LLMs are one type of generative artificial intelligence (AI) which is one type of AI/machine learning which is one type of approach to computational modeling. In this episode Jake and David talk about the ethics of computational modeling, generally, and how behavior scientists might incorporate these ideas as they begin to build models specific to their everyday work settings.

In this episode, Jake and David discuss the Stanford AI Index Report (https://hai.stanford.edu/ai-index) with an eye toward the intersection of ethics, AI, and behavior science.

The term "bias" means different things to people coming from different scientific backgrounds. In this episode, Jake and David discuss those different definitions of bias, how those definitions impact the conversation around bias in AI, and recommendations for mitigating "bias" in AI systems, regardless of the point of view from which you come.

In this episode, Jake and David discuss the unique ethical concerns raised by LLMs, generative AI, agentic systems, and multi-modal AI.

For BACB Ethics CEUs, go to this site: https://www.bdspodcast.com/

In this episode, Jake and David discuss the ever-present possibility of bias in AI systems, and the resulting work and implications that has to mitigate AI bias when using LLM-driven products.

In this episode, Jake and David reflect on the many fantastic conversations of Season 4, and their thoughts on where things might go next.

In this episode, we have the distinct honor of being joined by Dr. Callie Plattner, Jenn Godwin, and Matt Filer to discuss their perspectives on quality measurement and client outcomes in Applied Behavior Analysis.

In this episode, we have the distinct honor of being joined by Kristine Rodriguez and Mahin Para-Cremer to discuss their perspectives on quality measurement and client outcomes in Applied Behavior Analysis.