Module · Does the filter help you see people

The Recruiter's AI Check

AI can rank a thousand applications before your first coffee, and that is both the promise and the trap. A tool that filters people you will never meet decides careers on your behalf, and in most jurisdictions hiring is a high-risk use of AI for good reason. This module checks the five habits that keep you in the loop: healthy skepticism of the tool, a candidate experience worth having, awareness of the bias the model learned, human contact where it counts, and reasons for rejection you could defend.

Question 1 of 5 · You question the tool

Do you know how your screening tool ranks candidates, or do you trust the score?

A ranking you cannot explain is a decision you cannot defend. Vendors call it objective, but the model learned from someone's past hires, with all their patterns baked in. If you cannot say why it scored someone low, you are outsourcing judgment to a black box.

Question 2 of 5 · Candidates get a real experience

Does AI in your process treat candidates like people, or like inputs to a funnel?

The candidate remembers how it felt to apply. Auto-rejections with no signal, chatbots that loop, interviews with no human until round three: these cost you the people you most wanted, and they talk.

Question 3 of 5 · You watch for learned bias

Are you alert to the bias an AI tool can inherit and amplify at scale?

A model trained on your past hires learns your past preferences, including the ones you would never write down. The difference from a biased human is scale: it applies the same skew to every candidate, silently, all day.

Question 4 of 5 · A human makes the call

At the points that change a person's path, is a human deciding, not the model?

Some decisions are too consequential to leave to a ranking: who gets an interview, who gets rejected, who gets the offer. Automation can inform those, but a person should own them, and be able to say so.

Question 5 of 5 · Rejections have real reasons

For anyone the process rejects, could you give a reason you would stand behind?

The screen dropped them means nothing to the candidate and nothing to a regulator. If the only reason for a rejection is a score you cannot unpack, you have made a decision you cannot explain or defend.

For the statistics · one click each

Three questions for the public picture

These do not affect your score. They feed the anonymised, aggregated statistics; groups under 8 respondents are never shown.

How much of your candidate screening relies on AI tools?

None

Sourcing only

Ranking and filtering

Most of the funnel

End to end

Do you know how your screening tool actually ranks candidates?

No idea

Roughly

Fairly well

In detail

I use no such tool

Has anyone checked your AI hiring tools for biased outcomes?

Never

Informally

Once, at purchase

On an ongoing basis

I do not know

Your context

Used to calibrate the report. Company size and sector remain in the anonymized dataset; your email does not.

Company size Sector (optional)

Your corporate email required

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