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Can ChatGPT Plan Your Retirement?: Generative AI and Financial Advice
By Andrew W. Lo, Jillian Ross
We identify some of the most pressing issues facing the adoption of large language models (LLMs) in practical settings, and propose a research agenda to reach the next technological inflection point in generative AI. We focus on four challenges facing most LLM applications: domain-specific expertise, an ability to tailor that expertise to a user’s unique situation, trustworthiness and adherence to the user’s moral and ethical standards, and conformity to regulatory guidelines and oversight. These challenges apply to virtually all industries and endeavors in which LLMs can be applied, such as medicine, law, accounting, education, psychotherapy, marketing, and corporate strategy. For concreteness, we focus on the narrow context of financial advice, which serves as an ideal test bed both for determining the possible shortcomings of current LLMs, and for exploring ways to overcome them. Our goal is not to provide solutions to these challenges—which will likely take years to develop—but to propose a framework and road map for solving them as part of a larger research agenda for improving generative AI in any application.
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