Lesson 205 · 3 min
Screening CVs fairly with AI
AI can help you compare CVs against clear criteria, but a person must make the decision, and you must watch for bias.
Sorting a hundred CVs is tiring, and tired people make unfair choices. AI can help by checking each CV against the criteria you set and noting the evidence for each one.
Write the criteria first, before you read any CV: the skills and experience the job truly needs. Ask the AI to score only against those and to quote the line in the CV that supports each score.
AI models can carry bias from their training data, for example favouring certain schools, names or styles of writing. Remove names, photos, ages and addresses before screening if you can, and never let the AI reject people on its own.
CVs are personal data. Use only tools your company has approved for it, tell candidates how their data is used where the law requires it, and delete what you no longer need.
Do it now
Write your criteria first
- 1. For a role you know, write 4 to 6 criteria that really matter.
- 2. Use the prompt below on a sample CV with personal details removed.
- 3. Check each score against the quoted evidence and decide for yourself.
Assess this CV only against these criteria: [LIST]. For each criterion, give a score of 0 to 2 and quote the line from the CV that supports it. If there is no evidence, say so. Do not consider anything outside these criteria, and do not make a hiring recommendation. [PASTE CV WITHOUT NAME, PHOTO, AGE OR ADDRESS]
Quick check
Keep going
Next →Better interview questionsWords from this lesson
- Bias
- When an AI treats some people or ideas unfairly because of skewed patterns in the data it learned from.
- Human in the loop
- Designing a process so a person reviews or approves the AI's work before it has real consequences.
- Data privacy
- Keeping personal or confidential information under control, including deciding what you type into AI tools and where it is stored.
- Automation bias
- Our habit of trusting a machine's answer too readily, even when our own judgement or other evidence says otherwise.