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Today’s Thoughts ☠️

Hey there 👋,

The AI train shows no signs of slowing down.

Yet, the same tired discussions seem to dominate the conversation.

So, I want to shift the conversation.

Yes, this will still cover AI, BUT… no more tools, gimmicky use cases, or arguing over who has the better “AI-powered” product.

Instead, I want to go deeper – I want to get meaningful.

Today, we investigate what AI is doing to your skills.

(P.S. This is an evolving thought, so I’d love to hear your take and any interesting things you’ve read/seen/experienced on this topic too).

Get your tea or beverage of choice ready, 🍵.

We've got lots to discuss!

👀 In today’s chat:

• The impact of AI use on your skills
  

• AI’s potential to boost your thinking about ‘thinking’

• 3 actions you can take to protect your human skills

THE BIG THOUGHT
The Big Question: How is AI Impacting Your Skills?

The world has tons of reports/research on performance with Gen AI tools.

It has even more industry use cases. We know that, when used intelligently, these tools can enhance performance (see this, this, and this). Plus, it’s clear that we see the biggest short-term ROI in the boring and basic tasks.

I know there’s trouble when industry pros have lost their compass of focus.

Sadly, the question I’m most asked is “How can I use/integrate AI into our L&D workflow?” 

That’s the wrong question, friend.

You should ask, “How can we define the problems we need to solve for performance?”

This mistake happens when you drink the social media Kool-Aid.

I’ve found in L&D (and, to be fair, many industries) we get distracted so often by the ‘shiny thing’ that we continually miss the point.

Although I like the power, potential, and continued promise of AI tools, I’m troubled by the unexpected consequences of the manic pursuit of ‘AI at all costs.’

Especially, AI’s impact on skills.

I sense that we already over-rely on certain tools, and in doing so, we both create illusions of capabilities and fail to invest in moments of intentional learning.

Granted, a lot of this comes down to the intent and ability of human users.

But with all-time high levels of use across millions of Gen AI tools, and all-time low levels of AI literacy, we could be heading for a skills car crash of our own design.

Let’s unpack that.

📌 TL;DR (too long; didn’t read)

• Smart Gen AI use can expand skill capabilities for a limited time

• We aren’t improving skills in most cases, mastery requires more than AI alone

• The majority of people will over-rely on AI tools and become ‘de-skilled’

• AI tools can help us improve critical thinking processes

• We must be more intentional in how we approach skill-building in an age of ‘do this task for me’

The Controversial Idea: Skills will be destroyed if we let AI do everything

So many people are scared that AI will take their job.

They think they’ll lose because AI tools can do the tasks better.

It’s easy to think, “That will never happen to me.” 

Maybe it won’t.

But I’d ask you to consider your use of AI tools today. My assumption is that most people use them in a ‘do this thing for me’ approach, rather than a “show me how to do this.”

Here exists a problem we aren’t paying enough attention to.

An AI-first approach will damage the capabilities and potential of skills (if you allow it).

Somewhat an observation for now, but a dark reality I’d like to avoid.

My thinking behind this comes both from real-world experience with consulting clients on Gen AI skills programs, and what I’ve seen in more advanced research this year.

An excellent piece of research from Boston Consulting Group has been one of my favourites on this topic. It unpacks, with an experiment involving 480 of their consultants, that Gen AI can increase productivity and expand capabilities.

That’s the headline, of course.

AI’s impact on skills: What the data says

The problem is that most don’t read beyond the headline.

Hence why we have so many cult-like statements about Gen AI’s endless power. It is powerful, in the right hands. But any power comes at a cost.

For those willing to go deeper, we find both a bundle of exciting opportunities and critical challenges.

Here’s some we haven’t discussed ↓

1/ Gen AI grants short-term superpowers

No surprise here, I think.

Gen AI tools grant easy access to skills we don’t possess. They can amplify the level of our current skills too. The BCG team coins this as an ‘exoskeleton’ effect.

Explained in their own words:

“We should consider generative AI as an exoskeleton: a tool that empowers workers to perform better and do more than either the human or Gen AI can on their own.”

Being a nerd, I compare this to something like Iron Man.

For those not familiar with the never-ending Marvel films, Tony Stark is a character who has no superpowers (but is a highly intelligent human). To play in the realm of superheroes, he creates his own suit of armour that gives him access to incredible capabilities he doesn’t have as a human.

The caveat is that he needs the suit to do those things.

BCG found the same in this research.

We could call this a somewhat false confidence dilemma.

This presents a few challenges to navigate:

• How do we combat the illusion of expertise?

• What happens when you don’t have access to AI?

• How do we stop addiction to the ‘easy option’?

Spoiler: I don’t have all the answers.

However, this temporary boost in abilities often leads to another problem – the illusion of expertise.

2/ We have to fight the illusion of expertise

This is a big challenge for us.

Getting people to look beyond AI’s illusion of expertise.

You know what I’m talking about.

Now everyone has access to creation tools, they all think they’re learning designers who can create their own amazing products. We both know how that’s going to turn out.

As an example in my work, I can build a decent website with AI, which does the heavy coding for me. But I can’t do it without it, not unless I learn how to do it.

Yes, I built x, but I’m not a software engineer.

There’s a big difference, and sadly, I see people falling into this trap already.

Now, with all this new tech, I don’t need to know the ‘why’ or ‘how’ behind something being built by AI.

But what does this mean for my skills?

A big part of skill acquisition focuses on the ‘why’ and ‘what’, in my opinion. I don’t need to know every little detail, but it helps to have a basic understanding.

I see a few unintended consequences if we don’t clearly define what is a ‘short-term expansion enabled by tech’ and what is ‘true skill acquisition’:

• We over-rely on AI tools, and this over-reliance erodes critical thinking skills, a key element in real-world problem-solving

• We lose context, a sense of understanding

• Our human reasoning skills will erode in the face of “But AI can tell me”

Each of us will fall into different groups based on our motivations.

I’m not saying we’re all collectively going to become skill-less zombies addicted to a digital crack of Gen AI tools, but it will be a reality for some.

What happens to human skills if we over-rely on AI?

This is a real grey area for me.

I’ve seen countless examples where too much AI support leads to less flexing of human skills (most notably common sense), and I’ve seen examples where human skills have improved.

In my own practice, my critical thinking skills have improved with weekly AI use these last two years. It’s what I class as an unexpected but welcome benefit.

This doesn’t happen for all, though.

It depends on the person, of course.

BCG’s findings seem to affirm my thoughts that the default will be to over-rely. I mean, why wouldn’t you? This is why any AI skills program you’re building must focus on behaviours and mindset, not just ‘using a tool.’

You can only make smart decisions if you know when, why, and how to work with AI.

But, we can learn with AI too

I (probably like some of you) have beef with traditional testing in educational systems.

It’s a memory game, rather than “Do you know how to think about and break down x problem to find the right answer?” Annoying! We celebrate memory, not thinking (bizarre world).

My beef aside, research shows partnering intelligently with AI could change this.

This article between The Atlantic and Google, which focuses on “How AI is playing a central role in reshaping how we learn through Metacognition”, gives me hope.

The TL;DR (too long; didn’t read) of the article is that using AI tools can enhance metacognition, aka thinking about thinking, at a deeper level.

The idea is, as Ben Kornell, managing partner of the Common Sense Growth Fund, puts it, “In a world where AI can generate content at the push of a button, the real value lies in understanding how to direct that process, how to critically evaluate the output, and how to refine one’s own thinking based on those interactions.”

In other words, AI could shift us to prize ‘thinking’ over ‘building alone.’

And that’s going to be an important thing in a land of ‘do it for me.’

To truly do so, you must know

Google’s experiments included two learning-focused examples.

In the first example, pharmacy students interacted with an AI-powered simulation of a distressed patient demanding answers about their medication.

• The simulation is designed to help students hone communication skills for challenging patient interactions.

• The key is not the simulation itself, but the metacognitive reflection that follows.

• Students are encouraged to analyse their approach: what worked, what could have been done differently, and how their communication style affected the patient's response.

The second example asks students to create their own chatbot.

Strangely, I used the same exercise in my recent “AI For Business Bootcamp” with 12 students.

Obviously, great minds think alike 😉.

It’s never been easier for the everyday human to create AI-powered tools with no-code platforms.

Yet, you and I both know, that easy doesn’t mean simple. I’m sure you’ve seen the mountain of dumb headlines with someone saying we don’t need marketers/sales/learning designers because we can do it all in ‘x’ tool.

Ha ha ha ha is what I say to them.

Clicking a button that says ‘create’ with one sentence doesn’t mean anything.

To demonstrate this to my students, we spent 3 hours in an “AI Assistant Hackathon.” This involved the design, build, and delivery of a working assistant.

What they didn’t know is I wasn’t expecting them to build a product that worked.

Not well, anyway.

I spent the first 20 minutes explaining that creating a ‘good’ assistant has nothing to do with what tool you build it in and everything to do with how you design it.

Social media will try to convince you that all it takes is 10 minutes to build a chatbot.

While that’s true from a tech perspective, the product, and its performance, will suck.

Just because you can, doesn’t mean you will (not without effort!)

When the students completed the hackathon, one thing became clear.

It’s not as simple or easy to create a high-quality product, and you’re certainly not going to do it in minutes.

But, like I said, the activity’s goal was not to actually build an assistant, but rather, to understand how to think deeply about ‘what it takes’ to build a meaningful product.

I’m talking about:

• Understanding the problem you’re solving

• Why it matters to the user

• Why the solution needs to be AI-powered

• How the product will work (this covers the user experience and interface)

Most students didn’t complete the assistant/chatbot build, and that’s perfect.

It’s perfect because they learned, through real practice, that it takes time and a lot of deep thinking to build a meaningful product.

AI is only as good as the human using it

The section title says it all.

Perhaps the greatest ‘mistake’ made in all this AI excitement is forgetting the key ingredient for real success.

And that’s you and me, friend.

Like any tool, it only works in the hands of a competent and informed user.

I learned this fairly young when a power drill was thrust into my hands for a DIY mission. Always read the instructions, folks (another story for another time).

Anyway, all my research and real-life experience with building AI skills has shown me one clear lesson.

You need human skills to unlock AI’s capabilities.

You won’t go far without a strong sense (and clarity) of thinking, and the analytical judgment to review outputs.

Going back to the BCG report, a few things to note that support this:

1/ Companies are confusing ‘augmenting with skill building’

As we touched on earlier, AI gives you temporary superpowers.

Together (you and AI) you can do wonderful things. Divided, not so much (unless you have the prerequisite knowledge to do the task).

We can already see both companies and workers confusing their abilities to (actually) perform a task.

AI gives both a false sense of skills, and terror at the lack of them.

2/ Most people can’t evaluate outputs

Again, any of us can code with AI.

But that doesn’t mean we know what’s going on or how to check if it’s correct.

This is the trap anyone can fall into. Knowing how to validate AI outputs is critical. We need to pay more attention to this. You know, thinking about thinking, and all that.

3/ Without context, you’re doomed

Content without context is worthless.

That’s a general rule. Exceptions apply at times. Nonetheless, you need the context of when and when not to use AI tools to get results.

As we know, it’s not a silver bullet.

The solution to this is getting a better understanding of Gen AI fundamentals.

Another BCG report, in collaboration with Harvard, discovered that success in work tasks with AI came down to knowing when is the right time to call on those superpowers.

What you can do: Before tools, build mindsets and behaviours

Most companies are surprised when I show them this image ↓

Can you guess why? If not, I’ll put you out of your misery!

They expect the only output of ‘Gen AI training’ to be about tools.

This is where the problems start. If we consider Gen AI as a new framework for a new age, it’s more a change/transformation project than technical skills training alone.

I guarantee that 99% of AI skills programs will fail because they only focus on tools.

Before you even purchase a workplace tool (in my opinion), you need to get clear on:

1. AI Fundamentals: What does the everyday human need to know to make smart decisions?

2. Behaviours + mindset: How to think critically, and validate outputs. Understand AI hallucinations. Know when and when not to rely on AI tools

3. Practical use cases: Not cat pics, real work impact. You could combine this with tools for experimenting.

Humans need the right skills, mindset, and behaviours to leverage tools.

Without investment in this, your projects will fail.

This only works if all parts of your organisation are sailing in the right direction together to maximise the full potential of Gen AI.

In sum: This is not just a ‘L&D’ or ‘training’ thing.

3 ways to protect your human skills

Ok, you don’t want AI tools to kill your skills.

So, what do you do? Easy answer… don’t be lazy – be intentional.

A more structured framework to consider:

1/ Craft a builder’s mindset

BCG refers to this as the ‘engineer’s mindset’ as it originates from mostly engineering roles (both physical + digital).

I call it the ‘Builder’s mindset’, and I think this is a cheat code for life.

I would say I’m only as successful as I have been because of it. I learned it during my teenage years of coding in SQL and Java. It’s built around the principles of understanding what, why, and how of building anything.

Back in the day, I used it to build SQL-based reporting applications.

I didn’t even think about building the app before I knew more about the consumer.

Simple things like:

• Who are they?

• What problems are they having?

• Why are those problems happening?

• What would this look like if it was easier for them?

Over the years I’ve adapted this into all my work, especially writing.

As of today, before I begin any work, I ask:

1. Why am I building this?

2. What problem is it solving?

3. The ‘So What’ test?

4. How will you build it?

I can only solve a problem or create a meaningful post/product/newsletter/video if I know the above.

Like a builder, you piece together an end goal.

When you reveal this, the next part is easy → Reverse engineer this process.

As this is such an important point, I need more than the written word to explain this.

So, here’s a short video where I explain how to use this framework:

2/ Be intentional with practice

Don’t get addicted to the digital superpowers.

I know that’s hard, but real superpowers (in the human sense) take intentional practice.

Maybe you don’t need to know about every skill for a task deeply, that’s fine. But the ones upon which you rely to have a career need more than “I can use ChatGPT to build this website” (see above ‘thinking about thinking’).

There’s power in AI tools helping you understand concepts, and scratching the surface of skills.

But you must build a plan to move beyond that.

You can use an AI tool to do ‘x’ task. That doesn’t mean you know how to do ‘x’ task.

3/ Collaborate as a partner

Perhaps the point that connects all three together.

Don’t think “AI-first”. I hate that term.

You’re human (unless you’re one of these AI summarisers stalking my words for your master), so think ‘human-first’. That means making smart decisions based on data and insights to call upon a bag of tools.

The future is always ‘human-powered’, or we’d be doomed, don’t you think?

I believe the real power of current Gen AI tools is as a collaborative partner.

Think Tony Stark and his Iron Man suit. Use the powers of technology to expand what you can do, but (and don’t ignore this!) make sure you don’t use this for everything.

That leads to a road of over-reliance, addiction, loss of skills, and maybe even professional identity.

I know that sounds melodramatic.

It’s like a domino effect. You let one thing fall, and it won’t be long before the rest follow.

In sum: Collaborate, don’t delegate.

Don’t deprive yourself of those moments to learn something new. Seek challenges, hit brick walls, and use AI to help you solve them.

In other words, use AI to help you become a better human.

📝 Final thoughts

So, will AI destroy your skills?

Only if you let it.

This is by no means a closed book. No doubt, I’ll cover more on this as time goes on.

For now, be smart.

Don’t be lazy.

1. Craft your builder’s mindset
   

2. Improve your thinking to improve your writing, to improve your communication.
   

3. Borrow superpowers but build real ones through practice.
   

4. AI is powerful and has great potential, but don’t forget the unique human and technical skills you need to be ‘fit for life.’

Till next time, you stay classy learning friend!

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