R3ciprocity.com - Prof David Maslach: Innovation; Research Life; Striving Towards Happiness

I’m going to say something that might sound extreme:

If we got rid of higher education as we know it—college, university, all of it—maybe we’d be better off.

Why?

Because most people don’t actually want to learn.

They don’t care. They’re checked out. And no message—no matter how true or kind—seems to land unless it’s already preaching to the choir.

And yet… I keep going.

Because I know this: real education moves the needle.

But only when people take it seriously.

Only when they do the hard work.

Only when they show up—again and again—even when it’s miserable, boring, thankless, and lonely.

I’ve lived it.

I’ve seen what this kind of work does to a life.

You don’t see it in the moment. You don’t feel it in your bank account.

But give it 10 or 20 years, and it changes everything—your class, your identity, your capacity to survive.

This episode is for the person who’s being laughed at right now.

For the person who’s grinding and feels invisible.

For the one who wants to quit because the gains feel too far away.

Keep going.

It’s supposed to be hard.

And yes, it feels stupid while you’re doing it.

But one day, someone will come up to you and say: “I wish I had done what you did.”

And that moment will be worth it.

We’re taught in school to look for a single best answer. One multiple-choice question. One correct option. Select A and move on.

But the real world never works like that.

Most of the time, the answer is never given to you.

Most of the time, you don’t even know what the question actually is.

In real life, the “answers” are never independent. They’re highly connected in weird ways. If you select A in the first question, the response in the second question might be B. Or D. Or something you didn’t expect at all.

And when you actually interact with the world, you realize you just don’t know. There isn’t a straight answer. There isn’t even a clear question. You have to piece together artifacts of this very complicated world and make sense of it yourself.

The central problem is this: people wait to be told the right answer.

But it’s not going to present itself that way.

You have to figure out what you’re even asking.

Then decide what you will call the correct choice based on what you see.

And the only way to build that skill is by pushing against the world. Saying “screw you” to the idea of a single right way. Doing something. Seeing what happens.

It’s always going to be a complicated interactive mess.

But you learn by doing. Not by waiting.

It’s not lost on me how wrong management theories often are.

I read a lot. And I know this sounds pretentious, but I’m confident enough now to say I’m one of the few people who actually studies platforms and builds one. The only reason I got here is because I’m building the Reciprocity platform with my own money, my own time, and all the embarrassment that goes with it.

And that’s why I see how disconnected management theory often is from the real world. We rarely capture what it feels like to actually build something — the shame, the failure, the stress, the weird looks, the feeling of being an outsider, and doing the “wrong thing” for years before anything works.

Nobody writes about how hard it is to get attention.

Nobody writes about being stuck in the middle — too practical for academia, too theoretical for builders.

Nobody writes about waking up, wasting money, screwing up, and getting back up again.

Students talk about innovation.

Big companies talk about innovation.

But almost nobody actually does it — because it’s humiliating, slow, lonely work.

The only reason I understand this now is because I was foolish enough to build something real. And once you do that, you realize how little our theories explain and how much of innovation is simply:

get up, feel the shame, try again.

Take care and have a wonderful day.

I built the most powerful research tool I have ever used — more impactful than AI. It lets you compare ideas, generate abstracts, and get instant feedback. I don’t know why researchers keep scrolling past it.

I keep hearing that academia is dying.

That we’re in an existential crisis.

That peer review is broken. That the system is collapsing.

And I get it.

I’ve been deeply concerned about parts of it, too—especially peer review. When it’s bad, it’s almost useless. But when it works, it’s beautiful. And hard.

Still, I don’t buy the narrative that we’re watching the death of the academic system.

Because one thing organizational theory teaches us—if we’re really paying attention—is that you can look at the same system in multiple ways. And when I step back and squint, academia starts to look like something much simpler:

A distributed network of smart people paid to think.

That’s it. That’s the whole thing.

Strip away the institutional formalities, the politics, the performative routines—and what we’re left with is still valuable. Because even if universities crumble or AI replaces traditional processes, there will still be demand for smart people solving hard problems.

And if the public systems fall apart? Private ones will emerge.

Will they be better? Maybe. Worse? Maybe.

But they’ll exist—because thinking has value.

In this episode, I explore why I’m not afraid of the supposed collapse of academia.

I’m actually kind of excited.

Because the system was never perfect.

And maybe what comes next could be even more alive.

Sometimes I’ll see a new bill passed or read a shocking headline—and my first reaction is the same as yours: “What the hell is happening to the world?”

I’ll get grumpy. I’ll vent to my wife. I’ll think, “This is dumb.”

But then I stop.

Because I’ve learned that we, as human beings, are terrible at making sense of complicated systems.

Even if something seems obviously harmful—or genuinely is harmful—it’s often impossible to know what the actual long-term effects will be. The systems we live in are too complex. You move one piece, and another shifts in a direction you never saw coming.

We teach this in business schools all the time. But we forget it when the world feels uncertain.

In this episode, I talk about why we get suckered into overreacting to things we barely understand. Why even smart people with lots of data still get it wrong. And why real change—like with climate tech—often comes from places we least expect.

I talk about China, capitalism, solar panels, and storms. But really, I’m talking about how hope still survives in complexity. And why stepping back doesn’t mean giving up—it just means seeing the system for what it is.

If you’ve felt overwhelmed by the news, this episode is for you.

Not because I’ll tell you what to think.

But because I’ll remind you that it’s okay not to know right away.

There is absolutely far too much hype around innovation.

I say that as someone who teaches innovation for a living and then tried to build something myself.

I have spent unbelievable amounts of time, effort, and money on the Reciprocity platform. And the great irony is that it was meant to help researchers in a field that talks nonstop about innovation. Yet when you look around, almost no one actually innovates. Not really.

At the beginning, I fell for the hype. I read all the good stories. I believed the models. But once you try to build something in the real world, you see how big the selection bias is. We only hear from the winners. Nobody counts the people who tried for a week or two and quit because they were crushed by the psychology of it.

The truth is this: most innovation is not technical. It is emotional.

You have to sit with your own failures. You have to feel like an outsider.

You have to speak into the darkness and hope someone even cares.

And you have to keep going when it feels like nobody does.

I misunderstood how hard that would be.

And I am still trying.

There is a lot of mystery and ambiguity around the career of a researcher or scientist, and the general public often gets it wrong. Reporters and commenters talk about science in a certain way, but when you are in it, you know it does not work that way at all. Different domains are very different in how they operate in the scientific way, and there is a lot of nuance that people never see.

What the public thinks we actually do is striking, and these misperceptions pass to policymakers and government analysts. Even popular science shows report things like the number of citations, but that is one of the most meaningless things in terms of what good science really is. More citations does not mean better science.

Good work needs depth, nuance, and looking at the world in a different way. There are big differences in scientific effort across fields. Some work is very good, and some is easy to see as not very good at all. You see it fast when you look at abstracts, even my 13-year-old could spot it.

People also think science is full of facts, but real facts are very hard to come by in a world with so much uncertainty. Science is probabilistic, complex, and never as clear as it looks. Better understanding of probability, science, and even financial literacy would help people understand it all a lot more.

We need more clarity about how science actually gets done, why ideas repeat, why norms develop, and why science is not the simple story most people imagine.

Is Business Strategy Just Luck, Privilege, and Repetition?

Over time, I have become increasingly cautious about what strategy truly means. I have spent much of my career studying it, teaching it, and trying to apply it. Yet the longer I engage with the topic, the more I have come to wonder whether we sometimes overstate what we can actually achieve.

Respecting the Tradition

It is important to acknowledge that the study of strategy has given us remarkable insights. The field has taught generations of scholars to think about positioning, competitive advantage, and the careful use of scarce resources. These ideas have shaped me deeply.

The narrative assumes that we can diagnose a situation, marshal our resources, and execute a well-chosen plan. Yet when one examines real world examples as it actually unfolds—in markets, in careers, in scientific discovery—the connection between deliberate planning and eventual success appears less direct to me.

The Invisible Forces: Luck and Social Position

Much of what we observe as performance may be better explained by forces that are rarely incorporated into our models of organizational life: luck and social position. Luck determines when and where one is born, who crosses one’s path, and which events unfold unexpectedly in one’s favor. Social position shapes access to information, status, and networks that magnify opportunity.

None of this invalidates the importance of strategy. It simply means that strategy often operates within constraints that are difficult to see and even harder to measure.

If luck and position matter so much, what remains within our control? The answer lies in gumption and humility, rather than perfect decision-making. The causes of success and failure are often intertwined.

In such a world, the most strategic capability may not be the ability to choose perfectly, but the ability to continue acting (gumption) when the outcomes are unclear. It is not brilliance, but endurance, or… stupidity.

The Engine of Performance: Gumption and Faith

I have grown to see persistence as the quiet foundation beneath every form of performance. Those who continue to show up, to be curious, and to believe that improvement is possible—despite repeated setbacks—often discover forms of success that were invisible.

To me, this does not diminish the value of strategy; it deepens it. It reminds us that deliberate planning must coexist with faith. Something we have known for all of humanity.

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The Humility to See Complexity

The traditional tools of strategy remain valuable, but they describe only one slice of a vast, open, and adaptive system. Recognizing this should not make us cynical—it should make us humble.

True strategic insight may not come from trying to control the world, but from patience, grace, and joy.

Strategy, at its core, is not about mastery.

It is about learning to move forward through muddy messes—again and again—while still believing that tomorrow can be brighter than today.

There is a lot of discussion about the validity of science right now.

Researchers talk endlessly about how to make results “more valid,” how to fix problems, and how to improve the system.

But here is what I actually think.

It is not about “bad apples.”

It is almost never about that.

The real issue is culture.

And culture often comes down to one or two people inside a community who stress performance above all else. Those one or two people create tension. They make others feel lesser than. They make you feel like you are the problem. And then everything starts to bend around that pressure.

This is true everywhere.

Every organization. Every department. Every field.

You can feel it when the conversation becomes only about outcomes:

number of citations, number of papers, number of grants.

All lagging indicators. All terrible predictors.

My field in strategy does this constantly.

It is completely wrong.

And it has been wrong for a long time.

A lot of this came from the old Jack-Welch-style management thinking of the 1980s. That mindset seeped everywhere. It made people believe outcomes were all that mattered. Just hit the number. Hit the target. Hit the metric.

But if you look at the research coming out of the systems-dynamics world at MIT — the Sterman group especially — the story is always the same:

When you focus on outcomes, everything erodes.

Eventually it all falls apart.

Because outcomes are not the thing that matters.

What matters is whether people feel safe.

What matters is whether people feel supported.

What matters is whether there is unconditional kindness in the room instead of fear.

You fix culture, you fix science.

And none of that starts with performance.