Why Smart People Are Extremely Bad at Explaining Things with Sean Malloy

Insurance fraud investigator Joe Stephenson joins Alicia Burke and Sergey Filimonov to talk about what investigators see that never reaches the data. He covers how AI is changing both fraud and the way it's caught, from synthetic IDs and fully fabricated claims to link analysis and pattern detection. He also explains why humans still need to be in the loop. Joe is VP of Innovation Technology at Lemieux and Associates.

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.

Insurance-linked securities have been part of the reinsurance market for decades. But as alternative capital expands beyond property catastrophe risk, new opportunities—and new complications—are emerging.Recorded live at the CAS Seminar on Reinsurance in Philadelphia, Bill Dubinsky of Gallagher Securities and Michael Leybov of Fermat Capital Management join Alicia Burke and Max Martinelli to explore the growing market for casualty and non-cat sidecars. They break down how these structures work, what attracts investors and insurers to them, and why reporting, servicing, standardization, and liquidity will be critical to the market’s next stage of development.The conversation also looks at what actuaries bring to this evolving market and what it will take for alternative capital to become a more established part of casualty reinsurance.

Jonathan Lim returns to Almost Nowhere one year after his first appearance to answer a simple question: what actually changed?Joined by Alicia Burke and Max Martinelli, Jonathan revisits AI, reinsurance, autonomous vehicles, and emerging technology, separating what has moved from hype to reality from what remains harder than expected. The conversation explores the challenge of operationalizing AI inside insurance companies, changing property and casualty markets, new sources of insurance data, and why the next wave of innovation may create entirely new risks for insurers to understand.From driverless cars and robotics to data centers, nuclear fusion, and the specialized expertise needed to insure what comes next, Jonathan makes the case that the future still belongs to people willing to understand risks before everyone else does.

In this episode recorded at the CAS Seminar on Reinsurance, Nick Klinka, FCAS MBA, discusses how autonomous vehicles are already affecting insurance. He explains differences between commercial and personal AV markets, coverage challenges like product liability and cyber risk, and what actuaries should watch — including regulation, data credibility, and shifting pricing variables. The conversation focuses on practical implications for underwriting, reserving, and product design as autonomy grows in pockets rather than overnight.

In our final episode from RPM in Chicago, Joanna Amorim, COO of ACTEX Learning, joins Alicia Burke and Max Martinelli to ask a bigger question: How do we prepare actuaries for an AI-enabled profession? They dig into the changing role of judgment, how we train the next generation, and why governance and accountability matter even more as AI becomes part of everyday actuarial work.