4: Environmental impact

In the last email (subject: The wrong lever​), I made the claim that for L&D to stay relevant, we need to prioritise the design of the environment ahead of the capabilities of the individual.

Whilst skills matter, the greatest opportunities for performance improvement come from improving the environment in which those skills are applied.

Why?

Because when performance depends on people remembering, interpreting, improvising or compensating, it becomes less reliable.

And the best performance partners have always understood this. They don't just help people perform better - they make work easier. 

But unlike people, AI can’t compensate for ambiguity, which makes relying on heroic effort an increasingly fragile strategy.

From earlier email ​Learning & Development 2.0​:

“For AI to perform well, it needs clarity. Which means for anyone using AI to perform well, they must provide AI with that clarity. And unless that clarity has been defined ahead of time, they'll be forced to figure it out in the moment - leading to inconsistent results.”

Now, I want you to interrogate my claims with scepticism - am I overstating the importance of the environment? Surely skills still matter?

Of course. But if both skills and environment influence performance, wouldn’t it make sense to start by designing the conditions within which people apply those skills? Otherwise, we’re putting the cart before the horse.

And if so, does that challenge some of our assumptions about the role of L&D?

Well, it’s an objection I hear regularly - we’re proud of ‘helping people’. For many of us, it’s why we do this work. But is it possible that by focusing on people and their skills, we're unintentionally limiting what they can achieve?

To make the point, let’s use an example: ‘critical thinking’.

I've chosen this because I want to discuss a soft skill - something that traditionally, we might assume depends on the individual. 

And it's also topical. There’s lots of focus on the need for better judgement when it comes to evaluating AI outputs.

So, how would we improve someone’s ability to ‘think critically’?

Well, if we looked at this as a knowledge problem, the solution might be an awareness campaign, reminding people AI can hallucinate and deliver dodgy outputs. 

And whilst that’s a good start, knowing one should do something doesn’t mean one will do it (I know better than to eat cake, but when you’re halfway through hosting a four-year-old's birthday party and need a sugar hit before the next round of musical chairs, it’s tough to say no). 

If we looked at this as a skill problem, the solution might be to provide practice activities: “evaluate this AI output and we’ll tell you what you missed”.

On the face of it, not a bad idea. 

But dig a little deeper and we spot some problems…

Firstly, how is someone supposed to ‘think critically’ in relation to that specific AI output? What are they looking for? How do they know it’s acceptable? Against what criteria are they assessing it?

Secondly, even if they did know how to evaluate it, will they remember in six months' time? Or will they do it when it’s 5pm and they’re late to collect their toddler from nursery?

And what about Trevor who was wiped out with man flu and missed the workshop - how do we ensure he thinks as critically as those who attended?

So, whilst practise is important, I'd argue the first step isn't building the skill - it's defining what good critical thinking looks like in that context. And then baking that into the flow of work.

That might include:

• examples of good and bad outputs

• a short checklist that appears with the AI output: “before sharing, check against these five criteria”

• peer review before sharing sensitive work

Now, once this checklist has been designed, of course it makes sense for people to practise using it. Throw them some edge cases, force them to navigate tricky scenarios, build the muscle of using the checklist so using it becomes second nature.

See what we're doing here? Environment first, skills second.

What we're not doing is relying on people remembering how to 'think critically'.

And so, if this approach is true of critical thinking, could it be true of other skills too? Skills we’ve historically considered 'soft' and which therefore come down to individual capability?

If so, we have some thinking to do - because if performance improvement starts with the environment, what does that mean for those of us who've built our careers around 'learning'?

We'll tackle that next.
- Ant