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Understanding and Mitigating Biases in AI Systems: Insights and Recommendations

In: Behavioral Finance Beyond the Basics

Author

Listed:
  • Ruti Gafni
  • Boris Kantsepolsky
  • Sofia Sherman

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.

Suggested Citation

  • Ruti Gafni & Boris Kantsepolsky & Sofia Sherman, 2024. "Understanding and Mitigating Biases in AI Systems: Insights and Recommendations," World Scientific Book Chapters, in: Itzhak Venezia & Rachel Calipha (ed.), Behavioral Finance Beyond the Basics, chapter 13, pages 299-333, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789811290633_0013
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