The Federal Reserve’s leadership seemingly views generative AI as a “super analyst” capable of turbocharging the agency’s work process.
Leaders at the United States Federal Reserve appear convinced that generative artificial intelligence tools will function as a “super analyst” for banks and the government — one capable of handling customer service duties for banks and replacing human programmers. Sunayna Tuteja, the Federal Reserve’s chief innovation officer, recently spoke at the Chicago AI Week event in a fireside chat with Margaret Riley, SVP at the payments unit of the Fed’s financial services division.from financial news and analysis outlet Risk.net, Tuteja and Riley discussed five use cases for generative AI being explored by the Fed: data cleansing, customer engagement, content generation, translating legacy code and enhancing operational efficiency.
On the subject of “translating legacy code,” Tuteja appeared to lean into the idea that large language models , such as ChatGPT or similar AI products, could replace some jobs traditionally reserved for humans: “It’s hard to justify coding developers to update all old code to new code, but now you can leverage LLMs and then the developer becomes the auditor or the editor versus the primary doer.”The two were careful to stress that generative AI and LLMs have their limitations and that the use cases discussed were exploratory at the present time.