The European Central Bank announced that it is exploring the use of artificial intelligence (AI) to enhance its understanding of inflation and its oversight of large banks. However, it emphasized that these efforts are still in their early stages.
The bank is investigating the application of large-language models, such as ChatGPT, for various purposes, including generating summaries and briefings to support policy-making, making public statements more accessible, and analyzing documents provided by banks.
Additionally, the bank already utilizes machine translations to communicate in multiple languages across the eurozone and is evaluating AI’s potential in nine projects.
Myriam Moufakkir, the bank’s chief services officer, stated that they will continue to explore the possibilities and challenges of using AI, and the mentioned examples are only a fraction of the potential applications.
While the primary responsibility of the central bank is to set interest rates for eurozone countries, it also oversees the largest banks in the bloc, which involves handling extensive data. AI offers novel methods to collect, cleanse, analyze, and interpret this data, stated Ms. Moufakkir. For instance, AI can automate the time-consuming task of sorting data required for economic analysis. However, monetary policy decisions, including interest rates, remain under the control of humans, specifically the members of the governing council.
Furthermore, AI can contribute to improving the central bank’s comprehension of inflation. The bank already gathers real-time data on product prices, and AI can enhance the accuracy of inflation analysis by organizing this vast amount of incoming data.
The European Central Bank’s move towards AI adoption follows an unexpected rise in inflation. Alongside the rapid increase in interest rates to alleviate price pressures, policymakers have reevaluated forecasting models and questioned their assumptions about price movements.
Other central banks are also exploring AI applications, sharing knowledge and expanding the use of machine learning. The Federal Reserve Bank of New York, for instance, will host a conference on generative AI for economists.
Last year, the Bank of England announced its utilization of AI for analyzing massive datasets, aiding in economic growth forecasts, detecting issues in banks, and assessing financial crises. Additionally, it is exploring AI’s potential in analyzing news articles, improving economic forecasting, and developing indicators to track economic trends more swiftly than traditional statistics.
Although central banks are not typically at the forefront of advanced technology, they are keen not to be left behind as AI becomes more accessible and governments strive to regulate it.
Nevertheless, central banks exercise caution amid debates surrounding the benefits and risks of AI.
According to Jon Danielsson, co-director of the Systemic Risk Centre at the London School of Economics, AI can significantly benefit central banks in areas such as risk management and routine economic analysis. However, macro problems like financial crises pose challenges, as these events are infrequent and unique, making it difficult for AI to learn from past experiences.
The European Central Bank takes a cautious approach to AI, considering factors like data privacy, legal constraints, transparency, and accountability. However, its aim is to expedite AI adoption to ensure the bank’s modernity and innovativeness.
Furthermore, the bank has collaborated with the Bank for International Settlements to explore the use of large-language models in analyzing climate disclosures by companies.