Ideas on fairer hiring
Product updates, perspective, and practical guides on verified, anonymous-first hiring.
What an AI bias audit actually measures
A bias audit is an outcome analysis, not a code review. What impact ratios are, what an audit cannot tell you, and how to read a summary you have been handed.
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Seven areas we write about in depth — process design, fairness, regulation, assessment integrity, and guides for candidates.
Practical process design — job descriptions, structured interviews, assessment validity, feedback, and the metrics actually worth tracking.
- What skills-based hiring actually is (and what it is not)
- Does your assessment predict anything? Validity for non-specialists
- Why candidates get ghosted, and how to actually stop
What the evidence supports about bias in hiring, and the structural changes that measurably reduce it rather than merely signalling intent.
- Blind hiring: what the evidence supports, and what it does not
- The four-fifths rule: how to test your hiring for adverse impact
- The biases that actually change hiring outcomes
The EU AI Act, NYC Local Law 144, GDPR and Emiratization, translated into what a hiring team has to actually do.
- The EU AI Act and hiring: what recruitment teams are responsible for
- What an AI bias audit actually measures
- GDPR and candidate data: what recruiting teams get wrong
AI assistance, proxy interviews and identity fraud — how to detect what matters without surveilling candidates in their homes.
- Candidates are using AI in your assessments. Now what?
- Fake candidates: proxy interviews, stolen identities and deepfakes
- Why webcam proctoring is the wrong fix for assessment integrity
For candidates: how skills-first hiring works, what really happens to your résumé, and how to compete without a degree.
- How to get hired without a degree
- Does an ATS really reject your résumé? What actually happens
- How to prepare for an AI interview
Longer arguments about why hiring works the way it does, and why the résumé was the wrong artefact to build it on.
Browse PerspectiveWhat we are building on CalHire, and the reasoning behind the decisions.
Browse ProductLatest posts
Candidates are using AI in your assessments. Now what?
AI-text detectors are unreliable and disproportionately flag non-native speakers. What to do instead: assessment design, signals and human review.
July 30, 2026
Does your assessment predict anything? Validity for non-specialists
An assessment that feels rigorous can predict nothing. What validity and reliability mean, how to check yours, and the four ways hiring tests quietly break.
July 30, 2026
Does an ATS really reject your résumé? What actually happens
The "75% of résumés are rejected by robots" claim has no verifiable source. What an ATS actually does, where filtering happens, and what to do.
July 30, 2026
Blind hiring: what the evidence supports, and what it does not
Blind hiring has one of the cleanest natural experiments in labour economics behind it, and real limits. What it fixes, and what it cannot.
July 30, 2026
Why candidates get ghosted, and how to actually stop
Ghosting is almost never malice. It is what happens when closing the loop is optional, unowned and manual. The four structural causes, and the fix for each.
July 30, 2026
Dropping the degree requirement: what has to replace it
Removing a degree requirement without replacing the signal makes hiring more subjective, not less. What the degree was doing, and what to measure instead.
July 30, 2026
The EU AI Act and hiring: what recruitment teams are responsible for
AI used to recruit or evaluate candidates is high-risk under the EU AI Act. What that means for employers, what providers owe you, and what to ask vendors.
July 30, 2026
Fake candidates: proxy interviews, stolen identities and deepfakes
Remote hiring created a real identity-fraud problem: proxy interviewers, borrowed identities and deepfaked video. How the fraud works and where to verify.
July 30, 2026
The four-fifths rule: how to test your hiring for adverse impact
The four-fifths rule is a rule of thumb, not a legal safe harbour. How to calculate it, where it misleads, and how to find the stage causing the disparity.
July 30, 2026
GDPR and candidate data: what recruiting teams get wrong
Consent is usually the wrong lawful basis for recruitment. What to rely on instead, how long to keep applications, and the rules on automated decisions.
July 30, 2026
How to get hired without a degree
A practical guide to competing on demonstrated skill: what to build, how to describe it, which employers to target, and how to handle the question directly.
July 30, 2026