Is cash the best way to help the poor? (Michael Faye)

Is cash the best way to help the poor? (Michael Faye)

The idea of giving poor people cash, no strings attached, is "very unappealing" for most donors, admits economist Michael Faye -- but it's still one of the best ways to help the poor. Michael and Julia discuss the philosophy behind his organization (GiveDirectly), the evidence we have so far about cash transfers as an anti-poverty intervention, and the various concerns people have about it: How long-lasting are the effects? Does it make recipients less likely to work? Does it cause inflation?

Humanity on the precipice (Toby Ord)

Humanity could thrive for millions of years -- unless our future is cut short by an existential catastrophe. Oxford philosopher Toby Ord explains the possible existential risks we face, including climate change, pandemics, and artificial intelligence. Toby and Julia discuss what led him to take existential risk more seriously, which risks he considers underrated vs. overrated, and how to estimate the probability of existential risk.

Dangerous biological research - is it worth it? (Kevin Esvelt)

Kevin Esvelt, a scientist at MIT, argues that research intended to prevent pandemics is actually putting us in a lot more danger. Also discussed: Kevin's own research on engineering wild animal species. Are the risks worth the benefits?

Why we're polarized (Ezra Klein)

Ezra Klein explains how Republican and Democrats in the US became so different from each other, ideologically and demographically, and why that trend + our institutions =  political gridlock. Questions covered include: Is polarization necessarily bad? Has the left polarized more than the right? And what should we make of polls that seem to show Republicans and Democrats used to agree on immigration policy?

The genetic lottery (Kathryn Paige Harden)

Kathryn Paige Harden, author of “The Genetic Lottery: Why DNA Matters for Social Equality” explains what scientists have learned about how our genes affect our educational success. Why is this research so controversial? And is it worth doing anyway?