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Federal Reserve: Artificial Intelligence and Bank Supervision

Author

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  • John Mullin

Abstract

Artificial intelligence has come a long way since English mathematician, logician, and cryptographer Alan Turing's seminal 1950 essay, "Computing Machinery and Intelligence," which explored the idea of building computers capable of imitating human thought. In 1997, almost 50 years after Turing's essay, AI posted a historic breakthrough when the IBM supercomputer Deep Blue won a chess match against reigning world champion Garry Kasparov. Since then, AI's capabilities have improved rapidly, largely through advances in machine learning (ML), especially in ML models that use digital neural networks to classify text, images, or other data. (See "Machine Learning," Econ Focus, Third Quarter 2018.) ML is now commonly used in industrial applications, and it underpins a vast number of consumer services, from Google searches to Netflix movie recommendations. Of more recent note, ML technology is the basis of the new generative AI programs, such as ChatGPT, designed to, among other things, conduct useful conversations with human beings.

Suggested Citation

  • John Mullin, 2023. "Federal Reserve: Artificial Intelligence and Bank Supervision," Econ Focus, Federal Reserve Bank of Richmond, vol. 23(2Q), pages 8-11.
    • Handle: RePEc:fip:fedrrf:96252
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    File URL: https://www.richmondfed.org/-/media/RichmondFedOrg/publications/research/econ_focus/2023/q2/federal_reserve.pdf
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    Cited by:

    1. Grigorescu Aura Elena, 2024. "Artificial Intelligence in Central Banking," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 18(1), pages 1892-1901.

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