI systems, particularly in the area of financial risk management. This research project intends to examine the link between artificial intelligence and finance, with a focus on the risks associated with potential biases present in AI systems. Through literature reviews, case studies, and industry practices, we hope to discover the basic factors that drive AI biases in finance, including data selection, algorithmic design, and human involvement.
Additionally, this poster will discuss the ethical implications of AI biases in finance. By emphasizing the need of fair, transparent, and accountable decision-making processes, this research aims to inform others on the need for proactive measures to reduce bias-related risks. Through this research, I hope to add to the ongoing discussion about the appropriate use of AI in finance by pushing for strategies that maintain integrity and foster trust in financial markets.