Imagine for a second that you have spent your
entire professional life begging for one specific
thing. Like your whole career. Right. I mean,
for decades, you have been pounding the table,
you know, altering your entire workflow, restructuring
a whole industry, all just to get this one highly
specific outcome. Yeah, you're just totally obsessed
with it. Exactly. And then one day someone invents
a machine that just, it just gives it to you
instantly. perfectly in endless quantities. You'd
think you'd be throwing a parade. Right. It sounds
like an absolute dream come true. Or a classic
monkey's paw situation. Oh, yeah. Because, you
know, getting exactly what you asked for is quite
often the quickest way to realize you were asking
for the completely wrong thing all along. And
that is exactly the brutal realization that's
currently just... sweeping through our education
system, which is what we are getting into today.
It's a huge shift. It really is. Welcome to the
Deep Dive, everyone. We are jumping right into
a fascinating piece from April 2026 by Gary Ackerman.
Over at hackscience .education. Yeah, yes, exactly.
The post is titled, Generative AI. We are getting
what we asked for. And it outlines this massive.
unintentional irony playing out in classrooms
right now. Such a great framing of the issue.
It is because teachers and administrators, they've
spent decades demanding data. You know, give
us the measurable data. Show us the metrics.
Right. But now that generative AI is basically
handing them pristine, flawless data on a silver
platter, they are fundamentally dissatisfied.
They hate it. They really do. Okay, let's unpack
this. Because to understand why educators are
suddenly dreading the very thing they demanded,
we have to, um... we have to look at how our
brains actually work. That is the core of Ackerman's
argument right there. He grounds this whole crisis
in the actual mechanics of human thought. So
psychology, basically. Right. Specifically, he
references Daniel Kahneman's framework from the
2011 book, Thinking Fast and Slow. Yeah, a classic.
It really is. And to understand the trap we've
fallen into with AI, we have to understand Kahneman's
two systems. Right. So for those who might not
have read it, Kahneman argued that our brains
basically operate using in two distinct systems
of thought. System one and system two. Exactly,
so system one is your fast, intuitive, automatic
thinking. It's the trust your gut reflects. The
instinct. Yeah, like if you're walking down the
sidewalk and a bicycle suddenly swerves toward
you, you don't stop to do a bunch of like physics
calculations about mass and velocity. Or you'd
get hit. Exactly, you just jump out of the way.
That is system one keeping you alive, it's instantaneous,
and it feels practically effortless. Effortless
is the key word there. It burns almost no cognitive
calories. Right. But then we have system two,
which Ackerman characterizes as the mandate to
trust your brain. OK, so gut versus brain. Precisely.
System two is deliberative cognition. It is incredibly
slow. It requires intense focus. And crucially,
it is biologically exhausting. Oh, man. Yeah.
It's that feeling you get when you're, I don't
know, sitting down to calculate a complicated
monthly budget. Or doing your taxes. Yes. or
trying to conjugate verbs in a new language you're
learning. You can literally feel your gears grinding.
You can. It is actual physical work for your
body. Because you're trying so hard. Right. Because
system two creates friction. When you are grappling
with a complex concept, your brain is actively
forging new neural pathways. Wow. OK. Yeah. That
friction, that slowness, is the literal mechanism
of learning. You are forcing your brain to reorganize
itself. OK. So we have system one trusting the
gut and system two trusting the deliberative
brain. Yep. But Ackerman's post introduces a
completely new wrinkle into this framework. Right.
And this is where he brings in that 2026 pre
-print paper, right? Yeah. By Shaw and Nave.
Shaw and Nave. And the title of their paper really
tells you where this whole thing is heading.
Let me find it. Here it is. Thinking fast, slow,
and artificial. How AI is reshaping human reasoning
and the rise of cognitive surrender. Cognitive
surrender. That phrase just hits hard. It really
does. So Sean and Ava are proposing that because
of modern technology, we now have to account
for a system three. An artificial system three,
which they summarize perfectly with the phrase
trust the data. Trust the data. Right. If system
one is trusting your gut reflex and system two
is trusting your slow, deliberative brain, System
3 is trusting an external artificial system.
Okay, I see. It's looking at the data the machine
provides and just accepting it, completely bypassing
your own internal cognitive processes. That makes
me think of navigation. like using a GPS. Oh,
that's a great example. Right. So system one
is me jumping out of the way of that moving bike.
Yep. System two is me sitting down with a big
paper map, analyzing the topography, and like
carefully mapping out a route to avoid busy roads.
Lots of cognitive friction there. Exactly. System
three then would be me just blindly following
the blue line on my smartphone's GPS, even if
it is actively routing me right into a lake.
Which happens. Right. Because I'm not navigating
anymore. I'm just trusting the data in the machine
handed me. That is a perfect visualization of
the mechanics at play here. You've surrendered
the rote finding entirely. I've cognitively surrendered
to the phone. Exactly. The artificial system
did the thinking, and you just... consume the
output. But wait, hold on though. Hasn't trusting
the data always been considered like the ultimate
objective good in our society? Oh, absolutely.
I mean, we are constantly told in business and
science, just in everyday life, to put aside
our biases, stop relying on flawed gut feelings,
and look at the hard data. Numbers don't lie.
Right. It sounds like a system three approach
should be the absolute pinnacle of logic and
reason. Why is Shaw suddenly framing trust the
data as a negative thing? What's fascinating
here is how Shaw and Nave separate the concept
of data from the process of cognition. The mandate
to trust the data does sound entirely objective
and scientifically rigorous. Yeah, it does. But
in practice, just as the urge to trust your gut
sways us toward lazy system one intuition, the
modern mandate to trust the data sways us toward
system three outsourcing. And here is the crucial
mechanism that makes it dangerous. It completely
bypasses human deliberative cognition. It entirely
bypasses system two. Oh, I see. So you get the
result without doing the math. Precisely. When
you just accept the artificial output, the data,
you aren't actually doing that slow, effortful,
friction -filled thinking yourself. You're just
taking the answer. Right. You are outsourcing
the cognitive load. You aren't building those
neural pathways. Wow. And this shift toward system
three isn't just some abstract psychological
theory happening in a vacuum. It has collided
head on with a decades long obsession in our
schools. Which brings us to Ackerman's slightly
snarky premise in his post. He's got a point,
though. He really does. He points out that for
decades in education, the dominant unquestionable
mantra from the top down has been trust the data.
If we connect this to the bigger picture, the
modern education system has been operating under
an intense systemic pressure to quantify absolutely
everything. Like an assembly line. It really
is a highly industrialized approach to human
development. Let's look at the reality of that
for a second. Think about it from the perspective
of a school administrator, or a district superintendent,
or even just a classroom teacher over the last
20 or 30 years. They're under so much pressure.
Insane pressure. You can't just look at a school
board and say, trust me, the kids are learning.
No, they'd laugh you out of the room. Right.
You have to prove it. Every single decision made
in a classroom, every piece of evidence used
to draw a conclusion about a school's funding,
every solitary item recorded in a teacher's grade
book, it all had to be grounded in data. Measurable,
chartable, graphable data. Exactly. And this
is where the conflict between data obsession
and genuine learning really takes root. How so?
Because true learning, that system to neuroplasticity,
that internal cognitive friction... is practically
invisible. Oh, wow. Yeah. You cannot easily log
a student's internal struggle into a district
-wide spreadsheet. You can't graph confusion
turning into understanding. Exactly. So over
time, the system became completely fixated on
the measurable end product, because that was
the only thing you could see. The proxies for
learning became the goal itself. Yes. The worksheet,
the five paragraph essay, the multiple choice
score. Yes, those artifacts generate the hard
data the system requires to prove that it's functioning.
But in demanding those specific artifacts, the
actual messy human process of deliberative learning
was completely overshadowed. They just wanted
the paper at the end. Right. The system optimized
for the output, not the internal process. Let's
build an analogy here to really solidify the
mechanics of this, because I think it's something
everyone experiences. Sure. Imagine you decide
you want to get really fit. You want to build
muscle mass. OK, good call. So you go out and
buy a really expensive state -of -the -art smart
scale. It measures your weight, your bone density,
your body fat percentage, everything. It gives
you all the data. all the data, and you become
absolutely obsessed with the data from that scale.
You track the numbers every single morning, you
make intricate spreadsheets, you draw trend lines
to project your future fitness. Sounds exhausting.
It is. But you never actually go to the gym to
lift heavy things. Oh no. You are entirely obsessed
with the data while completely ignoring the actual
physical process required to change your body.
That is a brilliant way to look at it, really.
Because the mechanics of muscle growth perfectly
mirror the mechanics of system two thinking.
How do you mean? Well, a muscle only grows when
you subject it to intense stress, causing micro
tears in the fibers. The lifting is what matters.
The struggle. Yes. The weight on the scale is
simply a byproduct. It's a lagging indicator
of that physical exertion. You've confused the
measurement of the thing for the thing itself.
And in education, the data. the essay, the test
score, is supposed to be a byproduct of a student's
cognitive exertion. Their mental micro -tears.
Right. Their system two deliberative thought.
But the educational system gradually stopped
caring about the invisible heavy lifting and
started demanding only the visible numbers on
the scale. So if you have a massive societal
system that demands nothing but visible formatted
data for decades. Decades of it. Right. It shouldn't
be a surprise when someone eventually invents
a machine perfectly designed to deliver exactly
that. And here's where it gets really interesting.
This is the core irony of Ackerman's post. The
punchline. Yes. Generative AI enters the chat.
And students, being incredibly adaptable, are
now using these AI tools to give educators exactly,
precisely what they have been demanding for 30
years. They are delivering the pristine data.
Instantly. By using AI to generate the answers,
students are, as Eckerman puts it, cutting to
the chase. They really are. Let's say a teacher's
highly structured rubric demands a 500 -word
essay with a clear thesis statement, three supporting
arguments with historical citations, and a summarizing
conclusion. A very standard design. Very standard.
That is the required data for the gradebook.
So a student feeds that prompt into a generative
AI, and the machine generates it in about four
seconds. No. Gone. Student hands it in. It checks
every single box on the rubric. It's flawless
data. But there's absolutely nothing else attached
to it. Nothing. No struggle. No grappling with
complex concepts. No synthesizing of disparate
ideas. No late night stressing over a blank page.
Exactly. No cognitive friction whatsoever. Zero
system to deliberative thought. It is the equivalent
of having a robot lift the heavy weights at the
gym for you and then stepping on the scale and
wondering why your muscles aren't growing. And
this raises an important question, one that gets
right to the heart of Shaw and Nave's subtitle,
The Rise of Cognitive Surrender. Right, that
phrase again. When we talk about cognitive surrender,
we really have to look at the biology of why
it happens so easily. It's biological. Oh, absolutely.
The human brain is naturally efficient. Its primary
evolutionary goal is to conserve energy. So we're
inherently lazy. Well, evolutionarily thrifty,
let's say. As we establish, system two thinking
burns a massive amount of cognitive energy. It
is genuinely tiring. Yeah, nobody likes doing
taxes. Right. So when an external tool system
three offers a way to produce the required data
without burning any of that energy, The brain
enthusiastically surrenders the task. Oh, wow.
Think about that in your own life for a second.
Think about the last time you had a massive complex
email thread at work. Oh, I know where this is
going. And instead of reading it, you use an
AI tool to summarize it for you. Guilty. We all
do it. You got the bullet points. You got the
data. But did you actually retain any of the
nuances of that conversation? Probably not. Did
you grasp the subtle frustrations of your coworkers?
No, because you bypassed the System 2 process
of reading and synthesizing. You conserved your
energy, but you surrendered the deep understanding.
And students are doing exactly that on a systemic
level. By handing over the pure data via AI,
students are successfully fulfilling the system's
explicit demands. But they are doing it by relying
entirely on System 3. They're outsourcing the
brain work. They have achieved maximum efficiency
in data production with zero cognitive development.
OK, I have to stop and ask a practical question
here. Go for it. Let's put ourselves in the shoes
of the system itself. You know, you are a school
principal or a state education board member.
OK, I'm the boss. You spend years setting up
a rigorous, standardized system asking for pure,
quantifiable data to ensure students are meeting
specific benchmarks. Right. The student utilizing
new technology provides that pure data with incredible
efficiency. On a purely mechanical administrative
level, shouldn't the system be thrilled? I mean...
The demand was met. The spreadsheet is full of
perfect scores. Mechanically speaking, yes. The
system is operating at peak efficiency. Right.
But the humans inside the system... the teachers
and educators, are not thrilled at all. Not even
a little bit. In fact, they are feeling an overwhelming
sense of dread, frustration, and honestly an
existential crisis. Which leads directly to Ackerman's
brutal foundational conclusion. Yes. So what
does this all mean? Why the dread if the data
is perfect? Ackerman delivers a very striking,
almost melancholic conclusion in his post. He
says educators are getting exactly what they
asked for, but they find it deeply dissatisfying
because we were asking for something that does
not matter. Wow. Let that sink in for a second.
We were asking for something that does not matter.
It is a devastating realization for an entire
industry. I can't imagine realizing that after
a 30 -year career. The pure data, the flawlessly
generated AISA, the perfectly completed worksheet
is fundamentally worthless. if it isn't a byproduct
of the student's internal system to deliberative
cognition. The essay itself was never the point.
Exactly. The actual text on the paper was never
the point. The point was the structural neurological
changes that happen inside a student's brain
while they struggle in the dark to write the
essay. That is such a crucial, clarifying distinction.
The output is meaningless without the process.
Completely meaningless. It's the difference between
buying a souvenir and actually going on the vacation.
Oh, that's a good one. Let's say the goal of
a trip to Paris is to broaden your worldview,
right? To struggle with the language, to get
lost in the streets, and to experience a new
culture. The friction of travel. Exactly. An
AI can instantly print out a beautiful, high
-resolution photo of you standing at the Eiffel
Tower. It looks perfect. Flawless. That's the
souvenir that... That's the data, but it means
absolutely nothing to your personal development
because you never actually traveled there. You
just have the picture. Right. You never tasted
the food. You never walked the streets. You never
experienced the friction. The education system
spent 30 years demanding souvenirs, assuming
that handing in a pristine souvenir meant the
student had taken the grueling trip. And generative
AI completely broke that core assumption. It
shattered it. AI can manufacture an infinite
number of perfect souvenirs at zero cost. It
entirely severed the link between the product
and the process, exposing the massive flaw in
the metric itself. This synthesizes the entire
journey for us so clearly. The conflict is fully,
uncomfortably exposed now. It really is. This
decades -long obsession with data metrics, with
what Shaw and Knave now classify as System 3
artificial thinking, accidentally highlighted
a very hard truth. Which is? In genuine learning,
that System 2 deliberative thought is inherently
messy. It is invisible. It is really hard to
measure on a spreadsheet or grade with a standardized
rubric. It involves failure, hesitation, slow
progress, and immense cognitive friction. Everything
the system hates. Right. It is the exact opposite
of a clean, instantly generated data point. And
crucially, it is impossible to fake with an AI.
By getting exactly what they asked for, instant,
perfect data educators realized they had been
asking the wrong question all along. They asked
for the final product when the only thing that
actually mattered was the internal process. The
heavy lifting at the gym. The messy vacation.
And the introduction of System 3 into everyday
life means this isn't just an education problem
anymore? Oh no. It's everywhere. This dynamic
is everywhere. The temptation to bypass the messy
process and just grab the clean data is practically
universal now. So true. Let's quickly recap how
we got here before we wrap up. Sure. We started
with Daniel Kahneman's foundational framework
of human thought. System one, the fast, intuitive,
low -energy gut reaction. The bike swerve. Right.
And system two, the slow, deliberative, heavy
lifting brain power that actually builds understanding.
The friction. Exactly. Then we looked at how
Shaw and Nave's 2026 paper introduced the artificial
system 3. trusting the data and outsourcing the
thought process entirely to conserve energy,
which leads to cognitive surrender. A great term.
Really is. Finally, we arrived at Gary Ackerman's
incredibly ironic realization. The education
system's relentless decades -long demand for
pure, measurable data led to a completely hollow
victory when generative AI gave them exactly
what they asked for, completely devoid of the
actual human learning process. Which leaves us
with a necessary and slightly uncomfortable application
of this idea. Let's hear it. If a massive well
-intentioned system like education fell so deeply
into the trap of obsessing over data that ultimately
didn't matter It is worth looking at your own
life. Oh, wow. Yeah. Think about your daily routines,
your workplace habits, or your long -term goals.
Where are you blindly demanding system three
data? Where are you taking the shortcut? Exactly.
Where are you taking the hyper -efficient shortcut
just to get the result, and in doing so, completely
bypassing the messy human system two deliberative
process that actually gives that result its value?
Are you just stepping on the smart scale every
day and ignoring the heavy lifting? That's the
question. It is a phenomenal question to chew
on as these tools become more and more integrated
into our lives. Thank you so much for joining
us on this deep dive into the mechanics of cognition
and the irony of our data obsession. He's a fun
one. Keep questioning the metrics. Keep leaning
into that slow, friction -filled, deliberative
thinking. And remember to always stay critically
engaged in a world that is practically begging
you to surrender to the easy answer. Don't just
take the souvenir. Exactly. Because as we learned
today, getting exactly what you asked for might
just mean you are asking for the wrong thing
all along. Catch you next time.