Talk to Strangers

Colgate-Palmolive couldn't figure out how to get fluoride powder into a toothpaste tube without it scattering everywhere. Its own chemists were stuck. The company did something that should have been absurd. It posted the problem to the open internet and offered a reward to anyone who could solve it.

Not consultants. Not a rival lab. Anyone, in any field, anywhere in the world, through a platform called InnoCentive, built by the drugmaker Eli Lilly for exactly this kind of problem.

A Canadian engineer named Ed Melcarek solved it. His answer was to put a positive charge on the powder and ground the tube, so the particles flew where they were sent, basic physics that Colgate's chemists had never thought to apply. He was paid twenty-five thousand dollars. He did not work at Colgate. No literature search, no recruiter, no one inside the company would ever have found him.

InnoCentive has run this thousands of times. Researchers studied 166 scientific problems from the labs of twenty-six companies, attempted by more than twelve thousand solvers. Roughly a third of the problems that had defeated experienced corporate scientists were solved by outsiders. One especially stubborn problem drew solutions from a carbohydrate researcher in Sweden, a retired aerospace engineer, and a veterinarian, not one of them in the field. And the further a solver's expertise sat from the field of the problem, the more likely they were to solve it.

Not as likely. More likely.

The Expert's Groove

This runs against the premise every organization is built on, that the person deepest in a domain is the one most able to solve its problems. The InnoCentive data says the reverse. The chemist working the chemistry problem carries a disadvantage the aerospace engineer does not.

The disadvantage has nothing to do with how much imagination the expert has. The expert has spent decades imagining inside the field, picturing how molecules will behave, running scenarios a novice couldn't follow. The trouble is direction. That imaginative power has been pointed one way for so long that it now runs in a single groove. Show the mind a new problem and it reaches for the pattern that solved the last one, and the answer forms before the question has been examined. This is the cognitive entrenchment described in What Gets Harder When AI Gets Better, the wall that expertise itself builds. The novice has no familiar pattern. The expert reaches before seeing the problem has changed.

The outsider has no groove. The aerospace engineer looking at a chemistry problem cannot route it through twenty years in the field, because there are no twenty years. There is only the problem and a set of instruments shaped by an entirely different world. The engineer's imagination builds what the specialist's can no longer build, the thing the field had trained its experts to stop seeing.

What Imagination Is Doing

When you picture something that isn't in front of you, a solution, a strategy, a conversation that hasn't happened, your brain runs a coordinated process across three networks. The default mode network builds the scene, stitching fragments of memory and knowledge into a plausible new construction. The executive control network evaluates what the default mode produces. Is this realistic? Useful? Worth pursuing? Between them, the salience network decides what deserves attention and when to hand control from free construction to hard evaluation. When the three cooperate, you can drift into an idea, test it, and move on it with confidence. When stress or fatigue or pressure knocks them out of sync, the construction either drifts without aim or shuts down before the idea takes shape.

When neuroscientists Eleanor Maguire and Demis Hassabis mapped this system, they confirmed that the regions the brain uses to remember the past are the same ones it uses to imagine the future. Memory isn't a recording. The hippocampus binds fragments of experience so the mind can recombine them, letting you walk through a remembered kitchen and an imagined boardroom with the same fluency. Imagination is memory turned toward what hasn't happened yet.

Roger Beaty and his colleagues found that highly imaginative people show stronger connectivity among these networks. Connectivity, like any pattern in the brain, rewires with use. Neuroscientists call this neuroplasticity, and it means the capacity is not a fixed trait handed out at birth. It strengthens through practice, the way a muscle strengthens.

The expert hasn't lost the capacity. The networks are intact. They've been running the same two jobs for so many years, planning the path and defending what works, that the third job, building what doesn't exist yet, has fallen out of practice. The stranger has no special talent for this. The stranger's networks simply aren't grooved on your problem, so they build freely where yours build on rails. The capacity rebuilds with practice. The only question is where the practice happens.

And With Whom

The earlier piece, What Gets Harder When AI Gets Better, ended right here, on the claim that the competence rebuilds with practice and not in the rooms that caused the atrophy. It left the harder question open. A reader answered it with an analogy. AI is like handing everyone the keys to an airplane with no flight training and no air traffic control. The training is individual capacity. Air traffic control is the collective frame. Most of the AI conversation treats the engine as the whole problem and skips the question of where we're flying, and with whom.

And with whom. That is the part that goes missing, and the InnoCentive results show that who's in the room decides everything.

Rebuilding imagination gets framed as a personal exercise. Protect time on the calendar. Ask a different question. Catch the dismissed idea before it leaves the room. All true, all necessary, and all of it still assumes the room is yours, your team, your industry, your building, the people who share your training, your blind spots, and your standing. That room is the problem the InnoCentive results expose. Put a group of experts from one field on a problem from that field, and the room runs in a single groove, multiplied by everyone sitting in it. The same pattern gets reached for around the table. The same thing gets missed. Conviction rises while the range of what anyone can picture stays exactly where it started.

The solo answer fails for the opposite reason. Thinking alone frees you from the room's shared blind spot but starves the imagination of the raw material other minds supply. The default mode network builds scenes out of what it has. Give it nothing new and it recombines the same fragments. Neither the room of your own people nor the desk by yourself is where the competence rebuilds.

The Two Things the Room Has to Do

What rebuilds the competence is a room that does two things at once, and they pull against each other. Range wants strangers. Safety, in most rooms, comes from people who already know you. Chase one and you lose the other.

The first is range. Minds from outside your field, whose imaginations run in grooves yours never cut, able to build the scene you have lost the ability to build. InnoCentive got this through distance, broadcasting one problem to thousands of strangers who never met. A room gets it through proximity, putting the outsider across the table from you. Either way the principle holds. The point is accuracy more than variety. The outsider is the one positioned to tell you the problem on the table is the wrong one.

The second is harder to build, and most rooms get it wrong. The room has to be safe enough that people will think out loud. Comfort is not the same thing. The safety has to be structural, where no one present can grade you.

Across decades, research on group idea generation has found that people produce fewer original ideas under evaluation, and the effect compounds when the evaluator holds power over them. The expectation alone is enough, with no one saying a word of criticism. Put a senior leader in a room with peers who will remember, reports who are watching, or a board that controls their future, and the salience network reads threat and hands control to the protective mode, the one built to defend what already works. The default mode network never gets to build. The generative work shuts down before the conversation starts. The leader performs certainty. They will not risk the unfinished thought. And the unfinished thought is the raw material imagination needs.

This is why the room that rebuilds imagination cannot be your own organization. Your organization is the one place you can least afford to be seen building badly on the way to building well.

A Room Built on Purpose

Pixar's Braintrust exists to take an unfinished film apart. Smart people in a room, finding everything wrong with work that isn't working yet. It functions because of two rules its founders made explicit. The people giving feedback hold no authority over the project, and the director can use all of it or none. And they never prescribe the fix. They name the problem and leave the solution where it belongs. Strip the authority out and honesty becomes possible. The moment feedback carries power, the threat response takes over and candor gives way to performance. The most senior people in the building could hear the hardest things about their work, because no one in the room held power over it. They credit the Braintrust with a run of films that doesn't happen by accident.

Pixar solves the safety half. The range half comes from rooms built across fields, the way InnoCentive built one across thousands. Put both halves together and you have the room imagination needs. Minds from outside your field, in a space where none of them can grade you. Range and safety, at the same time, on purpose.

That room is close to impossible to assemble for yourself. The calendar won't produce it. Your network mostly returns your own field. The people who would make it work are the ones you don't yet know, in industries you don't operate in, with no stake in your standing.

The Work That's Still Yours

What gets harder when AI gets better is the generative work — picturing what isn't there yet, deciding what deserves to exist, recognizing when the question itself is wrong. That work is imagination, the human competence this era demands. It rebuilds with practice, and the practice needs a room. The room that works is the one your instincts and your calendar will never build, because every instinct says to solve the problem with the people standing closest to it.

The leaders who rebuild this competence will stop trying to think their way out alone, and stop relying on the only room they already have. They'll go find the strangers. They'll make the space where no one can grade anyone. And they'll prove for themselves what the InnoCentive results have said all along, that the person who can finally picture your problem clearly is almost never the one who has been staring at it the longest.

Colgate's chemists stood closest to the problem. A stranger solved it with physics.

---

The Executive Imagination Lab on June 24 is built as that room. Twelve senior leaders from different industries, ninety minutes of protected space, the same idea worked through the lens of each one's work, with no one present who can grade anyone else.

What Gets Harder When AI Gets Better

In 1903 two teams were racing to achieve powered flight. One had a Congressional grant and the most powerful aircraft engine ever built. The other had a bicycle shop in Dayton, Ohio.

Samuel Langley, Secretary of the Smithsonian Institution, was the most credentialed aeronautical scientist of his era. A Congressional grant of $51,000 (roughly $1.9 million in today's dollars) funded his work on the Aerodrome, powered by a 125-pound, 53-horsepower gasoline engine designed with his assistant Charles Manly.

The Aerodrome was launched from a catapult atop a houseboat on the Potomac in October 1903. With news reporters watching, it promptly collapsed on itself and fell into the water. A second attempt on December 8 produced the same result. As Smithsonian Magazine recounts, the press was unsparing. The New York Times ran "Flying Machine Fiasco." The Washington Post called the craft "a total and admitted failure."

Less than ten days later, Wilbur and Orville Wright achieved sustained powered flight at Kitty Hawk. They had built the Flyer for about $1,000 (roughly $38,000 in today's dollars), funded from their bicycle shop in Dayton. They constructed a homemade wind tunnel and asked a different question. The unsolved problem was how a pilot would balance an aircraft against unstable air. Their three-axis control system is still the foundation of every aircraft built since.

Langley solved the wrong problem with extraordinary precision. The Wrights had spent years watching how birds held themselves steady in unstable air, and imagined a flying machine that could do the same.

AI is the Langley engine of this moment. It will optimize, model, and forecast at a power no leadership team has had before. It cannot tell anyone when the engine is pointed at the wrong problem.

Sixty percent of US CEOs say changing the business model is their top priority for boosting profitability this year (Conference Board). PwC's latest CEO survey adds two more numbers to the picture. Just thirty percent of CEOs are confident about revenue growth, the lowest reading in five years, and only twelve percent say AI has delivered both cost and revenue benefits. Pressure is up, conviction is down, and the space between them is what senior leaders are now being asked to close.

AI was supposed to close it. Three years after it moved to the top of every leadership agenda, the senior leaders who see what's getting harder are keeping it to themselves, and the conversation that could change the trajectory isn't happening.

What gets harder when AI gets better.

AI is consolidating the work senior leaders have excelled at for decades. What remains is the harder work of picturing what isn't there yet and deciding what deserves to exist. Most are out of practice.

The Reinvention Problem Is Not a Strategy Problem

Every offsite is a reinvention offsite now. The board has been explicit. Original strategy, original positioning, something a competitor hasn't considered. Several rounds in, with AI threaded into every transformation memo, the plan has become indistinguishable from what every competitor is producing. Sharper language, updated metrics, same trajectory.

The pattern shows up anywhere a senior leader is being asked for a move no one has made yet. It's the sixth version of the investor pitch the audience has already heard, the annual letter that could have been written by three peer foundations, the product roadmap that mirrors every competitor's, the marketing that reads like every other CMO's. Same outcome, different rooms.

CEOs know the model has to change but don't believe they're moving fast enough. PwC research finds the top third of companies that reinvented their business models outperformed industry peers by 71 percentage points on a combined measure of profit margin and revenue growth. The advantage isn't from better execution. The companies that fall behind tend to be the most disciplined of all, running playbooks with precision against a picture that no longer matches the terrain.

Two more signals never surface. The senior leaders the institution is counting on for the next move have started pulling back. They're still in their seats, but they've disengaged in a way that engagement surveys won't catch for six months. The one accountable for what comes next is sitting with an unsettled feeling. The instinct is to dismiss it. Not one of those offsites produced a move a competitor couldn't replicate.

The feeling is signal, running ahead of what the surveys and the market will eventually confirm.

AI is consolidating the cognitive work senior leaders have been rewarded for throughout their careers — pattern recognition, optimization, risk modeling, scenario planning, and forecasting. Machine learning now matches or exceeds human performance on most of it, and the consolidation is accelerating.

What's left is what AI cannot do. That work belongs to imagination as a competence. Sensing what's missing, choosing what to commit to, reading what the data can't show, recognizing whether the question on the table is even worth asking.

That cognition has been atrophying in senior leaders. The work AI now handles is the work the institution trained them to do, promoted them for doing well, and reinforced at every level of seniority.

AI is consolidating what the institution rewarded. The work that's left was never cultivated with the same intent.

The Atrophy Is the Diagnosis

This is not a willpower problem. It's how expertise works.

Erik Dane's 2010 paper in Academy of Management Review makes the mechanism specific. As people develop deep expertise in a domain, their thinking gets locked inside the schemas of that domain. Dane calls it cognitive entrenchment. Domain mastery produces inflexibility in problem-solving, adaptation, and creative idea generation. The deep specialization that makes a leader excellent at one way of thinking entrenches the schemas for that approach, while the ones not in use grow less accessible. The competence that built the authority becomes the wall against everything else.

What makes the entrenched expert's blind spot distinct is the confidence behind it. The novice gets stuck because nothing looks familiar. The entrenched expert gets stuck because everything does. A novel situation activates the schema that solved the last one, and the expert responds before examining the question.

This holds across fields. It holds for the partner who has won the same kind of case for fifteen years. It holds for the operator who has scaled the same playbook through three companies. It holds for the founder whose pattern recognition built the company and now blocks them from seeing what comes next.

Imagination is the competence this era demands. It operates in three modes. Navigational plans the path forward, optimizing, sequencing, and executing. Protective scans for threat and defends what's working. Generative pictures what doesn't exist yet and decides what deserves to exist. Same engine, different directions.

The first two modes work inside an accepted frame. Navigational asks how to get there. Protective asks what could go wrong on the way. Both presume the destination is correct. Generative interrogates the destination itself. It's the mode that tests whether the right question is on the table.

AI accelerates Navigational and supports Protective. Generative is beyond its reach.

Generative fades first under sustained pressure. The institutions that shaped most senior leaders rewarded the other two for years, anchored to quarterly cadences and risk dashboards, promoting careers built on optimization and never being wrong. The leader can still execute and still defend, but Generative has been crowded out by everything the other two demanded.

The muscle hasn't disappeared. Atrophy describes what happens when a competence stops being used. It rebuilds with practice, and the practice doesn't happen in the same rooms that caused the atrophy.

Recognition Before Practice

What rebuilds the muscle is small, deliberate practice on unfamiliar ground.

Recognition comes first. The leader who can name which mode is operating can change it. The one who only feels stuck can't. Most leadership failures right now come from running the wrong mode. The moment needed Generative, the room defaulted to Navigational, and no one had the framework to name what was happening.

The work after that is unglamorous. It looks like protected time on the calendar that isn't optimizing, defending, or executing. It looks like a different set of questions in the strategy session, the discipline of catching the dismissed idea before it leaves the room, and practice with other senior leaders sharpening the same question against different contexts. The muscle rebuilds faster when the thinking happens outside your own industry, your own habits, and your own defenses.

This is the work senior leadership now demands. None of it will show up in the metrics that get tracked.

Vision Isn't a Trait

The directive coming down is the same everywhere. Be more visionary. Bring more vision to the strategy. Help us see around the corners.

The ask is clear, but the muscle isn't there. Senior leaders take the note, sit down to do something with it, and find that nothing moves. Trying harder won't help. Vision is what imagination yields in Generative mode, the output of a competence that hasn't had reps.

What gets harder when AI gets better is the work that was always human, and was always the first to fade under pressure. Senior leaders who recognize this and rebuild the muscle will define what comes next. The ones who don't will keep optimizing what they're already doing — faster, against the same picture as everyone else.

The work that was always human is what imagination does. That's the work that's still yours.

---

The Executive Imagination Lab on June 9 brings twelve senior leaders into this question for ninety minutes — the same problem, worked from twelve vantage points, sharpened against each other.

The Default Script

You're good at your life. That's not the problem.

You hit the milestones ahead of schedule. You can articulate why you made every major decision, and the reasoning holds up. The degree led to the career. The career led to the house, the partner, the account balance that lets you sleep at night. People tell you you're doing well. You believe them. Most of the time.

But there's a thing that happens on a Sunday night, or in the car after a dinner party, or in the ten seconds after you close your laptop and before you pick up your phone. A gap. Not unhappiness. Something stranger. The sense that the life you built is working perfectly and that you can't remember when you last felt like it was yours.

You file it away. You're busy. The week resets.

That gap has a source.

What It Is

The Default Script is the set of assumptions about what a good life looks like that you absorbed before you had the language to question them. What counts as achievement. How fast it should happen. What a person your age, your education, your tax bracket is supposed to want next.

It wasn't written by anyone with bad intentions. It was written by people who loved you, cultures that shaped you, and systems that rewarded you for staying on the path. Get a degree or two. Find stable work. Build wealth. Settle somewhere respectable. Retire once you've earned the right to rest.

Most of us don't argue with the script. We don't even recognize it as a script. We think it's just how life works.

The claim here is specific, and it's more uncomfortable than it sounds. The Default Script didn't just hand you a path. It handed you your desires. You didn't just follow someone else's plan. You were trained to want it. The wanting itself was installed.

How It Happens

Three mechanisms. Each one is well-documented. And each one closes a door you probably assumed was still open.

You watched, and your brain took notes.

Psychologist Albert Bandura called it social learning. Before you ever made a decision about what kind of life to build, you'd spent years observing which choices got rewarded and which ones drew worry. You watched which adults seemed calm and which seemed afraid. You watched what happened to the cousin who went to law school and what happened to the one who moved to Austin to paint. Nobody sat you down and explained the rules. The rules were in the atmosphere. Your brain cataloged them before you knew it was keeping score.

By the time you're choosing a major or accepting a job, the architecture is already built. The options that feel "realistic" are the ones that match patterns you absorbed years ago. The ones that don't match feel risky, impractical, self-indulgent. Not because they are. Because the prediction machine classified them before you got to weigh in.

This closes the first escape hatch. "That's just how I was raised" isn't a neutral fact. It's a description of the installation process.

The first number became the only number.

Amos Tversky and Daniel Kahneman identified something they called anchoring bias. The first standard you encounter becomes the standard you measure everything against. Name a salary in a negotiation and the whole conversation orbits that number, no matter how arbitrary it was. The same thing happens with a life.

The first image of success you absorbed — your parents' version, your neighborhood's version, the version that showed up in every commencement speech you half-listened to — became the anchor. Everything since has been measured against it. Not because you evaluated and chose it. Because it got there first.

You might have updated the details. Swapped the corner office for a startup, the suburbs for the city, the retirement account for a different kind of retirement account. But the underlying shape — the metrics, the timeline, the definition of enough — those are the anchor's. You've been decorating someone else's blueprint and experiencing it as self-expression.

This closes the second escape hatch. "But I really do want this" is worth examining. You might. But the anchor got there before you did, and the brain doesn't distinguish well between a desire it chose and one it inherited.

The familiar became the true.

Psychologists call it cognitive ease. The brain prefers what requires less effort to process, and what you've rehearsed a thousand times requires almost no effort at all. Familiar options feel right. Familiar goals feel chosen. The path you've been on for fifteen years doesn't feel like a default. It feels like a conviction.

This is the mechanism that makes the script invisible. The brain files what's familiar under "just how things are." Questioning it requires a kind of cognitive expense the brain would rather not pay. So it doesn't. And the script keeps running, not because you examined it and agreed, but because examination never seemed necessary.

This closes the third escape hatch. "I've thought about it and I'm sure" may be true. But certainty that comes from familiarity feels identical to certainty that comes from honest evaluation. The brain doesn't flag the difference. It just files both under "mine."

The Question

The Default Script isn't the enemy. It kept you moving when you didn't have a direction of your own. It gave you a framework when you needed one. Every culture writes its own version, and not all of it is wrong.

But a borrowed pattern can't invent. It can only replicate. And at some point, the question stops being whether the life is working and starts being whether the life is yours.

Not what's next on the list. Not what looks right from the outside. Something prior to all of that.

Who first imagined this version of success for you?

Sit with it. Not to produce an answer by Friday. Just to notice what happens when you ask.

Theresa Stroisch is the author of The Imagination Age: Reclaiming Your Most Essential Competence.

Why I Wrote The Imagination Age

People ask me some version of the same question all the time. How did you get from Montana to New York. How did you end up at the Gates Foundation. How do you and Kevin figure out how to live in Southeast Asia for months at a time. The question changes but what they're really asking doesn't: how do you keep doing this?

For a long time I didn't have a good answer. I'd say something about being open to opportunity, or following curiosity, which was true but not useful. It didn't explain the actual mechanism. And I wanted to understand the mechanism — not just for the people asking, but for myself.

So I started researching. I spent months in the neuroscience and behavioral science literature, trying to understand what imagination actually is and how it works. Not imagination as metaphor. Not the word on a motivational poster. Imagination as cognition — something with structure, something the brain does in specific ways. And alongside the research, I kept returning to what I'd seen over twenty years — in boardrooms and team offsites and long dinners with friends across three continents. People who were smart, accomplished, capable — stuck. A leadership team circling the same three options quarter after quarter. A person who built exactly the life they planned and can't explain why it feels hollow. Not because anything was wrong with them. Because something had happened to their thinking and they didn't have a name for it.

What I found is that imagination isn't a personality trait. It's a competence. One that operates in distinct modes, each serving a different function — and each one can be developed or lost. That was also my answer. Every leap I'd made, every unlikely room I'd walked into — it hadn't been courage or luck. It had been imagination doing a specific kind of work.

And then, mid-draft, I watched Demis Hassabis on 60 Minutes. Hassabis is the CEO of Google DeepMind — and a neuroscientist whose doctoral research on memory and imagination was named one of the top ten scientific breakthroughs of the year. He has spent his career at the intersection of how the human brain works and what artificial intelligence can do. And he said, plainly, that imagination is the last thing AI can't replicate. Here was someone who understands both sides of that equation — the neuroscience and the machine — confirming what I was already writing. Imagination is the thing. The human thing.

This is a book about what imagination actually is, how it works, and what happens when we stop using it. If you've been asking how — this is my answer.