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Greenhouse

Greenhouse

Published 3 weeks, 4 days ago
Description

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Daniel Chait, co-founder and CEO of Greenhouse, joins us to explain why AI has trapped hiring in a “doom loop” where, for the first time he can remember, “neither side is really happy.”

He co-founded Greenhouse in 2012 and has built it into one of the world’s leading hiring platforms, used by more than 7,500 companies with a team of over 700. His Dream Job feature lets job seekers flag one application a month as their top choice, and he says those candidates now convert from application to hire at around five times the rate of everyone else.

Daniel also shares why 1 to 1.5% of applicants fail an ID check, how North Korean operatives use deepfakes to get through interview rounds, and why he believes starting with an AI interview can remove bias from the most biased stage of hiring.

In our in-depth episode, we discuss:

* How auto-apply tools and AI résumé filters created the hiring “doom loop,” and why job seekers and employers no longer trust each other

* The three-layer “Swiss cheese” model Greenhouse uses to catch fake candidates, and why North Korean infiltrators are so hard to spot once they’re hired

* Why an AI interview at the first stage can take racial bias out of résumé screening, and how it cuts around six days from the process

* Why Greenhouse’s value has shifted from workflow to data and context, and whether it will come out of this moment as Blockbuster or Netflix

* How Daniel decides which bets to place, why “we can do anything, we just can’t do everything,” and what it would mean to hire AI agents through Greenhouse

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Timestamps

[00:00] Meet Daniel Chait[02:16] The state of hiring right now[04:03] Why employers get 1,000 applications in a day[05:31] The AI doom loop explained[10:31] Why AI résumé filters fail[11:35] The “Jared problem”: how AI amplifies bias[13:32] North Korean spies and fake candidates[16:03] 1 in 100 applicants fail ID checks[16:32] The Swiss cheese model of hiring security[20:34] How deepfake hiring rings get caught[

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