AI in human resources
M24
Integrate AI in HR without reproducing bias or breaching Law 25.
Online10–15 min
Training by function
Human resources
AI in HR touches the most sensitive ground: applications, evaluations, personal data. Here is the path that lets your HR teams benefit from it without reproducing bias or breaching Law 25.
Why this path
Pre-screen, yes. Judge a human alone, never.
A poorly framed tool can screen out candidates on discriminatory criteria, retain application data without consent or produce a decision no one can explain. HR literacy turns AI into a useful assistant while keeping the decision and the responsibility on the human side.
The module dedicated to your function
The common core for everyone
The baseline reflexes your whole team shares, whatever the job.
Understanding generative AI
M01
Demystify the probabilistic engine and distinguish it from predictive AI.
Online10–15 min
A probabilistic engine predicts the most plausible word without understanding meaning: brilliant, but sometimes wrong. Never feed it confidential data in a public tool.
RegisterHallucinations
M02
Identify fabricated information and how to verify it at the source.
Online10–15 min
A hallucination is fabricated information presented confidently. The risk is real on expert tasks (figures, citations): every output must be verified at the source.
RegisterUsing an assistant well
M03
Structure your prompts (Role + Context + Task + Format) and iterate.
Online10–15 min
Good results come from a structured prompt and an iterative approach. Providing examples of the desired output markedly improves quality.
RegisterConfidential data: the basic reflexes
M04
Sort your data and de-identify rigorously before every prompt.
Online10–15 min
Anything entered into a public AI can be retained and reused. Never client names, salaries or API keys; removing just the name is not enough.
RegisterApproved tools and "shadow AI"
M05
Recognize shadow AI and have tools approved by IT.
Online10–15 min
Shadow AI is the use of unapproved tools, often free and poorly protective. The reflex: check the IT allowlist and get the tool approved before using it.
RegisterYou remain responsible: the human role
M06
Apply "human-in-the-loop" and the "four eyes" method.
Online10–15 min
AI is a gifted junior assistant with no judgment: final responsibility stays human. Review and validate every deliverable as if you had written it yourself.
RegisterGo deeper for your context
The modules most relevant to the risks specific to your function.
Law 25 in plain terms for employees
M07
Apply purpose, minimization and informed consent day to day.
Online10–15 min
Minimize the information given to AI and respect the purpose of collection. Reusing data for a new objective requires new consent.
RegisterBias and fairness: origins and detection
M16
Understand where bias comes from and see through apparent objectivity.
Online10–15 min
Bias comes from training data, which reflects human prejudice. Reduce it through diverse oversight and testing across different scenarios.
RegisterHigh-impact decisions: mandatory human oversight
M22
Guarantee explainability, fairness and the right to human review.
Online10–15 min
A high-impact decision is never fully delegated to AI. The person concerned is entitled to an explanation of the criteria and to human review.
RegisterReady to equip your team?
Enroll your teams in our AI-literacy and governance training paths, from the common core to function-specific use cases.
Immediate access · 100% online · at your own pace