Is There a Future for Machine Learning?

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We're in a turning point, like a real fulcrum moment as a kind of a global society. And it really does depend on what we're optimizing for. I think this ends up meaning that we change a lot of things. There's a million new kinds of businesses to make and a million unit kinds of nonprofits. Like absolutely everything can be rearranged from the point of view of what's meaningful.

In episode 63 of The Gradient Podcast, Daniel Bashir speaks to Joe Edelman.

Joe developed the meaning-based organizational metrics at Couchsurfing.com, then co-founded the Center for Humane Technology with Tristan Harris, and coined the term “Time Well Spent” for a family of metrics adopted by teams at Facebook, Google, and Apple. Since then, he's worked on the philosophical underpinnings for new business metrics, design methods, and political movements. The central idea is to make people's sources of meaning explicit, so that how meaningful or meaningless things are can be rigorously accounted for. His previous career was in HCI and programming language design.

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Outline:

* (00:00) Intro (yes Daniel is trying a new intro format)

* (01:30) Joe’s origin story

* (07:15) Revealed preferences and personal meaning, recommender systems

* (12:30) Is using revealed preferences necessary?

* (17:00) What are values and how do you detect them?

* (24:00) Figuring out what’s meaningful to us

* (28:45) The decline of spaces and togetherness

* (35:00) Individualism and economic/political theory, tensions between collectivism/individualism

* (41:00) What it looks like to build spaces, Habitat