This Deep Dive podcast is AI generated from the Start With AI Newsletter on LinkedIn - linkedin.com/newsletter/start-with-ai

We’re diving into a super intriguing idea today that flips the script on how we think about staying relevant in an automated world. Instead of just fine-tuning our skills to perfection, we’re exploring how embracing the messy, unrefined bits of being human might actually be our secret weapon.

We kick off with a vivid story about a mathematician in a resource-strapped classroom in South Carolina, where kids are solving complex equations without any fancy tech. This sparks a conversation about how cognitive friction—like the kind those kids face—can actually boost creativity and problem-solving.

As we unpack this together, we’ll challenge the notion that optimization is the be-all and end-all, and instead, we’ll highlight the irreplaceable value of genuine human connection and curiosity.

So, grab your headphones and let’s get ready to rethink what it means to be human in the age of AI!

Details:

What if the secret to thriving in an AI-dominated world lies not in perfecting our skills but embracing our wonderfully messy human nature?

Enter the classroom of Po Shen Lo, a mathematician who, despite the lack of modern tech, witnesses students solving problems at lightning speed. What’s their secret sauce?

They play games, they create, they innovate—free from the constraints of a curated digital experience. This episode takes us through the implications of this creativity, arguing that our educational systems often push us towards optimization that can ultimately lead to unemployment.

We explore how standardised training can strip away the very qualities that make us human, turning us into 'human versions of AI.'

The conversation encourages listeners to reflect on what makes them irreplaceable in a world where machines are becoming increasingly capable. How do we cultivate genuine curiosity and care in our interactions?

Through stories, humour, and engaging anecdotes, we challenge the notion that efficiency should reign supreme and propose a new paradigm where the ability to connect and create becomes the ultimate currency in the future economy.

So, grab your headphones and join us as we navigate the delightful chaos of being human!

Chapters:

• 00:02 - The Mathematician's Arrival
• 02:31 - Exploring the Mathematician's Story
• 06:00 - The Impact of Technology on Learning
• 09:05 - The Irreplaceable Human Skill
• 13:51 - Using AI to Discover Human Value
• 18:30 - Finding Your Value in a Tech-Driven World

Takeaways:

• The kids in that South Carolina classroom demonstrated that creativity thrives in the absence of tech, showing us how essential cognitive friction is for learning.
• Po Shen Lo's observations challenge the idea that standardization and optimization are the keys to success in an automated world.
• The future will favour those who can build genuine human connections, rather than those who simply master technical tools.
• Heather Masters argues that the irreplaceable human skill is the ability to genuinely care and connect, which machines can’t replicate.
• Navigating an unpredictable future requires us to focus on our unique human qualities and values, not just technical skills.
• The ultimate takeaway is that trust and human connection are becoming the currency of the future economy, as machines take over routine tasks.

Companies mentioned in this episode:

• Po Shen Lo
• Carnegie Mellon
• Dan Martel

Links referenced in this episode:

• linkedin.com/newsletter/start-with-ai

So picture this.

A brilliant mathematician walks into this rural, like, severely underfunded fourth grade classroom in South Carolina.

Okay?

I'm picturing it.

And there are no iPads anywhere on the desks.

There's no high speed Internet pulsing through the walls.

Right.

None of the usual modern tech.

Exactly.

So he picks up a piece of chalk, walks to the blackboard and just writes out a sequence.

1 3 5 7 9.

Just a standard addition problem.

Yeah, but before he can even finish, draw the second line of the equal sign, the kids are just shouting out the answer.

Wait, really?

Just instantly.

Instantly they yell out 25.

And he's completely stunned.

I mean, he asks them how they're processing information with that kind of raw.

Velocity, especially in a place completely devoid of, you know, educational tech.

Right?

So he asks them what they do for fun, and the kids just look at him like it's obvious.

And they say, we make our own games.

Wow, that is such a powerful image.

It really is.

And welcome to today's Deep Dive, everyone.

We are exploring a fascinating, honestly kind of counterintuitive idea for anyone trying to stay relevant today.

Yeah, we're looking at what happens in an increasingly automated world.

Right.

What if the key to surviving the AI revolution isn't about perfectly optimizing your skills, but, well, leaning hard into the messy, unoptimized parts of being human?

I love that framing.

Yeah, the piece is titled Start with AI.

Real AI.

Real talk for practitioners who want to stay human.

It's a piece of writing that takes all that existential anxiety so many of us feel about automation and just completely.

Reframes it because we've spent, what, the last few decades essentially treating our human inefficiencies as bugs.

Exactly.

Our weird tangents, our boredom, our need to just pause and process.

We treat them like glitches in our personal operating systems, right?

So we download productivity frameworks.

We try to hack our morning routines to squeeze out, like an extra 10 minutes of output.

We are desperately trying to turn ourselves into frictionless software.

And Heather Masters looks at that trajectory and argues that we are optimizing ourselves right out of a job.

And if you are listening to this right now, whether you're a corporate coach, a tech worker staring down a new coding AI, or just someone overwhelmed by algorithmic life, this Deep Dive is going to reframe your value.

It really challenges how we define what makes us useful.

Totally.

And to do that, we have to start by digging deeper into that mathematician story from the intro.

Right.

The guy in the South Carolina classroom.

Yeah.

So that mathematician is Po Shen Lo.

He's a Carnegie Mellon professor and the former coach of the United States Maths Olympiad team.

So this is a guy who understands high level cognitive processing better than almost anyone on Earth.

Exactly.

He travels to one of the poorest counties in South Carolina.

Right, to a classroom where the kids don't have smartphones to scroll on.

What's fascinating here is the underlying mechanism of cognitive development that Lowe observed in that room.

Right, because it's not just a cute story.

No, not at all.

When those kids say, we make our own games, it's not just a sweet anecdote about childhood imagination.

It is a profound statement about how the brain builds architecture when it's left alone.

You mean?

Exactly.

These kids are finding complex things for their minds to chew on precisely because no algorithm has arrived yet to do the chewing for them.

Ah, I see.

In the absence of a curated, frictionless digital feed serving them infinite entertainment, their brains are forced to manufacture the entertainment they're encountering.

A blank space.

Yes.

And rather than being hindered by it, they are fueled by it.

Okay, let's unpack this, because I want to make sure we aren't crossing a very dangerous line here.

Fair enough.

What are you thinking?

Well, are we suggesting that having no Internet or educational resources is inherently a good thing?

I mean, surely we aren't romanticizing lack of resources, right?

Oh, no, absolutely not.

Poverty itself is a developmental disaster.

Lack of resources limits opportunity, full stop.

Right.

We don't want to treat systemic underfunding as some kind of rustic character building exercise.

Exactly.

But what low is isolating isn't the poverty.

He's isolating the cognitive friction that happens to be a byproduct of their lack of screens.

Friction.

Okay, explain that.

The advantage is that they have to actively construct their reality rather than passively consume it.

Like when you remove the tech that constantly tells you what to look at and how to play.

Right.

You force the brain to build its own neural pathways to solve the problem of boredom.

You know, it makes me think about using a GPS on your phone.

Oh, that's a perfect analogy.

Right.

Because when you drive in a new city and blindly follow the blue line, taking the lefts and rights exactly when the voice tells you to, you arrive at your destination, but you have absolutely.

No idea how you got there.

Exactly.

Your brain outsourced the spatial mapping to the machine.

You never actually learned the layout of.

The city you were Just following prompts.

Yeah, but if your phone dies and you have to navigate by looking at street signs, making wrong turns, and correcting yourself, you build an internal map.

It's wildly frustrating in the moment, but you actually learn the territory.

Right.

And these fourth graders in South Carolina are building their own internal maps because they have to.

There is no blue line telling them where the fun is.

That internal mapping is exactly the point.

The device holds the intelligence when you use the gps.

And Lo saw something different in that classroom.

He saw minds that retained their own intelligence because they hadn't outsourced the heavy lifting.

He's been traveling across rural America and Africa observing this repeatedly.

Wow.

So it's a consistent pattern.

Yeah.

He is finding that the kids who haven't been optimized for standardized tech assisted performance are often vastly better positioned to think laterally.

And the stark contrast to this is what he observed when he looked at the other end of the educational spectrum.

Right.

Yes.

He watched an AI powered exam coach being used by students in China.

And this AI tool was functioning exactly as it was programmed to function.

I assume flawlessly.

It was highly efficient at identifying a student's weaknesses and drilling them on standard questions until their test scores improved.

I mean, that sounds like an optimization masterpiece.

It was.

But Lowe looked at this highly effective system and concluded it was, quote, entirely the wrong thing.

Wait, why, if it improves test scores?

Because he said, the curriculum as it stands is producing human versions of AI.

We are training people to do exactly what AI already does.

Better.

Wow.

Human versions of AI.

That is chilling.

If we connect this to the bigger picture, that observation dismantles the entire philosophy behind modern corporate training and education.

Because we've been pushing for standardization for what, over a century?

Exactly.

The goal of schooling and corporate onboarding has always been a predictable, repeatable, free, flawless execution of a known process.

Think about your own onboarding at your last job.

Right.

Were you trained to creatively solve unprecedented problems?

Probably not.

You were likely trained to memorize the company's algorithm for handling a client.

We historically wanted people to act like machines, mostly because we didn't have machines that could do those tasks yet.

Right.

We were just placeholders for the software.

But now, in a world dominated by actual artificial intelligence, standardization is a massive.

Trap because the AI does it infinitely better.

Faster and cheaper.

Exactly.

We are spending billions of dollars and years of our lives training human beings to execute processes that machines have already mastered.

But wait, can I ask you to clarify something?

What is the fundamental difference between knowing the information like the students with The AI coach and applying it in a messy real world scenario.

Well, knowing the information in a standardized curriculum means you can perfectly execute a clean protocol when all the variables are control.

Right.

Like a closed system where the test has a known answer.

Exactly.

Applying knowledge in a messy real world scenario means you have the capacity to keep learning past the point where the curriculum ends.

So when a novel problem arises that isn't on the test, what happens?

The standard answer stops working.

At that moment, the human version of AI freezes.

It throws a mental error code because.

It hasn't been programmed for this anomaly.

Right.

But the unoptimized mind, the one accustomed to cognitive friction and making its own games, doesn't freeze.

It looks at the anomaly and figures out a new way to play.

It's like imagine dedicating your entire life, training eight hours a day studying every mental shortcut, just to become the world's fastest human calculator.

Right.

You optimize your brain to do long division in milliseconds.

And on the exact day you finally achieve your goal, the digital calculator hits the market for $5.

It's a perfect analogy.

You spent a lifetime optimizing yourself for a game that just became economically irrelevant.

Which means we all have to pivot.

Standardized skills are becoming obsolete.

Yes.

We have to isolate what the irreplaceable human skill actually is.

If it's not optimization, what cannot be coded into a large language model?

And this brings us to the perspective of nlp, or Neuro Linguistic programming.

Yes.

Heather Masters really leans into this in her newsletter.

For anyone listening who might be unfamiliar.

NLP is a psychological approach.

It involves analyzing strategies used by successful individuals and applying them to reach a personal goal.

Right.

It relates thoughts, language, and learned behavior to specific outcomes.

NLP practitioners focus deeply on how humans communicate and change.

And Masters draws a really sharp line between two distinct concepts.

Here she does.

On one side, you have running a process that is the human calculator.

You follow the script, ask the diagnostic questions, output the advice, and machines can.

Learn to run a process easily.

But on the other side, you have the ability to hold the room while everything underneath shifts.

Holding the room?

That requires a completely different architecture than just running a process fundamentally different.

A machine can perfectly mimic the transcript of a therapy session or an executive coaching call.

It can analyze the semantic data and spit out the statistically optimal response.

Exactly.

But holding a room requires a human being who is tested, genuinely curious, and deeply invested in the outcome of the person sitting across from them.

And Po Shen Lo actually has a Brilliant.

Simple test for what AI can't replicate here.

The eyes test.

Right.

He says you can read it in a person's eyes.

You instinctively know whether you are being met or.

Or if you were being managed.

I love that phrase.

And Heather shares a great quote from Low.

You will never get that confidence from a robot's eyes.

Being met versus being managed.

I mean, think about the last time you were sitting in a doctor's office or on a call with a customer.

Service rep. You can physically feel when they're running through a mental checklist.

Exactly.

Their eyes glaze over.

They're listening for keywords to categorize your problem and get you out of their queue.

You are being managed.

Now, compare that to those rare moments when someone actually stops, breaks the script, looks at you directly, and you feel genuinely seen.

They go off book because your specific reality actually matters to them in that moment.

This raises an important question about the systems we currently operate in.

Yeah, what kind of question?

Well, if the feeling of being genuinely met is becoming increasingly rare and therefore overwhelmingly valuable, what are we doing to foster it?

Are our educational and corporate systems cultivating genuine curiosity and the intention to help?

Exactly.

Or are our KPI dashboards and school curriculums actively punishing it because taking the.

Time to genuinely meet someone ruins your efficiency metrics?

Right.

We currently reward the appearance of helping packaged as a fast transaction.

Here's where it gets really interesting, though, because I have to push back on the practicality of this.

Okay, push back.

How do you systematically train someone to actually care?

I mean, you can teach a sales script, you can teach a coding language, but you can't issue a certificate in giving a damn.

No, you really can't.

You either have that deep empathy and curiosity or you don't.

So how does an entire generation stay human if caring isn't something you can just download into a syllabus?

Well, maybe the premise of training is the flaw in the logic.

You don't inject empathy into someone via a corporate seminar.

So how do you get it?

Heather Masters suggests that this trait isn't taught.

It's forged through lived experience.

You uncover their capacity to care by stripping away the rigid metrics.

You stop incentivizing robotic behavior.

Exactly.

The people who will matter most in the coming decade are the ones whose first instinct is to help the person in front of them, not to look good while doing it.

The ones who stay curious, far past the point where it's financially rewarded.

And as the newsletter points out, that's a very narrow description.

But that scarcity is precisely where the economic and social value lives.

If you can do what the machine can't genuinely care, you become irreplaceable.

Right.

And what's great is that Heather Masters doesn't just preach this theory from a distance, she turns it inward.

Yeah, that's what makes her newsletter so compelling.

She shares her own struggle with trying to apply this unoptimized human theory to her actual life.

She admits that right now, trying to look 10 years into the future and plan a career path is incredibly difficult.

Because the technological ground is shifting so violently.

Right.

Long term planning feels like guessing.

The algorithmic noise is deafening.

She needed to figure out her own unwritten human value, her own uncoded vision.

And to find that vision, she employed a method that sounds completely paradoxical at first glance.

She used an AI.

Yeah, specifically an AI trained on the frameworks of Dan Martel.

Right.

For context, Dan Martel is a highly sought after coach for SaaS founders.

He's known for very intense, high performance business frameworks.

So Masters essentially put herself in the digital hot seat.

She didn't ask a generic chatbot to write a business plan.

No.

She used this specialized AI to interrogate her own thinking.

So she used the exact machine technology she's trying to differentiate herself from to actively move through her own psychological patterns.

The beautiful paradox, really?

But how does that actually work in practice?

How do you use a machine to find your humanity?

You use it as a high powered spotlight acting as a mirror.

She let the AI strip away her corporate jargon and her safe, optimized career plans.

Because an AI trained to aggressively question your assumptions doesn't accept vague, polite answers.

Exactly.

It forces you to articulate exactly what you want.

It removes the friction of your own second guessing.

It kept prompting her, kept reflecting her own hypocrisies back to her until she could sketch out an incredibly clear vision.

And that vision had nothing to do with standard corporate success.

Right.

It wasn't a massive tech startup or a flawlessly optimized consulting firm.

She envisioned a retreat, a physical place.

She saw animals, physical books, a beach house and dogs.

And most importantly, she envisioned a place for kids who have lost their internal signal in the deafening noise of the algorithmic world.

A place where they could come to find that signal again, completely unplugged.

And she positions Generation X as the crucial demographic to make this vision a reality.

She calls Gen X the Bridge Generation.

Because they grew up entirely analog.

They have a physical, bodily memory of what it feels like to be truly bored.

They know how to be present to be deeply curious without a screen feeding them their identity.

But they also learn the digital landscape fluently as adults.

They speak both the language of the dirt playground and the language of the algorithm.

So what does this all mean for you?

The listener Masters identifies that analog lived experience as the exact medicine the next generation needs to survive what's coming.

And going back to the idea that you can't teach someone to care.

She argues this medicine isn't taught, it is transmitted.

Yes, passed down through human connection, through the physical act of holding the room.

It's transferred when an unoptimized human looks another human in the eyes and meets them where they are.

And the way she consciously engaged with the Dan Martell AI is the blueprint for how we all need to operate.

Right.

Because she didn't surrender her agency to the tool.

It's like using a highly advanced digital compass to find your way out of the matrix and back to the wilderness.

Exactly.

The AI didn't invent the vision of the dogs in the beach house.

It just asked the right interrogating questions to clear the brush.

It acted as a mirror for her own analog memories.

And when she remembered the story of Po Shen Lo and those South Carolina kids, her vision clicked into focus.

She realized that naming what you are building, especially when the future is completely uncertain, is the exact same act as those kids making up a game.

It is original creation in the absence of a prescribed path.

And Heather mentions she's currently finishing a playbook for NLP practitioners on exactly this concept.

Right.

A guide on how to integrate powerful AI into their workflows without losing the messy, caring core of what makes them human.

Which brings us to the ultimate thesis of this whole deep dive.

The final takeaway from her newsletter that ties it all together.

The kids, the exam coaches, the beach house.

Yep, she writes, the people who come out of this shift intact won't be the ones who mastered the most tools.

They'll be the ones who stayed human enough to be trusted with what matters.

It perfectly synthesizes the tension.

Mastery of tools is just the baseline.

Now, learning to prompt, learning to code.

Everyone has the same tools, right?

Trust.

Human trust, built on the physical reality of being genuinely met and truly seen, is the ultimate currency of the future economy.

So for you listening, the question shifts from what technical skills am I learning to something much deeper.

What are you building toward?

And does it feel big enough to be worth the uncertainty?

We want to leave you with a final thought exercise to chew on as you go back to your routine today.

Yeah.

Think about this Imagine you log into work tomorrow morning and you are told that an AI has been installed overnight that can perfectly execute 100% of your daily technical tasks.

Your spreadsheets, your code, your emails.

All of it instantly replaced by a machine that never sleeps and never makes a typo.

If all your technical output is suddenly brought to zero value, what is the unwritten human value you bring to the room that the machine couldn't capture?

What is your version of making your own games?

Exactly.

Finding that answer isn't just a fun philosophical exercise anymore.

No, it really isn't.

In the age of total algorithmic optimization, finding the messy, caring original parts of yourself is your actual survival guide.

Thanks for taking this deep dive with us.

Keep making your own games.