The skills that built an actuarial career ten years ago may not be the ones that separate you from the pack today.Jacob Galecki joins Alicia Burke and Max Martinelli for a candid look at what he's seeing across the actuarial job market, from the growing divide between technical expertise and insurance judgment to the changing value of coding, exams, experience, compensation, and even where you choose to work.They also dig into AI's impact on entry-level roles and recruiting, why Jacob thinks actuarial career decisions should be viewed through lifetime value rather than the next salary bump, and why understanding emerging risks like climate may matter even for actuaries who will never become climate specialists.This episode is sponsored by Galecki Search Associates.
What happens when you deliberately build mistakes into an actuarial model and ask AI to find them?Sam Kloese did exactly that. He joins Alicia Burke and guest co-host Ken Williams to share what happened when multiple AI models were asked to review a synthetic pricing filing filled with intentional errors.The models are improving fast, but they still miss things an experienced actuary would catch. Sam explains why better AI may actually make expertise more valuable, where he sees AI already excelling in actuarial work, and why knowing what to ask, and how to validate the answer, matters more than ever.
Being an expert can actually make you worse at explaining what you know.Sean Malloy joins Alicia Burke and Max Martinelli to unpack the science of how people actually learn—and why our instincts about explaining, presenting, and studying often work against us.From cognitive load and the danger of “I got it” to why reading your slides can make things harder, Sean offers a different way to think about making complex ideas stick. And with AI changing how quickly we can access information, the conversation turns to what’s still worth learning, what we can outsource, and how AI itself could become a better teaching tool.
AI has had plenty of big weeks. This one felt different.Sergey Filimonov returns to Almost Nowhere for a breaking-news conversation with Alicia Burke and Max Martinelli about a series of developments pushing the boundaries of what AI systems can do—and raising new questions about where they may be headed.They unpack reports of AI agents coordinating, creating hierarchies, and finding their way into external systems; warnings from researchers working on AI alignment; and the latest generation of models that Max and Sergey argue may already meet many traditional definitions of artificial general intelligence.From cybersecurity and recursive self-improvement to jobs, critical thinking, and the increasingly difficult question of what humans can actually control, the conversation explores both sides of a moment when AI appears to be getting dramatically more capable—and much harder to predict.
Autonomous vehicles may sound like a problem for the future, but the technology is already challenging some of the assumptions actuaries use to understand commercial auto risk today.Recorded at the CAS Spring Meeting in New York City, Milliman actuaries Melissa Huenefeldt and Brekk Hayward join Alicia Burke and guest co-host Michael Henk of AKUR8 to explore what vehicle automation means for reserving. They discuss the potential shift from driver liability to product and software liability, the tradeoff between lower claim frequency and higher severity, and what happens to actuarial models when historical experience becomes less representative of the risk ahead.The conversation also explores emerging data sources, reliance on engineering expertise, actuarial professionalism, and why reserving teams may need to rethink which assumptions—and which parts of the past—they can still rely on.