This episode critically examines the foundational assumptions of behavioral economics, specifically how experts identify "bad" or "improvable" decisions. It highlights a new NBER paper which reveals that the three primary diagnostic methods used by behavioral economists to identify mistakes are inconsistent and contradict each other, challenging the validity of widespread "nudge" policies and choice architecture. Listeners will learn how this fundamental flaw undermines the rationale for paternalistic interventions, with the first diagnostic method, the Characterization Assessment, being introduced.

This episode explores the emerging "Giving Gulf" in charitable giving, revealing a stark divergence between high-net-worth individuals who are increasing their donations and the general population whose giving is significantly declining. Listeners will learn that while the wealthy are primarily motivated by impact, legacy, and personal values, the average giver faces economic pressures, creating two distinct philanthropic realities.

This episode explores a field experiment in Mozambique on HIV medication adherence, demonstrating that financial incentives significantly improve patient compliance. Listeners will learn that while money alone boosts adherence, adding a simple, low-cost text message reminder can more than double the incentive's effectiveness, highlighting the power of cognitive nudges over solely increasing financial rewards.

This episode explores the pervasive and costly issue of medication non-adherence, highlighting its staggering financial and human impact. It discusses the BETTER-BP trial, which demonstrated that while incentives can significantly boost adherence, this behavioral improvement doesn't always translate into better health outcomes, revealing a central paradox. Listeners will gain insight into the deep psychological biases, such as present bias and optimism bias, alongside practical barriers that drive this widespread problem.

This episode explores how future smart devices could generate a "longevity score" based on micro-behaviors, drawing parallels to groundbreaking research on African turquoise killifish. Listeners will learn how scientists used machine learning to identify subtle behavioral patterns ("behavioral syllables") in fish to accurately predict their remaining lifespan. The discussion also reveals a surprising "staged architecture" of aging, suggesting that decline occurs in abrupt transitions rather than a gradual process, with profound implications for human health and technology.