AI Regulatory Intelligence โ€” by YRproject

factual analysis · traceable to primary sources

Explainer

Targeted job advertising with AI: high-risk and a discrimination risk

Adopted 2026-06-21 ยท ≈ 2 min read ยท Dirk Baaijen

AI that shows job ads to specific groups falls explicitly under Annex III of the AI Act as high-risk. The biggest risk is discrimination: an algorithm that shows a vacancy mostly to young men invisibly excludes others. The GDPR and the DSA set additional limits.

Short answer: Using AI to target job ads โ€” deciding who does and does not see a vacancy โ€” is named explicitly in Annex III, point 4 of the AI Act as high-risk. It is not an edge case. The reason is discrimination: an algorithm that shows a vacancy mostly to a certain age, gender or origin excludes others without anyone noticing. On top of that come the GDPR and the DSA.

Why this is high-risk

Recruitment begins before the application: with who sees the vacancy at all. Ad platforms optimise for "click likelihood", and that optimisation can lock onto demographic patterns โ€” the technical role lands mostly with men, the care role mostly with women. The result is a biased applicant pool you never see, because the excluded group never got to apply.

The discrimination risk

This touches equal-treatment law directly. Even without deliberately targeting a protected characteristic, platform optimisation can produce indirect discrimination. See AI and discrimination in recruitment: responsibility lies with the employer, even when the platform performs the targeting.

What the GDPR and DSA add

Targeting is profiling, and thus processing of personal data with a valid basis and transparency (GDPR). The Digital Services Act also bans ads based on special-category data and profiling-based ads to minors, and requires platforms to make ads recognisable. If you recruit through large platforms, these rules reach you via the advertising terms.

What to do

  • Treat job-ad targeting as high-risk โ€” with human oversight and monitoring for skewed outcomes.
  • Target broadly, not narrowly: avoid demographic narrowing and don't let the platform optimise unchecked.
  • Check the reach figures for unintended exclusion (age, gender, region).
  • Record the basis and the trade-offs โ€” you need them in a complaint.
  • Combine with your broader recruitment approach and CV screening; the whole funnel falls under the same regime.

The fairest selection starts with fair reach. An algorithm that decides who sees your vacancy helps decide who can be hired โ€” which is exactly why the law is strict about it.

Sources

  1. https://eur-lex.europa.eu/eli/reg/2024/1689/oj
    Regulation (EU) 2024/1689 (AI Act): Annex III, point 4 explicitly names the targeted placement of job advertisements as high-risk.
  2. https://eur-lex.europa.eu/eli/reg/2022/2065/oj
    Regulation (EU) 2022/2065 (DSA): advertising transparency and limits on profiling-based ads.

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Dirk Baaijen

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Compiled and maintained by YRproject โ€” programme and project direction at the intersection of digital transformation, AI and regulation. Every factual claim is traceable to its primary source. YRproject is led by Dirk Baaijen About & method โ†’

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