In a 70,000‑applicant field experiment in the Philippines, an LLM voice recruiter made 12% more offers and 18% more starts than humans, achieved 17% higher one‑month retention, and showed less gender discrimination with equal candidate satisfaction. This indicates AI can improve match quality at scale.
— If AI reduces bias and raises retention in hiring, HR policy, anti‑discrimination enforcement, and labor‑market dynamics will shift toward algorithmic selection as a presumed best practice.
Tyler Cowen
2025.10.03
55% relevant
Both pieces examine AI’s growing role in hiring pipelines; the new paper warns that LLM screeners systematically favor resumes written by the same LLM, adding a fairness risk that complements prior evidence that AI recruiters can outperform humans.
Tyler Cowen
2025.09.10
95% relevant
The post summarizes a 70,000‑applicant natural field experiment where AI voice agents led to 12% more offers, 18% more starts, and 17% higher 30‑day retention with similar satisfaction—mirroring the core findings of the cited idea (likely the same paper).
Kelsey Piper
2025.08.26
60% relevant
By diagnosing overloaded human‑run pipelines as approaching a random lottery, the piece indirectly motivates algorithmic or redesigned selection; our prior shows LLM recruiters improved match quality, a concrete counter to the paper‑sift chaos described here.
Alexander Kruel
2025.08.20
100% relevant
SSRN study: 'AI in HR' experiment with 70,000 applicants showing higher offers, starts, retention, and lower gender discrimination.