The field of neuroscience has been collecting more and more data, and developing increasingly advanced technological tools in its race to understand how the brain works. But can those data and tools ever yield true understanding? This episode features neuroscientist and computer scientist Eric Jonas, discussing his provocative paper titled "Could a Neuroscientist Understand a Microprocessor?" in which he applied state-of-the-art neuroscience tools, like lesion analysis, to a computer chip. By applying neuroscience's tools to a system that humans fully understand (because we built it from scratch), he was able to reveal how surprisingly uninformative those tools actually are. Julia and Eric also discuss the related question: what kind of tools *would* we need to really understand the brain?

You may have heard of the Implicit Associations Test (IAT) -- one of the most famous instruments from social psychology, it's frequently cited as evidence that most people harbor implicit racism or sexism, even if they aren't aware of it. This episode features science journalist Jesse Singal, who argues that the IAT has been massively overhyped, and that in fact there's little evidence that it's measuring real-life bias. Jesse and Julia discuss how to interpret the IAT, why it became so popular, and why it's still likely that implicit bias is real, even if the IAT isn't capturing it.

There are a lot of sensitive topics about human nature that would be interesting to study, such as people's sexual behavior, or how racist people really are. Researchers studying those questions have always faced the problem that we tend to lie on surveys -- but we don't lie to Google. This episode features Seth Stephens-Davidowitz, economist and data scientist, and author of the book Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. Seth and Julia discuss the insights new research gives us into which parts of the USA are more racist, what kinds of strategies reduce racism, whether the internet is making political polarization worse, and the sexual fetishes and insecurities people will only admit to their search engine.

You've probably heard of Pascal's Wager: That it's rational to believe in God, because if you're wrong it's no big deal, but if you're right then the payoff is huge. This episode features philosopher Amanda Askell, who (though not religious herself) argues that it's much trickier to rebut Pascal's Wager than most people think. Amanda and Julia also discuss how to handle other decisions where a risk has very low probability but would matter a lot if it came true -- should you round them down to zero? Does it matter how measurable the risk is? And should you take into account the chance you're being scammed?

In this episode Julia sits down with neuroscientist and obesity researcher Stephan Guyenet, to talk about what scientists know so far about the causes of obesity, and in particular the brain's role in regulating weight gain. Julia and Stephan cover questions such as: Why did obesity start to increase in the United States in the latter half of the 20th century? Does the body have a "set point" of fat that it tries to defend, and what affects those set points? Are low-carb diets more effective for weight loss than low-fat diets, and if so, what explains the difference?

In this episode, recorded live at the Northeast Conference on Science and Skepticism, Julia interviews evolutionary psychologist Rob Kurzban, author of "Why Everyone (Else) is a Hypocrite." Rob describes the "modular mind" hypothesis, and how it explains hypocrisy, self-deception, and other seemingly irrational features of human nature. Rob and Julia argue about how useful these kinds of "strategic wrongness" really are.

What determines which policies a person votes for? Is it their personality, their upbringing, blind loyalty to their political party? Or is it self-interest -- people voting for policies that will benefit themselves and the groups they belong to? This episode features psychologist Jason Weeden, arguing that self-interest is a much bigger determinant of voter behavior than most political scientists think it is. Jason and Julia talk about why researchers disagree over this question, and what "self-interest" even means.

Humans have an innate urge to reach for explanations of the world around us. For example, "What caused this tragedy?" or "Why are some people successful?" This episode features psychologist and philosopher Tania Lombrozo, discussing her research on what purpose explanation serves -- i.e., why it helps us more than our brains just running prediction algorithms. Tania and Julia also discuss whether simple explanations are more likely to be true, and why we're drawn to teleological explanations (e.g., "Why does the sun shine? So that plants can grow.")

We're used to conflating political parties (Republican and Democrat) with political ideologies (conservative and liberal), but the two were very distinct only a few decades ago. In this episode of Rationally Speaking, Julia talks with political scientist Hans Noel about why the Democrats became the party of liberalism and the Republicans the party of conservatism, whether voters are hypocrites in the way they apply their ostensible ideology, and whether politicians are motivated by ideals or just self-interest.

Nothing changed the course of human history as much as the industrial revolution. Yet its cause is a mystery: Why did it occur in the late 1700s, and not sooner (or later)? Why did it occur in Britain, a relatively small and geographically isolated country, and not somewhere much bigger like China, or elsewhere in Northern Europe like the Netherlands? This episode features economic historian Gregory Clark, author of A Farewell to Alms and one of the leading scholars of the industrial revolution. Greg and Julia explore different theories, as well as the epistemological challenges of answering this kind of causal question about history.