BIS-生成式人工智能在中央银行的应用

Data Science in Central BankingClosing remarks by Paolo Angelini, Deputy Governor of the Bank of Italy4th Irving Fisher Committee and Bank of Italy WorkshopRome, 20 February 2025Good afternoon ladies and gentlemen,I am happy to be here with you today as we mark the conclusion of this workshop on data science in central banking. As highlighted in the Irving Fisher Committee Annual Report for 2024, launching this periodic workshop series jointly with the Bank of Italy, back in 2019, was a far-sighted strategic decision.1 The focus of this fourth edition of the workshop, Generative Artificial intelligence (AI) and its applications in central banking, aptly underlines the ongoing transformation in the field.2 There is broad consensus that Generative AI has the potential to significantly boost productivity worldwide. According to some estimates, it could yield annual productivity gains in the $2.6 - 4.4 trillion range globally.3 Others predict an increase in output of the order of 15-20 percent, largely phased in over 15 years after adoption.4 Survey evidence collected from global corporations suggests that for over 40 percent of respondents the return on investment in the most advanced Generative AI initiatives falls within the range of 11-30 percent, and meets expectations (Fig. 1). 1 The primary goal of these workshops is to showcase projects, share expertise among central banks, and reduce reliance on external service providers. The first workshop, in January 2019, focused on "Computing Platforms for Big Data and Machine Learning". The second focused on “Data Science in Central Banking” and was organized in two parts, dealing respectively with “Machine learning applications” (October 2021), and with “Applications and tools” (February 2022). The third workshop was also on “Data Science in Central Banking”, with a focus on “Data sharing and data access” (October 2023). 2 An excellent primer on AI and central banks is in Bank for International Settlements, “Annual report”, June 2024, pp. 91-127.3 McKinsey, “The economic potential of generative AI”, June 2023.4 P. Aghion, S. Bunel, and X. Jaravel, “What AI Means for Growth and Jobs”, Project Syndicate, January 14, 2025. I. Aldasoro, L. Gambacorta, A. Korinek, V. Shreeti and M. Stein, “Intelligent financial system: how AI is transforming finance”, BIS Working Papers, no 1194, June 2024.2The uncertainty surrounding any estimate remains significant, largely due to the rapidly evolving nature of the phenomenon itself. Consider for instance the launch of the ChatGPT-like AI model “R1” by DeepSeek, a Chinese startup, at the end of January. The event cast doubt on the widespread belief that AI requires massive amounts of hardware and energy, raising questions about the leadership of the American tech industry and causing strong stock markets fluctuations. The adoption rate of AI by firms is also uncertain, but growing rapidly. In early 2024, 65 percent of respondents in a survey of international corporatio