Fair hiring in the age of AI
Hiring systems decide who gets seen and who gets an offer. When they're badly designed, they keep making the same unfair decisions, and once AI is doing part of the screening they make those decisions faster and at a scale nobody checks.
This is my commitment to designing hiring that's fair on purpose, and what I ask of the companies I work with.
Where a candidate gets filtered before a person reads anything
Ranks and sorts applicants.
Decide who shows up at all.
Sort resumes against criteria someone set.
Tell candidates what it's like to work there.
Fairness in hiring used to be a promise a company published. Now it's a property of the hiring system, and you can test it.
Most of the decisions that shape a workforce now happen before a person reads anything. An ATS ranks applicants, a sourcing tool decides who shows up, a screening model sorts resumes and an AI answer tells candidates what it's like to work somewhere. Each one can widen the pool or quietly narrow it.
What I commit to
- Structured, skills-based evaluation in every hiring process I design, with criteria agreed before anyone reads a resume.
- Bias audits on the AI tools a client already uses, checked against real outcomes rather than vendor claims.
- People at the decision points. AI handles the repetitive work. It doesn't make the call on who gets rejected.
- Employer brand that tells every candidate the truth about the role and the company.
- Talking to the people the process usually leaves out, including candidates who dropped out and employees from underrepresented groups, before I recommend anything.
- The same standard for Proactive Talent, in who I partner with and how I treat the people who work with me.
What I ask of the companies I work with
- Measure who moves through each stage of hiring, not just who gets hired.
- Keep a named person accountable for every automated decision that affects a candidate.
- Tell candidates where AI is used in your process, and give them a way to reach a person.
- Fix what the audit finds, even when the fix slows a req down.
If a company isn't willing to look at those numbers, I'm probably not the right partner for it.
Where this shows up in the work
Recruiting Operations
Bias checks on screening and sourcing tools, AI governance legal can sign off on, and verification that protects candidates as well as the company.
Employer Brand
An EVP that tells the truth about the job, written so people who don't already see themselves at your company can.
Recruiter Enablement
Recruiters trained to check AI's work, run structured interviews and spot when a tool is narrowing the pool.
Want to know how fair your hiring system is today?
The Recruiting Operations Audit includes a review of every automated step that affects a candidate.