Making A Large Language Model Transparent, Compliant And Reliable

The article discusses the potential of Large Language Models (LLMs) and generative AI in automating business decision-making and improving customer service. However, it highlights the risks associated with LLMs, such as lack of transparency in decision-making and potential non-compliance with regulations. The author suggests combining LLMs with digital decisioning systems to mitigate these risks. Digital decisioning systems use decision models, business rules, and decision tables to automate complex decision-making processes, ensuring regulatory compliance and transparency.

The author illustrates this combination using the example of claims handling in insurance. An LLM can power a chatbot to interact with customers, gather necessary information, and call the digital decisioning system for an official decision. This approach provides customers with an easy-to-use, human-centric interaction while ensuring the decision is accurate, transparent, compliant, and reliable. The author concludes that LLMs are a powerful technology that can complement, rather than replace, expert-based decisioning solutions.

Key takeaways

Large Language Models (LLMs) and generative AI have seen a significant increase in interest due to their ability to manage complex problems, summarize complex documents, and generate readable text.
Despite their potential, LLMs pose risks such as lack of transparency in decision-making, potential non-compliance with regulations, and the possibility of providing incorrect responses.
Digital Decisioning systems can complement LLMs by providing expert knowledge in software, ensuring transparency, repeatability, and compliance in decision-making.
Combining LLMs with Digital Decisioning systems can provide an AI-driven interactive experience for customers, while maintaining the accuracy and reliability of expert-based decisioning solutions.

Making A Large Language Model Transparent, Compliant And Reliable

Key takeaways

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