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[2502.20063] Strategic Hiring under Algorithmic Monoculture
Summary
The paper explores strategic hiring in labor markets dominated by algorithmic evaluation, highlighting the inefficiencies of naive hiring strategies and proposing equilibrium strategies that enhance social welfare.
Why It Matters
As algorithmic hiring becomes prevalent, understanding its dynamics is crucial for firms aiming to optimize their recruitment processes. This research offers insights into how strategic differentiation can mitigate congestion in candidate selection, ultimately benefiting both employers and job seekers.
Key Takeaways
- Naive hiring strategies lead to congestion as firms target the same candidates.
- Equilibrium strategies can significantly improve social welfare for firms and applicants.
- The Price of Naive Selection increases with the number of firms, indicating greater inefficiency.
- Firms require access to congestion information to adopt optimal hiring strategies.
- A sequential best-response process can converge to a socially optimal equilibrium.
Computer Science > Computer Science and Game Theory arXiv:2502.20063 (cs) [Submitted on 27 Feb 2025 (v1), last revised 18 Feb 2026 (this version, v2)] Title:Strategic Hiring under Algorithmic Monoculture Authors:Jackie Baek, Hamsa Bastani, Shihan Chen View a PDF of the paper titled Strategic Hiring under Algorithmic Monoculture, by Jackie Baek and 2 other authors View PDF HTML (experimental) Abstract:We study the impact of strategic behavior in labor markets characterized by algorithmic monoculture, where firms compete for a shared pool of applicants using a common algorithmic evaluation. In this setting, "naive" hiring strategies lead to severe congestion, as firms collectively target the same high-scoring candidates. We model this competition as a game with capacity-constrained firms and fully characterize the set of Nash equilibria. We demonstrate that equilibrium strategies, which naturally diversify firms' interview targets, significantly outperform naive selection, increasing social welfare for both firms and applicants. Specifically, the Price of Naive Selection (welfare gain from strategy) grows linearly with the number of firms, while the Price of Anarchy (efficiency loss from decentralization) approaches 1, implying that the decentralized equilibrium is nearly socially optimal. Finally, we analyze convergence, and we show that a simple sequential best-response process converges to the desired equilibrium. However, we show that firms generally cannot infer the key...
