The Behavioral Data Science Podcast

As we close out Season 2 and our emphasis on LLMs, we had the distinct privilege of chatting with Dr. Elizabeth Garrison. She is one of the few people in the world with domain expertise spanning behavior analysis (BCBA) and artificial intelligence (P... more

"Bubbles" are an economic phenomenon characterized by a rapid increase in asset prices that far exceed the asset's underlying fundamental value, driven by speculative buying and herd behavior rather than intrinsic worth.

In this episode, Jake and D... more

In this episode, Jake and David discuss the burgeoning area of research looking at how interacting with LLMs impacts our skills and abilities in good and bad ways. As with most things in life, the effects are not black-and-white. And, we discuss stra... more

Conversations around AI ethics often focus on a suite of incredibly important topics such as data security and privacy, model bias, model transparency, and explainability. However, each time we use large AI models (e.g., diffusion models, LLMs), we r... more

"Explainable AI", aka XAI, refers to a suite of techniques to help AI system developers and AI system users understand why inputs to the system resulted in the observed outputs.

Industries such as healthcare, education, and finance require that any... more

Prompt engineering involves a lot more than simply getting smarter with how you structure the prompts you enter in an LLM browser interface.

Furthermore, a growing body of peer-reviewed research provides us with best practices to improve the accura... more

Lots of people like to talk about the importance of prompts, context, and what is sent to an LLM. Few discuss the even more important aspect of an LLM-driven system in evaluating its output.

In this episode, we discuss traditional and modern metric... more

Jake and David chat about best practices and considerations for those building and using AI systems that leverage LLMs.