Podcast | Human-Centric Learning Experiences And Using AI In L&D

More people Googled AI content in February than any month EVER! And it’s starting to knock on L&D’s door…

​✍️ Can it be used to create learning experiences?

​✍️ Would it remove the human feeling from content?

​✍️ Does it offer a good way to test ideas at speed and scale?

​These are all valid questions! And Filip Lam helped us answer them in this episode of L&D Disrupt Live.

With a background in psychology and over a decade’s experience in sales enablement and L&D, Filip knows human-centric learning experiences inside out.

Watch the episode

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Listen to the episode

Running order

0:00 Intro to Filip Lam
3:46 Defining human-centric learning experiences
11:21 Build systems for humans
16:54 How can L&D teams use AI?
22:03 Can AI help test ideas and analyse data?
35:47 What AI means for humans in L&D.
45:38 Writing prompts for AI
52:28 Closing questions

Five Lessons on using AI in L&D and human-centric learning

Why do Google employ so many psychologists, and what can it teach L&D pros?

“It’s to design products and services that adapt to humans and not the other way around. To me, that summarises what human-centric design is all about.” – Filip Lam

When a guest is dropping gold like this in the first three minutes of an episode, you know it’s going to be a good’un.

1. Human-centered learning is about more than just information and content

“You have to consider the individual, their needs and interests, and maybe even their lived experiences. And this is, of course, difficult when you’re trying to do things at scale… we have to go beyond one-size and adapt things to the human.” – Filip Lam.

So, what are some pointers for L&D teams?

• Recognise that learning is a social process. People enjoy and benefit from interactions, collaboration, discussions, and feedback.
• Retention of reading is 10%, whereas with practice, it’s about 75%. You might read a lot of stuff on providing feedback, but the theory and the culture are two very different things. And so…
• Context matters! A great example of it might be that people are learning things, but they don’t need to apply that information for six months, so can we provide it at the right time?

2. Human-centric doesn’t mean making people happy…

“Just because you prefer something, it doesn’t mean you’re more effective in learning it.”

A great example is an employee engagement survey, some people might think of it as making sure all employees are happy all of the time. But the purpose is to create commitment and engagement at the company level.

“And if L&D’s job is to accelerate execution and performance, when you think about human-centric approaches, it’s about creating moments and programs that help us improve performance faster for people.

“And that will, in turn, make people happier, instead of thinking what do people want to learn and give them everything they want.” – Filip Lam.

3. If you don’t get the fundamentals right, AI will just scale your problems

“If your team is lacking the right skills, and you don’t have the right strategy, using AI will just exacerbate all of your flaws. So you can create more problems rather than solving problems.” – Filip Lam.

Let’s think about the things good L&D teams do.

Identifying problems to solve, delivering solutions that fix that gap and accelerate execution, and defining what the outcome should be. If we know these, we can use AI effectively.

Let’s take a survey, for example, if we know the above then we can generate questions faster, word them better, and create variations.

Essentially, we have to be able to define problems, assess gaps and implement solutions – all those things remain the same, you can just do them faster and more effectively.

4. If you are going to use AI, you need to write great prompts

“Whenever you’re using AI, you have to be very specific about what you want as the output. You can prompt the AI on which format… you need to give it as much context as possible, tell it the target group or audiences, give it a specific role – like CEO or facilitator.” – Filip Lam.

But what goes into writing a great prompt?

• Be specific about output: From format to focus areas or how many bullet points you want, be clear on the deliverable.
• Give it as much context as you can.
• Tell it what you don’t want it to do.
• Define its role: Do you want it to act as a particular role or from a different perspective?
• Consider the target audience.

If you’re not getting the desired output, AI listens very closely to verbs, so you can change those and see if you get a different outcome.

Or, you might need to break the complex things down to smaller steps into enable it to generate more specific responses or concrete examples.

5. Can AI really help small and single-person L&D teams?

“It almost democratises L&D teams between big ones from big corporations to small L&D teams because now they can add a different level of skill and speed that they couldn’t before.

“It comes back to how much you’re able to imagine and dream of solutions… let’s say you’re looking at compliance, and the quiz data or participation rate, you could ask the AI to analyse if you have potential gaps and problems in your content.” – Filip Lam

Whether it’s leveraging its ability to write content or analyse data to inform your strategy, these are normally things small teams wouldn’t have the capacity or capability to do.

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