Erin Staples

Nondeterministic AI models, like large language models (LLMs), offer immense creative potential but require new approaches to testing and scalability. Drawing from her experience running New York Times-featured Generative AI comedy shows, Erin uncovers how traditional benchmarks may fall short and how embracing unpredictability can lead to innovative, laugh-inducing results. This talk will explore methods like multi-tiered feedback loops, chaos testing and exploratory user testing, where AI outputs are evaluated not by rigid accuracy standards but by their adaptability and resonance across different contexts — from comedy generation to functional applications. Erin will emphasize the importance of establishing a root source of truth — a reliable dataset or core principle — to manage consistency while embracing creativity. Whether you’re looking to generate a few laughs of your own or explore creative uses of Generative AI, this talk will inspire and delight enthusiasts of all levels.