Responsible AI in practice: Recognising bias and making fair decisions
A ready-made course you customise for your organisation, with a live session deck and two surveys. You only add the 7 details that are specific to your organisation.
- Length
- 30 min
- Lessons
- 6 lessons
- Frequency
- Annually
- Last reviewed
- 21 Oct 2026
An assistant makes a "typical team" image using only one kind of person
Try it: this is one of 15 interactive activities in the course.
What's included
Three pieces that work together
Copy once, get everything. Learners prepare on their own, you answer questions live, and the surveys tell you what stuck.
Self-paced course
Short lessons with real workplace scenarios, not walls of text.
- 6 lessons, about 30 minutes
- Scenario, process, timeline, flashcards and quizzes
- 10-question final check, 80% to pass
Live session deck
An AhaSlides presentation to run after the course, in person or online.
- 10 slides
- Poll, quiz, word cloud, open-ended slides
- A closing slide for your contacts
Two surveys
Find out what landed, and whether people use it on the job.
- Post-course feedback, about 2 minutes
- 30-day check-in
- Anonymous by default
- Results feed your next refresher
Learning objectives
At the end of this course, learners can
Each objective and the lesson that covers it.
| ID | Objective | Source | Where it's covered |
|---|---|---|---|
| TO 119.0 | Achieve ≥ 80% on the final assessment | - | Whole course |
| SO 119.1 | Define bias, fairness, transparency and accountability in AI with workplace examples | OECD AI Principles (updated May 2024); UNESCO Recommendation on the Ethics of AI (Nov 2021) | Whole course |
| SO 119.2 | Spot signs of biased AI outputs in text, images and scores | NIST AI RMF 1.0 | Whole course |
| SO 119.3 | Apply a short responsible-use check before acting on AI output about people | Best practice | Whole course |
| SO 119.4 | Raise concerns about unfair AI outcomes through the right channel + your info | Organisation's speak-up procedure | Whole course |
Your part: what a template can't do for you
- Your workplace details: fill in the 7 highlighted fields so the course describes your own policies, contacts and locations.
- Records: record completion in your own LMS or record system.
Course outline
6 lessons, about 30 minutes
Minutes per lesson are an estimate, shared out by page count.
1Why AI can grade unfairly
3 pages
6 min
Why AI can grade unfairly
3 pages
2Ethics principles and types of bias
3 pages
6 min
Ethics principles and types of bias
3 pages
3A four-question responsible-use check
3 pages
5 min
A four-question responsible-use check
3 pages
4Grey areas: images, translation and scores
3 pages
5 min
Grey areas: images, translation and scores
3 pages
5Raising concerns through the right channel
2 pages
4 min
Raising concerns through the right channel
2 pages
6Final assessment on responsible AI use
Assessment
4 min
Final assessment on responsible AI use
Assessment
Live deck and surveys
10 slides to run live, two surveys to close the loop
Pink slides are interactive. Both surveys are anonymous; pink questions are written for this course.
Post-course feedback: 11 questions, about 2 min
- Overall rating 5 stars
- Relevant, realistic, right length, helpful activities agree/disagree grid
- What was most useful? multi-select
- Confidence before this course, and now 1-5 scale
- Have you noticed bias in an AI output? multiple choice
- How confident are you explaining AI bias to a colleague? 1-5 scale
- Does your work feed decisions about people? multiple choice
- I would feel comfortable raising a concern that an AI result seems unfair. 1-5 scale
- One thing we should change or add open text
- Would you recommend this course? NPS
30-day check-in
- Have you used what you learned since the course? multiple choice
- How confident are you today? Compare with day 1 1-5 scale
- Do you know where to find the responsible-use check and the concern channel? yes / no / not sure
- A moment where the training helped, or where you weren't sure open text
- Which topics should the next refresher focus on? ranking
Results show whether people use the training on the job, not just whether they finished it.
Make it yours
7 fields to fill in, and you're ready
Everything else is done. These are the details only your organisation knows; each one is highlighted inside the course.
- AI concern channel
{{AI_CONCERN_CHANNEL}} - AI tool owner contact
{{AI_TOOL_OWNER_CONTACT}} - AI policy link
{{AI_POLICY_LINK}} - HR contact
{{HR_CONTACT}} - LMS or record system
{{LMS_OR_RECORD_SYSTEM}} - Survey 1 URL
{{SURVEY_1_URL}}
Show all 7 fields
- Survey 2 URL
{{SURVEY_2_URL}}
FAQ
Common questions
Can I run responsible AI in practice: Recognising bias and making fair decisions training online?
Yes. The course is self-paced and online, and the live deck lets you add a live session in the room or online.
How often is this training needed?
Annually; when an AI tool starts to inform decisions about people; after a fairness concern is raised.
Who needs this training?
All employees; especially people whose work feeds decisions about people (HR, recruiting, support, operations); run by L&D with HR, data or legal.
What records should I keep?
Record completion in your own LMS or record system, so you can show who finished the course and when.
Can I edit the content?
Yes, everything. Change the wording, swap scenarios for ones from your workplace, add your logo, or remove parts that don't apply.
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Ready to run it?
Open the live deck to see how the session runs alongside the course and both surveys.