Why We Always Need Someone to Blame
AI anxiety, the scapegoat mechanism, and what it means for leadership
Why I Wrote This
AI blame is nothing new.
It's just the latest version of humanity's oldest reflex.
This essay is meant to inspire you to lead more boldly.
To give you courage to get ahead in your career even if you feel far behind.
What You'll Get
The real reason people are terrified of AI—and why it has nothing to do with the technology itself
Why your expertise feels threatened even though you're smarter than ever
The five questions you need to ask to stay relevant when junior employees can outpace senior teams
How three leadership shifts let you guide change without becoming an AI expert
Why the choice you make today determines whether you'll lead the next decade or get left behind by it
Why AI is So Scary
First we sacrificed children.
Then animals (goats!).
Then witches.
Now AI.
Understanding that the human species was formed by and is built on sacrifice—on scapegoating—can help us navigate the challenges of AI with clarity instead of panic.
Quick Note:
This is the longest article I’ve written.
But I also think it’s the most valuable, by a lot!
If you have the endurance to read through, I’m confident you’ll find the sacrifice 😉 worth it!
Thank God They Killed That Guy
Studying ancient texts and myths, René Girard, a French literary critic turned anthropologist, uncovered humanity's founding violence.
He saw that in literature, this theme of scapegoating appeared across every culture, every era, every story.
From Greek tragedies to biblical narratives to modern novels
—the same pattern repeated endlessly.
He explained this by showing that human societies literally could not exist without sacrifice.
Here's what this looked like in practice:
The community would fracture.
Rivalries would escalate.
Brother against brother.
Neighbor against neighbor.
Everyone competing for the same scarce status or resources.
Violence would spiral until it threatened to destroy the entire social order.
Then they would find someone different—a stranger, an outsider, someone who couldn't retaliate.
The community would unite against this scapegoat,
channeling all their mutual hostility into collective violence against a single target.
They would expel them, or stone them, either way they would sacrifice them.
And it would work—temporarily.
Not because external conditions changed, but because the act itself restored peace.
The community that was moments away from tearing itself apart was suddenly unified again. The victim became sacred precisely because their death had saved everyone else.
When the next crisis emerged, they would repeat what worked before.
If the ritual didn't restore order this time, it wasn't because the mechanism was flawed—it was because they hadn't performed it correctly.
They needed to do exactly what they did last time, but more precisely, more completely.
This is, according to Girard, how we can explain religion and really all institutions to this day.
They are built on the sacred memory of successful scapegoating
—the moment when collective violence against an innocent victim restored peace to the community.
The victim becomes the foundation.
But this raises the question:
why did the rivalry start and escalate in the first place?
What drives humans to compete so intensely
that entire communities nearly tear themselves apart?
Why do we fall into these destructive patterns that require such violent solutions?
The answer lies in how we learn to be human.
The Imitation Game
Here's what makes humans different from nearly every other species:
we're born with very few instincts.
A baby bird knows to open its mouth when it's hungry.
A baby deer knows to start running within hours.
A baby turtle knows to crawl toward the ocean.
But a baby human is completely helpless.
No instincts for what to eat, where to go, what to fear, or what to want.
So how do we learn? We copy.
René Girard spent his life studying this phenomenon.
He called it mimetic desire: we learn by imitating others.
And we don't just learn what to do. More importantly, we learn what to want.
Nearly everything we think we want independently,
we actually learned to want by watching someone else want it first.
This isn't conscious imitation.
It's the fundamental mechanism by which we become human.
We model our parents, then our peers, then the broader culture around us.
We don't choose our desires so much as inherit them.
This is how this looks through the ages:
The overlooked toy that becomes irresistible the moment another toddler grabs it.
A three-year-old desperately wanting to help do the dishes (remember this when they're 12!).
That teen unironically sporting a mullet, because they saw some kid on TikTok rocking the 70s style.
Getting an iPhone upgrade every 2 years, because... well, you have no idea why you do this anymore, it's just expected.
We look to others to become our models for what to do, what to want, and how to be.
And that creates a problem.
When Models Become Rivals
Mimetic desire works beautifully—until it doesn't.
When two people want the same scarce thing, imitation transforms into rivalry.
The closer we are to our models, the more intense the competition becomes.
Every family has the person no one talks to anymore.
Simple workplace misunderstandings escalate into years-long feuds.
The most bitter academic disputes happen within the narrowest specializations.
Even our politics: candidates so remarkably similar in background and policy that their tiny differences tear us apart.
Here's why this happens: The person who taught you what to want becomes your greatest threat when resources are limited. Your role model becomes your rival. Your mentor becomes your competitor.
And this is exactly the spiral that leads communities to seek scapegoats.
Modern Scapegoating: Softer but Still the Same
We still do this, just with less blood.
Sports rivalries:
Why do entire cities of strangers unite in passionate hatred against another city of strangers?
Because it's safer to compete against them than fight each other for status, jobs, and mates within your own community.
Office gossip:
Why does everyone suddenly bond over criticizing the same colleague?
Because it redirects workplace competition away from your immediate team. Better to focus rivalry on the "difficult" person than acknowledge you're all competing for the same promotion.
Brand loyalty:
Why do people argue about iPhone vs Android like it's a religious war? Why pay extra for clothes because of a logo?
Because choosing sides lets you belong to a tribe without actual sacrifice. The brand becomes a safe way to establish identity and superiority.
Political polarization:
Why do we find it easier to hate the other party than address the problems both parties ignore?
Because unified opposition feels better than admitting our preferred candidates (and our own positions) are also flawed.
Here's the pattern: Rivalry creates tension. Tension demands release. Scapegoats provide that release by giving us someone else to blame.
The scapegoat mechanism preserves the status quo by redirecting energy that could change systems toward eliminating individuals instead.
Education's Rotating Cast of Scapegoats
Every generation picks a new educational scapegoat:
The calculator was going to destroy mathematical thinking in the 1970s.
The internet was going to make libraries obsolete in the 1990s.
Wikipedia was going to eliminate real research in the 2000s.
Each time, the pattern repeated: initial panic, institutional resistance, gradual adoption, eventual integration.
The underlying educational problems—teaching to tests, rewarding compliance over creativity, maintaining artificial scarcities of knowledge—remained untouched.
The technology was never the real problem.
It was a convenient target for anxieties about deeper systemic issues.
In fact, education reveals the scapegoat mechanism at its most sophisticated.
The entire system depends on manufactured scarcity and ritualized sacrifice.
We design courses so some students must fail.
We create grading curves that ensure hierarchy.
We maintain "academic integrity" policies that protect institutional authority more than learning.
We preserve the fiction that knowledge is scarce when it's actually abundant.
The student who "cheats" becomes the scapegoat that lets everyone else ignore the more uncomfortable question: why do we structure learning as a zero-sum competition in the first place?
The technology that "threatens" educational standards becomes the villain that lets us avoid asking: what are those standards actually measuring, and whom do they really serve?
But now something different has arrived.
Something that doesn't fit the usual pattern of educational scapegoats.
Something that forces the final reckoning.
AI: The Perfect Mimetic Rival
AI is different.
AI is the perfect model, the perfect rival, and perfect scapegoat, for two terrifying reasons:
It thinks and acts just like us
It makes others think and act just like us
This is mimetic rivalry at its purest.
We created artificial intelligence to be our perfect imitator.
We trained it on everything we've written, thought, and created.
We succeeded so brilliantly that it now competes with us in domains we thought were uniquely human.
The writer seeing AI produce compelling prose on command.
The programmer watching AI generate functional code in seconds.
The expert finding their specialized knowledge suddenly accessible to anyone with a prompt.
But here's the real twist: It's not just that AI can do what we do. It's that AI makes it possible for everyone else to do what we do.
The junior analyst with good prompts can now produce what took the senior team weeks to deliver. The novice writer can access expert-level frameworks instantly. The beginning coder can generate solutions that would have required years of training.
The cognitive moat that separated experts from novices is evaporating.
And the rivalry spiral becomes inevitable:
"Ban AI in schools!"
"We need AI detectors!"
"AI will destroy critical thinking!"
"AI companies are evil capitalists!"
Same fear. Same solution.
The Leader's Dilemma: Blame or Build?
We can't exile change.
AI is here.
It's making others just like us.
It's building systems that could potentially replace us.
You can debate whether and how to use it effectively,
but you cannot exile it into the wilderness and pretend that solves the current crisis.
Which means we need to lead differently.
The scapegoat reflex won't work this time.
We cannot sacrifice change on the altar of stability.
Instead, if you want to lead into this AI change, you need to ask hard questions about what value you actually create, which rituals actually serve you, and how to distribute capability without losing coherence.
What This Means For Monday Morning
Understanding the scapegoat mechanism and rejecting it already puts you ahead of 99% of people.
The next step is developing the leadership posture to work with people in a world that still doesn't completely make sense.
First, we ask five questions that cut to the heart of why AI feels so threatening—and why most leadership responses miss the mark.
Then, we unpack the three leadership shifts that let you guide change without becoming an AI expert, maintain authority while distributing capability, and bridge the gap between how you learned to work and how work actually happens now.
Preview: The Five Questions
AI has become our civilizational scapegoat because it's the first rival that perfectly mirrors us—and enables others to mirror us too. Instead of banning or blaming, leaders must:
Face the mirror: Use AI exposure audits to reveal what's actually broken in your systems
Question the rituals: Distinguish between processes that serve learning vs. those that just signal status
Redistribute smartly: Democratize capabilities while maintaining coherence around outcomes
Evolve expertise: Help knowledge holders become knowledge orchestrators
Optimize for capability: Build systems that absorb acceleration without losing direction
The scapegoat offers temporary calm. Real leadership offers permanent capability.
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Five Uncomfortable Questions Leaders Can't Delegate
The path beyond scapegoating requires confronting what AI reveals about us.
These aren't tactical questions about AI implementation
—they're existential questions about leadership itself.
1. "What value do we actually create when information isn't scarce?"
The AI rival shows: Most of your expertise was really information hoarding.
The uncomfortable truth: AI democratizes access to knowledge, analysis, and even specialized reasoning. If your competitive advantage was knowing things others couldn't easily learn, that advantage is evaporating.
The leadership question: When a bright junior employee with good prompts can produce 80% of what took your senior team weeks to deliver, what's the remaining 20% that only humans can provide? Judgment? Context? Relationships? Define it precisely, or lose it entirely.
2. "Which of our rituals serve us, and which just signal status?"
The AI rival shows: Many processes exist to demonstrate importance, not create value.
The uncomfortable truth: The three-approval workflow. The mandatory slide deck. The handwritten exam in the age of spellcheck. The meeting that could have been an async update. AI forces the question: what actually serves the mission versus what serves the hierarchy?
The leadership question: If AI can automate the form, what happens to the substance? Strip away every ritual that exists primarily to show effort rather than generate results. What's left is what matters.
3. "How do we distribute capability without losing coherence?"
The AI rival shows: Traditional organizations hoard capabilities at the top and push execution down.
The uncomfortable truth: AI inverts this model. A well-prompted individual contributor can now access capabilities that previously required entire departments. Strategy, analysis, content creation, even basic coding—all suddenly accessible to anyone willing to learn effective prompting.
The leadership question: Do you democratize these capabilities and risk chaos, or restrict them and guarantee irrelevance? The third option: teach your people to wield new capabilities responsibly while maintaining alignment around outcomes, not processes.
4. "What happens to expertise when the expert's knowledge becomes ambient?"
The AI rival shows: Your senior people built careers on exclusive access to specialized knowledge.
The uncomfortable truth: AI makes that knowledge ambient—available to anyone who knows how to access it. The financial analyst whose complex models can now be replicated by AI. The marketer whose campaign strategies are learnable from prompts. The consultant whose frameworks get commoditized.
The leadership question: How do you help experts evolve from knowledge holders to knowledge orchestrators? From gatekeepers to sense-makers? From monopolists to maestros?
5. "Are we optimizing for control or for capability?"
The AI rival shows: Most organizational design prioritizes predictability over adaptability.
The uncomfortable truth: AI accelerates everything—decision cycles, market changes, competitive responses. Organizations optimized for control move too slowly. Organizations optimized for capability move too chaotically.
The leadership question: How do you build systems that can absorb AI's acceleration without losing coherence? How do you maintain direction without micromanaging methods? How do you lead humans who suddenly have superhuman tools?
Beyond the Scapegoat: Leading Through Cognitive Disruption
Here's what nobody tells you about leading in the AI era:
The challenge isn't the technology.
It's the generational gap that AI accelerates.
You learned to work when information was scarce, when expertise took decades to build, when hierarchies existed because knowledge flowed slowly from top to bottom. Your mental model of leadership was forged in that world.
The people you're leading are learning to work differently.
They expect immediate access to any information.
They assume all capabilities can be learned quickly.
They question why hierarchies exist when knowledge flows instantly in all directions.
AI doesn't create this gap, but it does widen it.
And it forces a choice: evolve your leadership model or watch your influence erode one prompt at a time.
The Three Shifts That Matter
Shift 1: From Knowledge Keeper to Sense Maker
The old model: Leaders possessed information others couldn't access.
The new reality: Information is abundant; insight is scarce.
Your competitive advantage isn't knowing more—it's connecting dots faster, seeing patterns others miss, and translating complexity into clarity. The junior employee might prompt their way to expert-level analysis, but they still need someone who can tell them what it means and what to do about it.
This shift requires:
Building frameworks that help others navigate complexity
Developing pattern recognition that works across domains
Learning to ask better questions instead of providing more answers
Becoming comfortable with "I don't know, but here's how we'll figure it out"
Shift 2: From Command to Choreography
The old model: Leaders directed specific actions and monitored execution.
The new reality: The best outcomes emerge from aligned autonomy.
When your team has AI-augmented capabilities, micromanagement becomes counterproductive. They can analyze, create, and implement faster than you can direct. Your job shifts from controlling their work to choreographing their efforts—setting the rhythm, maintaining alignment, ensuring the pieces fit together.
This shift requires:
Building feedback loops that catch misalignment early
Defining outcomes clearly while leaving methods flexible
Creating guardrails that enable speed without sacrificing quality
Teaching your team to teach AI to work in your organization's style
Shift 3: From Expertise Protection to Capability Distribution
The old model: Hoard specialized knowledge to maintain competitive advantage.
The new reality: Distribute capabilities rapidly or lose them entirely.
The finance director who won't share their Excel wizardry will soon be replaced by someone who teaches the team to prompt their way to the same insights. The marketing leader who guards their strategic frameworks will watch a competitor hire their junior analyst and scale those frameworks across an entire organization.
This shift requires:
Finding value in orchestration rather than monopolization
Teaching others to do what you do—before they learn it elsewhere
Building systems that scale your judgment, not just your knowledge
Accepting that your job security comes from making others more capable, not less
The Uncomfortable Truth About Staying Relevant
Here's what leaders struggle to accept:
Your edge isn't your accumulated knowledge
—it's your ability to help others accumulate knowledge faster.
Your value isn't your exclusive access to information
—it's your capacity to help others turn information into decisions.
Your authority isn't your position in the hierarchy
—it's your ability to help the hierarchy function better.
This doesn't diminish your expertise. It transforms it.
The senior engineer who teaches junior developers to prompt effectively creates more engineering capacity. The experienced consultant who shares their frameworks enables more strategic thinking. The veteran manager who distributes decision-making capabilities builds more resilient organizations.
But it requires letting go of the scarcity mindset that built your career.
Working with the AI Generation
Workers coming up in your organization don't think like you do about work.
Where you see process, they see obstacles. Where you see hierarchy, they see latency. Where you see risk, they see possibility.
This is less generational rebellion and more generational adaptation.
Today's workers are learning to work in a world where:
Any skill can be learned rapidly
Any boundary can be crossed digitally
Any question can be answered instantly
Any capability can be augmented immediately
Your job isn't to slow them down to your pace.
It's to help them move at their pace without losing what experience taught you about quality, relationships, and sustained performance.
The bridge between your experience and their capability is where leadership happens.
The Next Decade Question
Here's the question that keeps successful leaders awake:
Can I work another 5-20 years in a world that's changing this fast?
The answer depends on one thing: Whether you can evolve your leadership model as quickly as the tools evolve.
The leaders who thrive will be those who:
Build systems that scale wisdom, not just knowledge
Create value through orchestration rather than monopolization
Find meaning in distributed success rather than individual achievement
Help others become more capable instead of protecting their own capabilities
The leaders who struggle will be those who:
Cling to information scarcity as a source of power
Optimize for control rather than collective capability
Resist distributing capabilities for fear of becoming irrelevant
Define their value by what they withhold rather than what they enable
Your Choice, Right Now
The scapegoat mechanism will keep offering you an easy out: Blame the technology. Slow down the adoption. Return to familiar processes. Preserve the world where your experience provided the greatest advantage.
But that world is already gone.
You can't exile AI into the wilderness.
It's just going to keep reflecting, with greater clarity each quarter, the choice you make between protecting what was and building what could be.