EU AI Act
Classifies candidate-evaluation AI as high-risk: human oversight, transparency, data governance, logging and technical documentation. Read our deep dive.
Compliance
Hiring AI is regulated now. We built for that.
The EU AI Act, New York City's Local Law 144, and data-protection law all shape how automated hiring tools may be used. This is the map of what applies and how hire.center is designed to help you stay on the right side of it.
The landscape
Three regimes that matter for hiring AI
Local Law 144
Automated employment decision tools require an annual independent bias audit, published results, and candidate notice. Enforcement is tightening.
Data protection (GDPR)
Candidate data is personal data: lawful basis, transparency, data-subject rights, retention limits, and safeguards around automated decision-making.
NYC Local Law 144 & bias audits
New York City's Local Law 144 governs "automated employment decision tools" (AEDTs). If an employer uses one to substantially assist a hiring or promotion decision, the law requires an independent bias audit within the prior year, publication of a summary of results, and advance notice to candidates.
hire.center's design supports this in two ways. First, our human-in-the-loop model means the tool assists — it does not make — the decision. Second, our construct-focused, demographic-blind scoring and retained evidence give an auditor the material they need to assess outcomes. Bias auditing is ultimately the employer's obligation; we build to make it feasible. See fairness & validity.
GDPR & candidate data
A candidate's simulation transcript and scores are personal data. We handle them accordingly: EU-hosted infrastructure, a clear lawful-basis and consent flow, defined retention, candidate rights (access, correction, deletion), and no use of your candidates' data to train third-party models. Details on security & privacy.
Beyond the EU and NYC
Illinois' AI Video Interview Act, Colorado's AI Act, and a growing set of U.S. state and international rules point the same direction: transparency to candidates, human accountability, and evidence that a tool measures the job rather than the person's background. hire.center's principles — advisory output, public-taxonomy grounding, quote-backed evidence — are meant to travel across these regimes.
Our commitments
What we hold ourselves to
Advisory by design
The system never makes the decision. A human always does.
Transparent to candidates
People are told they're taking an AI-assisted assessment and consent before starting.
Auditable
Blueprints, transcripts and quote-backed evidence are retained so decisions can be reviewed.
Construct-focused
We score demonstrated behavior against role-relevant constructs — not names, photos or demographics.
Honest about limits
We publish our method and don't overclaim validity we haven't earned.
Data-minimal
We collect what the assessment needs and no more, and we don't sell or broker candidate data.
Deploy hiring AI you can defend
Human-in-the-loop, evidence-first, and built for the regulated era.