Trust and Discernment Are the Same Muscle
What the AI backlash reveals about presence, what it reveals about judgment, and what is happening inside the founders who are leading through it.
The conversation about AI has gotten very loud. So far, in that conversation aspects about the human experience in the AI era have gotten a bit lost.
The Event Horizon is a letter built for founders who want to look clearly at what AI is actually doing—to our work, our thinking, our identity, and our businesses—and lead from that clarity rather than react from the noise.
We’re not here to chase the tools or debate the hype. We’re here to figure out what it means to stay human while building something powerful—and to do that work together, week by week.
Human lead. AI empowered. Always.
Welcome back to The Event Horizon—where we look at what AI is becoming, what it’s asking of us, and what becomes possible when humans stay in the lead! 🌅
The same day I had a woman tell me how she has an AI that keeps on top of her grocery shopping for her (it knows the ongoing list, keeps track of what she’s using and not using, loads her online cart, makes the purchase for delivery after her review and approval 🤯), I read research showing that more than three-quarters of Americans—a whopping 82%, in fact—responded to unrelated studies about AI recently expressing that they feel forced to choose between a fast decision and an informed one, while simultaneously saying they doesn’t trust AI-made decisions.
So this week starts with a number that’s hard to look away from:
71% of Americans now believe AI is moving too fast, and only 18% would trust it to make a decision for them. This is according to an Economist/YouGov poll released in May.
(Can you guess which camp I’m in? Stay tuned, and it will become clear.)
I think those numbers are the visible half of a story that’s also unfolding inside the founders building with AI every day—the same erosion, showing up in two places at once.
I’d like to talk a bit more about that, so let’s see where the signal leads…
📡 The Signal
So what’s happening in the AI landscape right now?
Almost three-quarters of the population of the US say AI advancement is moving too fast, and 81% don’t trust it to make decisions for them. At the same time, despite this overwhelmingly anxious sentiment, Americans are using AI more and more in their daily lives.
The use of AI search and chatbots (think Google Gemini, ChatGPT, Copilot, and Claude) alone is up—49% of Americans use them every day, according to Pew Research Center—while the overall outlook on AI remains quite pessimistic. As I write this letter, more Americans than not expect AI will have a wholly negative impact on society, and particularly on the economy, in the long-term.
The pattern, though counter-intuitive, is clear:
Adoption is rising fast
AND
Trust and optimism are declining faster still.
In a Computer Weekly article from February of this year, the signs were already starting to show. A quote from Tyler Johnston, executive director of The Midas Project (an AI watchdog group), shares the predominant perspective:
“It’s not clear if [AI] technology will, on net, benefit everyday people or disempower them.”
All this and the technology is still in its infancy, really… But isn’t that how it’s always been? A new technology comes into our reality, turns everything on its head, and people swear it’s the end of the world as we know it. And usually they’re right. But more on that in a bit.
What the data is actually revealing isn’t outright rejection of AI’s capability, but rather the public at large is rejecting something else entirely.
As Brian Solis observed in his article on Medium in June, “The AI Backlash is Really a Crisis of Trust and Agency,” “ the revolt against AI isn’t just fear of technology. It’s fear of losing agency.” And I believe he’s right. People aren’t afraid of the technology in and of itself as much as they are afraid of a future they feel they can’t choose for themselves.
Because the conversation around AI is no longer just about the technology and its advancement. It’s also about how it advances, who decides that, and what that will mean for society at large.
For months, I’ve been saying to anyone who will talk with me about it that while the possibilities of AI are truly staggering to think about, the technology is moving so fast that individuals, particular segments and communities, as well as whole industries, will find that they cannot process the changes happening in real time, nevermind fast enough to feel like they have any control.
And Solis addresses this as well, saying “ When people feel they have no voice in the systems reshaping their lives, resistance becomes rational.”
So here’s a question for the founders reading this, and thinking, “Hey, I use AI every day. I got this. No problem.” ...if your audience is part of that 71% who distrust AI and by default AI-driven companies, how will their relationship to your “AI-powered” language change? Because it likely already has, whether you’ve noticed or not.
Here’s a stronger question, and one that includes you in its scope: if the backlash surrounding AI isn’t really about capability, what is it about—and what does that mean for what a founder actually needs to protect?
🪨 First Principles
The Backlash Is a Referendum on Consent
My personal position, and in turn the position of SPS, has always been that AI belongs working on the mundane and repetitive so human energy stays where it’s irreplaceable—the creative, strategic, relational work only a founder can do. The data in this week’s issue turns that principle from an integrity stance into a competitive market mechanism: visible human presence has become the offer’s actual credibility layer, the thing the market is now pricing, whether founders have realized it or not.
The stakes intensify when you add the distinction between analysis and judgment.
AI performs analysis extraordinarily well—it is a pattern recognition machine, literally. But judgment is a different kind of thing altogether. It integrates context, values, relationships, history, and consequence, and those collectively fall into distinctly human capacity territory.
And this is the exact fault line the backlash discussed above traces.
A founder who lets AI absorb judgment-adjacent decisions, even efficiently, even with good intentions, is handing over precisely the thing the public has just said it doesn’t trust anyone to hand over invisibly. The backlash and booing (did you see that video?) of AI names something specific—people resisting being decided-about without their knowledge or consent.
This pervasive stance reframes what a founder needs to protect.
It was never really about how much AI a founder uses. It’s about how visible and consensual the judgment layer stays for the people on the other end of it. This is where genuine discernment and the expertise built by standing in the work long enough to know its terrain live.
Trust is a scarce resource, and an infrastructure built on top of judgment, context, and insight that only your experience can provide is the competitive moat, as well as the strategic differentiator, for any founder looking to scale and sustain in the next decade and beyond.
I would argue that’s always been the only moat that matters—and maintains. AI has simply sharpened that understanding.
And here’s the harder part—the test the public is applying to founders from the outside is exactly what’s being eroded by founders on the inside, one deferred decision at a time.
🫀 The Human Layer
The Same Test, Applied From the Inside
In the last issue of The Event Horizon, we talked about cognitive sovereignty—the idea that people should retain control over their own thinking—their attention, judgement, memory, and decisions—and avoid environments that would steal and steer it manipulatively or coercively.
But what happens when that environment is your own internal landscape, and you find yourself second-guessing your own thoughts and conclusions because an AI says something different?
That’s the layer of this trust and agency dilemma that’s not getting talked about much yet. There is, however, a growing body of research on leaders who rely on AI for decision-making, and one definitive pattern is emerging: the more people defer to AI’s read of the terrain, the more they begin to doubt their own, even when they know they disagree with the machine’s output.
Without protecting what only a human can do—the very discernment you earned through years of building your expertise and banking your experience, this dilemma becomes so much bigger than just about making a values compromise.
It means you are actively building on ground that’s actively eroding right out from under you. As discussed above, AI is a pattern recognition analyzing machine. And in the absence of your patterns (discernment and insight) to analyze, it will pull data from somewhere else it can (the aggregate) to create the necessary output. It doesn’t care. It can’t because it’s not human. It only operates to get whatever job it’s been given done.
Remember that line a few minutes ago—that when a new technology turns everything on its head, the people who call it the end of the world as they know it are usually right? Let’s shift gears for a moment (bear with me, I promise it will be worth the payoff).
I want to tell you a little story.
It’s the early 1900’s and you are a professional horse and buggy driver. Picture it: you’ve spent your entire life mastering this mode of transportation. You know how to read a horse’s mood, mend a wheel, judge exactly how far you can travel before your horse needs water. You’ve spent your savings on the best rig money can buy.
Then the automobile arrives.
For a while, roads hold both—your horse and buggy right alongside cars, each convinced the other is the passing fad. And for a while, you’re right. You get where you’re going, and a certain percentage of society still relies on you for getting where they need to go, same as always.
Then the world starts to change right before your very eyes.
The roads get repaved for tires instead of hooves. Gas stations replace feeding troughs. Insurance, traffic law, city planning—all of it rewritten for cars. The world’s infrastructure moves, and the driver who was right for years—you—is suddenly standing on ground that no longer holds you up. Your skill is exactly as sharp as it’s ever been, and the ground simply changed shape underneath it.
That’s the moment worth sitting inside right now.
AI is the new roads being poured under our feet: what clients expect, what “good” looks like, what a competitor can now accomplish, all shifting at once.
And it’s fair to grieve the expertise built for terrain that’s disappearing, even while you build for the terrain replacing it.
So how do you marry the deep body of expertise and experience that you have amassed over the years with the sheer power of this world-changing technology?
First of all, know that what made you great at your job for years, is still what separates you from the crowd now. Just with some slight upgrades to your task and execution. What shapes AI to your will rather than being led by it is operational expertise that you can give to the AI so its filter is your judgement. This requires you to codify your judgment.
What does it mean to codify your judgment?
Putting your expertise and systematized decision-making frameworks in an instructional form AI can read, use, and craft output through. This is how the founders who are using AI and winning are in fact getting those results. This is the edge you need over AI—to stay present, to stay the discerning factor of your AI’s output, and to stay the human in the lead of this revolutionary moment.
Years in the work aren’t a sunk cost—they’re the raw material of the discernment this moment actually requires. The moat was always judgment, not task execution, and it stays intact only if you apply it to guide AI rather than defer to it or refuse it outright.
🌅 Light on the Horizon
The Same Test, Passed
A Vaccine Component Designed by AI Just Completed Its First Human Trials
Researchers at the University of Cambridge used AI to design a vaccine component that has now completed its initial human trials—an early, uncertain stage of medical discovery that AI is uniquely built to help with.
It processed a scale of molecular possibility no human research team could hold in their heads, while the clinical judgment, trial design, and safety oversight stayed exactly where they belonged: in human hands.
This is the “AI on pattern recognition, human on judgment” argument playing out at its highest possible stakes—AI expanding what’s discoverable while the decisions that actually matter to a patient’s safety never left human hands. (Note: this comes from secondary reporting on the Cambridge research, not a primary source—worth a quick verify before you quote specifics.) Source
Struggle First, Consult Second: What New Research Says About AI and Critical Thinking
New research covered by Science News found something worth reflecting on: people who worked through a problem on their own before consulting an AI chatbot performed measurably better on critical thinking tasks than those who consulted the chatbot first.
The sequence of when you consult AI relative to your own effort appears to determine whether it sharpens your thinking or dulls it.
It’s the research behind this issue’s Understory practice, “Before You Defer”—so if you want the evidence before you try the tool, this is where it lives. Source
Small Business Owners Are Using AI to Extend Their Expertise
2026 reporting on small business owners found the same pattern playing out at ordinary scale: owners using AI tools like ad variant testing and cash-flow summaries to extend genuine expertise, compressing a week of routine work into an afternoon so their actual specialty gets more attention.
No enterprise-scale drama here, just a workable version of “codify your judgment,” happening at exactly the scale most of us are building at. Source
🎯 Your Move
Pick one place in your business right now where AI is producing something on your behalf—an email sequence, a proposal, a piece of content.
Now, ask yourself plainly: is my judgment actually shaping this, or has the machine started making the call on its own?
Name one thing only your years of experience would know to include, and make sure it’s there before that piece goes out. That’s part of the “codifying your judgment” process, and what it looks like in practice: one decision, reclaimed, this week.
🌀 The Ecosystem Pulse
Before you go—one honest question: Did this issue nourish something?
Reply with a single letter and let me know how this one feels for you:
A—Yes, I feel more aligned
B—I’m still sitting with it
C—This one didn’t connect
Every signal strengthens the ecosystem. Thank you for being part of it.
🧭 Constellation Compass
🌌Elsewhere in the Sitting Pretty Strategies constellation recently:
🗺️In this issue of Elegant Email Ecosystems, I made the case that voice and visibility multiply rather than add—and introduced the Four Anchors framework for locating the note before you worry about the room. [Read E3 #028 →]
📍In this issue of Pretty Strategic, I made the structural case for coherence as an AI-era indexing requirement—and why the founders who built foundation-first are the only ones a recommendation engine can surface with confidence. [Read PS #039 here ➔]
🌱 In the inaugural issue of The Master Work, I sat with the question of whether the life underneath a business is one the body can actually live inside, and the crossroads of protecting the health of what you’re building versus the health of the person running it. [Read TMW #001 →]
🔮 Inbox Alchemy is the lab side of SPS—this is where the ideas across these letters get turned into practice through a sequential, evergreen email experience. [Join the lab →]
📡 Signal Back
This week’s question:
When was the last time AI’s read on something didn’t match your gut—and what did you do with that gap?
I’d genuinely love to hear where you landed, and what it told you about how much room you’re currently giving your own judgment.
If this issue resonated with you, I have four small asks:
① Hit the ❤️—It takes one second and tells Substack this conversation is worth having.
② Hit the 🔄 restack—It puts this in front of your followers—the ones who are already building differently and don’t yet know there’s a name for what they’re doing.
③ Share this issue with a founder you know who could benefit, and might even think you’re their hero. 🦸
④ Drop a comment—I read every one. And I reply. Some of my best thinking happens in response to what you bring to the conversation here—and future issues often start in a comment thread.
💡The right idea finds the right person at the right time. You might be the one who gets it there.
🌿 The Understory
What you just read is the argument. What follows is the work.
What comes next was built for The Understory—and it goes where this issue has been pointing all along: into the practice of protecting the judgment you just spent this issue making the case for.
This week’s Understory is two things. A Self-Assessment: “Where Are You on the Spectrum?”—a short calibration tool for locating yourself somewhere between full deference and full resistance, so you know exactly where your own tuning currently sits. And a Practice Protocol: “Before You Defer”—one concrete pause-and-check practice for the moment AI’s read disagrees with your own, so the years you’ve spent building your judgment keep doing their job.
And at the close—a brief, honest note on how I used AI to write this issue. This is a standing section in every The Event Horizon Understory, because my position on AI is simple and steady: use the tools, stay in the loop—stay in the lead. Those ideas are not in conflict, and The Understory is built on exactly that premise.
Let’s get to work.
For everyone reading from The Canopy: this is what The Understory looks like. Join us in the deeper work.
