Understanding and Mitigating Biases in AI Systems: Insights and Recommendations

Ruti Gafni, Boris Kantsepolsky and Sofia Sherman

Chapter 13 in Behavioral Finance:Beyond the Basics, 2024, pp 299-333 from World Scientific Publishing Co. Pte. Ltd.

Abstract: Artificial Intelligence has become an inseparable part of civilization and rapidly changes every field of human activities. In addition to the positive impact of AI on humankind, it also may have negative consequences or unintentionally harm businesses, individuals, or parts of society. Through this chapter, we explain how the embedded human nature biases may become inherited in AI systems. Then, we raise the attention of AI practitioners to the dangers of ignoring human and machine biases and provide actionable recommendations on how to mitigate this phenomenon and thus contribute to increasing trust and adoption of AI systems.

Keywords: Market Efficiency; Cross-Sectional Anomalies; Arbitrage Trading Activity; Exploiting Mispricing Dividends; Stock Repurchase; Annuity; Financial Decisions; Lump Sum. Retirement Savings; Behavioral Factors; Disruptive Innovation; Market Transition; Investments; Analyst Recommendations; Coverage Initiation; Stock Market Reaction; Artificial Intelligence; Professional Investors (search for similar items in EconPapers)
JEL-codes: G4 (search for similar items in EconPapers)
Date: 2024
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