Using AI responsibly and effectively: Building capability, confidence, and ethical use of AI in training.

Duration: 4m20s

Artificial Intelligence, or AI, is changing the way people work, write and learn.

The question for trainers is not whether to use AI. Rather, the question is how to use it effectively.

Used properly, AI can save time, support learning and help trainers to work smarter.

However, when it's not used well, it can lead to errors, poor judgement and serious integrity issues.

Remember, AI is a tool. It can help with developing ideas, building structure, crafting summaries, as well as drafting wording for resources and assessment questions.

But it shouldn't replace trainer judgement, hands-on skill and evidence of learner competence.

The value of AI depends on how well the trainer uses it, checks it and understands its limitations.

I like to think of it as the assistant, rather than the manager. Which means it needs supervision and feedback to progress successfully.

One of the best ways trainers can use AI is in preparation. 

It can help you to draft session outlines, discussion questions, learning resources and a host of other materials that support training.

But don't just copy and paste AI responses without checking them. AI can be wrong (and often is), as many of the platforms are designed to please the user, so they can confidently give you the answers that you want. As such, oversight is necessary.

AI responses can also miss context. And produce content that really doesn't fit your site or learner group.

Therefore, use AI to create a starting point, then apply your own expertise.

For trainers in mining and automotive, AI works best when it supports real work, not generic content.

This means you still need real tools, real tasks, real risks and real decisions in the training.

Of course, AI can help to shape the session. But the training still needs to connect to the job.

If the learning feels too generic, learners will disengage fast.

Learners also need guidance.

If AI use is allowed, be clear about what's acceptable and what must be declared.

For example, AI may help a learner brainstorm ideas, improve wording or summarise notes. But it shouldn't replace their own thinking, practical skills, or evidence of competence.

Make the rules clear early, and that'll help build clarity and confidence while protecting the integrity of the training.

If learners use AI, checking becomes even more important.

Don't assess the final document alone. Ask questions. Check understanding. Observe the task. Get the learner to explain their choices in their own words.

This helps you to confirm whether the work reflects real understanding.

In the end, a strong assessment looks beyond polished wording. It looks for depth in application.

Responsible AI use also means talking about ethics.

Trainers and learners need to consider things like accuracy, privacy and bias.

Never put sensitive workplace information into public tools without approval, and don't trust AI output just because it sounds legit.

The best way to build confidence is to model good use.

Show learners how to write a better prompt. Remember "rubbish in, is rubbish out". So, show them how to test their output and explain how they can make improvements.

That's how you build capability, rather than dependence.

AI can be useful, but we do need to exercise care.

Use it to support planning, improve learning and enhance the overall training and assessment experience. But always check the output.

Furthermore, set clear boundaries and keep real skill, real judgement and real performance at the centre of your practice.

That's how trainers can use AI responsibly and effectively. It's about getting yourself into good habits that ultimately rub off on your learners. Good luck with the challenge.

END.