# A Silicon Valley Love Triangle: Hiring Algorithms, Pseudo-Science, and the Quest for Auditability

arXiv: https://arxiv.org/abs/2106.12403 · HTML: https://mlsanity.com/paper/2106.12403/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jun 2021.

## Built on by (most cited first, 16 of 16)

- [The Fallacy of AI Functionality](https://mlsanity.com/paper/2206.09511/) (2022)
- [Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning](https://mlsanity.com/paper/2202.05338/) (2022)
- [The Silicon Ceiling: Auditing GPT's Race and Gender Biases in Hiring](https://mlsanity.com/paper/2405.04412/) (2024)
- [An External Stability Audit Framework to Test the Validity of Personality Prediction in AI Hiring](https://mlsanity.com/paper/2201.09151/) (2022)
- [Fair Wasserstein Coresets](https://mlsanity.com/paper/2311.05436/) (2023)
- [On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach](https://mlsanity.com/paper/2211.01498/) (2022)
- [Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor](https://mlsanity.com/paper/2506.14652/) (2025)
- [Adversarial Scrutiny of Evidentiary Statistical Software](https://mlsanity.com/paper/2206.09305/) (2022)
- [FairWASP: Fast and Optimal Fair Wasserstein Pre-processing](https://mlsanity.com/paper/2311.00109/) (2023)
- [Algorithmic Monocultures in Hiring](https://mlsanity.com/paper/2605.27371/) (2026)
- [The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology](https://mlsanity.com/paper/2401.10877/) (2024)
- [Resume-ing Control: (Mis)Perceptions of Agency Around GenAI Use in Recruiting Workflows](https://mlsanity.com/paper/2604.26851/) (2026)
- [Don't "research fast and break things": On the ethics of Computational Social Science](https://mlsanity.com/paper/2206.06370/) (2022)
- [The Initial Screening Order Problem](https://mlsanity.com/paper/2307.15398/) (2023)
- [Unsafe at any AUC: Unlearned Lessons from Sociotechnical Disasters for Responsible AI](https://mlsanity.com/paper/2607.14353/) (2026)
- [A Chain Is Only as Strong as Its Weakest Link: A Scoping Review of System Integration Audits in AI](https://mlsanity.com/paper/2608.04921/) (2026)

## Abstract (arXiv)

In this paper, we suggest a systematic approach for developing socio-technical assessment for hiring ADS. We suggest using a matrix to expose underlying assumptions rooted in pseudoscientific essentialized understandings of human nature and capability, and to critically investigate emerging auditing standards and practices that fail to address these assumptions.