5 Opportunities and pitfalls of GenAI

Navigating the GenAI Frontier: Five Insights for Business Leaders

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We encounter a rich field of possibilities and pitfalls in the unexplored terrains of Generative Artificial Intelligence (GenAI). Navigating this complex web of opportunities and pitfalls associated with GenAI and large language models (LLMs) like ChatGPT needs to be understood.

If you knew about GenAI and ChatGPT before this article, you jumped at the chance. The first use case in any industry where data drives decision making is “summarization”. This is not surprising; people are lazy and want to get information quickly and accurately. GenAI serves as a basic tool here.

For example, you can take this article and copy/paste it into ChatGPT. This will be the result:

Plus, you can take big, boring legal documents and have LLM (Large Language Model) summarize it for you in seconds. As a result, financial professionals can harness the power of GenAI to be more efficient and ensure that decisions are well-informed.

Despite its impressive abilities, GenAI is bug free, tending to hallucinate if it doesn’t know the answer. LLMs simply predict the next word and are so good at fooling people into thinking LLMs are smart. The truth is that you can never really be sure that what you are getting is not a hallucination because LLMs tend to be very convincing in their output.

In a world like finance, such inaccuracies, no matter how marginal, can have cascading effects that can lead to wrong decisions and resulting financial losses. Hallucinations can come from biases in the training data or flaws in algorithms that can produce summaries that can skew numbers, predict inaccurate trends, or leave out critical information.

Therefore, it is highly recommended to keep one in the loop and never take the LLM answer as a 100% true result.

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