Nick Stobbs explores the realities of using Large Language Models such as ChatGPT for tax research
The complexity of the UK tax code, with its 10 million words and 18,500 pages, presents a challenge for accountants seeking efficient tax research. While AI, particularly Large Language Models (LLMs) like ChatGPT, have revolutionised various fields, its application to tax research has limitations.
LLMs lack explainability, specificity, real-time updates, context understanding, and interaction capability and recent legal cases highlight the risks, such as AI generating fictitious case citations. However, the emergence of Retrieval Augmented Generation (RAG) models offers a solution. Combining information retrieval and text generation, RAG technology improves context understanding, enables real-time updates and can efficiently handle complex queries. Tax on Demand, a UK-based AI company, has introduced Copilot, a tax research tool utilising LLM and RAG technologies, addressing the challenges and aiming to strike a balance between AI efficiency and human expertise.
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