The dominant framework for measuring AI's impact on jobs may be asking the wrong question entirely.

In this episode, Ben sits down with Isabella Loaiza, economist and researcher at MIT, to challenge some of the most widely accepted assumptions in the AI and work debate. From the concept of "exposure" to the narrative of an incoming white-collar bloodbath, Isabella makes the case we're missing a big part of the picture around AI.

At the center of the conversation is EPOCH, a framework Isabella developed with her coauthor Roberto to capture the human capabilities that AI is least equipped to replace: Empathy, Presence, Opinion, Creativity, and Hope.

Topics covered:

• Why the "white collar bloodbath" narrative gets AI wrong
• The difference between automation and augmentation
• Why "exposure" should probably be called "automation potential"
• The EPOCH framework around AI and its relation to humanity
• The burnout problem: why offloading routine tasks to AI may eliminate the cognitive rest that knowledge workers rely on to sustain performance
• Whether AI empathy is real empathy
• Dream jobs vs. meaningful jobs: why they're not always the same thing
• Why measuring task content across countries matters and what a global labor market taxonomy might actually need to capture

Find the paper by Isabella Loaiza and Roberto Rigobon about the EPOCH framework here

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