# Optiver's discriminatory recruitment AI
Australia, 2020-2021 | Severity: N2

## What Happened
The algorithmic trading firm Optiver used an automated, AI-driven recruitment and screening tool to evaluate and rank thousands of applicants for quantitative trading and software engineering roles. Investigations by labor advocates and regulators revealed that the screening algorithm systematically penalized female candidates and those from specific educational backgrounds. The algorithm used historical data of successful employees (who were overwhelmingly male and from a select few universities) as proxies for performance, leading to the systemic, automated rejection of diverse candidates before their resumes could be reviewed by human recruiters.

## How MEG 1 acted
The screening algorithm failed both the Dynamic Accuracy Index (DAI) and the Index of Safety and Responsibility (ISR) audits due to its systemic demographic bias and lack of scientific validity, violating the principles of non-discrimination and procedural fairness.

## MEG 2 Analysis - Legal Framework
* **Agent level:** N2 (management) - automated screening and scoring system used by a commercial organization to make critical employment and career access decisions.
* **Cause (6.1):**
  * **(a) system defect** - algorithmic bias and systemic gender discrimination built into the predictive recruitment model (design defect), attributable to the manufacturer.
  * **(b) autonomous decision error** - the system's decision to assign lower suitability scores to female candidates based on biased historical proxies.
* **Attachment of liability:** Optiver as the operator is fully liable for the discriminatory outcomes; the developer is liable for the model's design defects (6.1a) regarding fairness.

## Procedural Mechanism
* **6.2 (architectural human confirmation):** Candidate screening and rejection decisions must require architectural human confirmation. The AI must be technically blocked from autonomously rejecting candidates; a human recruiter must review the file and the justification before confirming any rejection.
* **7.1 (independent forensics):** The analyzed parameters, scoring weights, and the system's decision path must be securely logged in an independent ledger for labor and civil rights audits.
* **9.4 (least privilege):** The scoring system was granted significant influence over career access without independent validation, violating safe operational parameters.