Layered Intelligence: Generative AI Meets Classical Decision Sciences

In this talk, we'll delve into the integration of Generative AI, specifically Large Language Models (LLMs), with classical decision science methodologies. We'll see how LLMs extend beyond their typical chatbot applications to enhance traditional Natural Language Processing (NLP) and Machine Learning (ML) models. Innovative approaches will be introduced, such as AI-assisted topic modeling and a neural network featuring a generative AI-based QA review layer. This layered methodology brings a novel dimension to traditional techniques, enabling complex problem-solving, nuanced data interactions, and enhanced interpretability.

The presentation will detail the underlying methods and architectures, supplemented by real-world applications and demonstration implementations. A key highlight will be an overview of our efforts to implement these advanced AI strategies at the NIH/NICHD/RPAB (Referral and Program Analysis Branch at the National Institute of Child Health and Human Development, National Institutes of Health). We will explore how AI LLMs are revolutionizing decision sciences, driving forward strategic analytics, and elevating decision-making processes. We'll discuss how AI LLMs can breathe new life into decision sciences, advancing strategic analytics and decision-making.