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Good practice Imported

France Travail's 'Ciblage du Contrôle' — an AI Tool Sorting Job Seekers into 'Suspect' and 'Non-Suspect' for Control Priority

France · Paris · See the France profile · See the Paris profile

Evidence: Descriptive / self-reported Top 88% 33/100 · Ask Evidence Copilot about this practice

France Travail built an AI tool, trained on 60,000 cases across 26 variables, to classify job seekers as 'suspect' or 'non-suspect' for control priority, as controls scale toward 1.5 million by 2027. It has refused to release the source code, drawing opacity criticism.

60,000 cases
Past control cases used to train the model (as of 2025-2026)
26 variables
Variables scored per job-seeker file (as of 2025-2026)
roughly 40 %
Share of controls now algorithmically targeted (2025)
roughly 500,000 controls
Algorithmically-targeted controls (2025)
200,000 controls
Total controls conducted (2017)
1.5 million controls
Stated national target for total controls (by 2027)

Details

Maturity
Scaling
Promoter
France Travail
Period
2024–2026
Region (NUTS)
FR10
Keywords
employment services, welfare compliance, benefit fraud control, labour market

Context

France's national employment agency, France Travail (formerly Pole emploi), developed an algorithmic profiling tool named 'Ciblage du Controle de la Recherche d'Emploi' (Job-Search Control Targeting) to help select which job seekers' files receive an in-depth compliance review.

Objectives

Prioritise job-seeker files for human compliance review by sorting them into 'suspect' or 'non-suspect' categories, as part of a broader overhaul of the control process ('CRE renove').

Activities

The tool uses a decision-tree model trained on roughly 60,000 past control cases, scoring each job seeker's file on 26 variables, including declared job-search activity, whether a CV is visible online, targeted occupations, education level, registration tenure and prior non-compliance. It was piloted from July 2024 in eight regions, generalised nationwide by June 2025, and presented to France Travail's internal AI ethics committee on 10 December 2025.

Results

Algorithmically-targeted controls now account for roughly 40% of all controls, about 500,000 of the total in 2025, against a national policy backdrop of controls rising from 200,000 in 2017 toward a stated target of 1.5 million by 2027.

Conclusions

La Quadrature du Net reports that France Travail has refused to disclose the tool's source code, which the organisation says makes independent bias auditing impossible; France Travail's own internal documentation reportedly acknowledged a risk that the model could initially overrepresent job seekers receiving the lowest benefit amounts. This is included as a cautionary case: the operational scale is well documented, but there is no independent, published accuracy or fairness evaluation of the algorithm.

Implementation

Indicative cost
Medium (€50k–€500k) — No cost figures are disclosed in the public record.
Time to results
Medium (1–3 years) — Piloted from July 2024 in eight regions, generalised nationwide by June 2025, and presented to the internal AI ethics committee on 10 December 2025 as part of the broader 'CRE renove' overhaul.
Staffing & skills
France Travail internal AI ethics committee, France Travail control administration (CRE renove programme)

Conditions for success

  • Regional pilot (eight regions, from July 2024) before nationwide generalisation (by June 2025)

Common failure modes

  • France Travail has refused to release the tool's source code, which La Quadrature du Net says makes independent bias auditing impossible
  • France Travail's own internal documentation reportedly acknowledged a risk that the model could initially overrepresent job seekers receiving the lowest benefit amounts
  • No independent, published accuracy or fairness evaluation of the algorithm exists

Commonly funded by

National / regional programmes

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Data sources

Where this practice's information was retrieved from, and when.

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