What Our AI Predictions Reveal About Us (Simone Stolzoff, author of How To Not Know)

“Predictions tell us more about what we want and need in the present than what the future will look like.”

Futures often tell us what the present is afraid of, hungry for, or trying to sell.

That feels especially true in the AI conversation.

Most conversations about AI begin with prediction. Which jobs will go away? Which skills will matter? What will happen to education, to work, to young people, to the economy?

I understand the impulse. I feel it too. Prediction gives us the feeling of traction. It lets us imagine that if we can name the future clearly enough, we can prepare for it, protect ourselves from it, or maybe even control it.

But lately, I find myself less interested in whether any given AI prediction is right, and more interested in what the prediction is doing. What fear is it organizing? What market is it making? Who benefits if we accept that future as inevitable?

Simone Stolzoff has spent the last several years studying uncertainty: why we hate it, why we need it, and how to build a life without pretending the future is more knowable than it is. He is a two-time author, journalist, and former design lead at IDEO. His first book, The Good Enough Job, examined the role work plays in our identity. His new book, How To Not Know, makes him an especially useful guide for this moment.

Ursula K. Le Guin once argued that science fiction is not predictive so much as descriptive. The imagined future tells us more about the present than any ostensible future. I think the same is often true of AI forecasts. They may contain useful signals. But they also reveal what people fear, what they want, what they are trying to defend, and what they are trying to sell.

Simone’s point is that humans are prediction machines for a reason. Prediction helped us survive. When something rustled in the bushes, reducing uncertainty quickly was probably the right move. But in a moment like this one, our race to certainty can make us worse at seeing clearly. We choose the safe next thing too quickly. We mistake confidence for wisdom. We let people with economic stakes in a particular future tell us that it is inevitable.

For leaders, the question is how to guide institutions without pretending to know what cannot yet be known. What stays constant when everything feels unstable? What values, missions, obligations, or lines of work become the anchor?

For educators, the question is how to help young people build tolerance for uncertainty. Educators have to give students repeated practice with uncertainty: asking better questions, trying things before the answer is obvious, working through ambiguity, building from experience, and learning how to think when there is no single right answer.

And for all of us, the question is what purpose means in a world where the map keeps changing.

I’ve always thought of purpose less like an object we search for, find, and place on a pedestal forever, and more like a muscle we learn to build. We discover what gives us energy. We get better at something. We find problems worth solving. Then, over time, we learn how to apply that sense of meaning and motivation to new domains, new seasons, and new kinds of work.

I hope you enjoy this one.

Allison

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On How Uncertainty Unlocks Human Potential

ALLISON: What’s something you’ve changed your mind about in the past year?

SIMONE: When I started writing How Not To Know, I knew I wanted to write a book about the virtues of uncertainty. And in many ways, the book is that. But researching it and talking to experts in different fields has shown me that certainty is also very important. They’re both integral parts of a meaningful life.

When we are certain about some facets of our life, it makes it easier to hold uncertainty in others. We often hear the advice to embrace uncertainty—and it is, in some ways, the message of the book. But I believe phrases like that can also be gaslighting: uncertainty is incredibly uncomfortable by design. I’m trying to navigate the tension between seeing uncertainty as the birthplace of possibility—which I believe it can be—and not romanticizing precarity or insecurity. Uncertainty causes tremendous anguish too, and we need to treat it sensitively.

ALLISON: That insight reminds me of a term we use in education—the zone of proximal development. It’s a productive zone for learning because it’s neither comfortable nor alarming; learning can’t happen in a state of alarm. That means basic needs have to be met before learning can start. The zone of proximal development also requires a scaffold of safety to help you process uncertainty and apply it to your next best step. I think too many Americans lack that scaffolding, and consequently live with uncertainty as a toppling threat.

SIMONE: Definitely. One piece of advice I tend to give people in the midst of an interregnum or transition is to find the others in that space too. Find people who are maybe dealing with the same health scare, the prospect of retirement, or a recent layoff. Build the scaffold of support with them.

ALLISON: What do you think people most misunderstand about uncertainty?

SIMONE: For so many folks, uncertainty is a problem to be solved. We reach for certainty, even false certainty, because we want to rid uncertainty from our lives as quickly as possible. It’s rooted in our biology and how we experience fear. Imagine an ancestor hearing rustling in the bushes: they don’t know the source of that noise, and that uncertainty could be threatening. It could be lethal.

But if we always pick the fastest way out of uncertainty—the safe bet, the path of least resistance—we haven’t always made the optimal bet. I hope people can start to reframe uncertainty as the precursor to learning, growth, and new opportunities, if they are willing to sit with the fear and anxiety it will inevitably surface.

ALLISON: I’d love to hear a little bit about why you chose to write this book for this moment. Suppose the book really meets that moment: what would people, institutions, or leaders do differently?

SIMONE: It’s no secret that uncertainty is all around us right now, and there is data to support that perception. Nicholas Bloom, an economist at Stanford, has been tracking global uncertainty since the early 80s; he’s found that the five highest measurements since he began have all occurred in the last five years. Between the pandemic, wars overseas, tariff policies, and AI, we feel that the world is incredibly uncertain.

What’s less often talked about is that our tolerance for uncertainty is also declining, at both the individual and social level. Thanks to the internet and smartphones, we now hold the uncertainties of the world in our hands. We can see the real-time locations of our kids, and in the same half hour, track a war or crisis overseas. More information doesn’t necessarily lead to more wisdom—it often just fuels anxiety.

Phones also create the expectation that answers should be readily available. Ten years ago, I might have been okay not knowing the name of a given actor in conversation. Now, I have an almost involuntary need to reach for my phone to find it. Or we feel impelled to ask ChatGPT for answers to hard questions—a quiz problem, a career move, a relationship dilemma. But not all questions are answerable. And it’s hard to wrap our heads around that.

Here’s how I hope the book meets this moment: We often defer our dreams because its hard to tolerate the uncertainty they require us to experience. Here’s an example that isn’t in the book. In the early 2010s, there was a startup in the Bay Area called Tiny Spec, a massive multiplayer online game. It was the belle of the ball: it had raised 17 million dollars before launch, which was then covered in the New York Times.

But less than two years in, the founder had a sneaking suspicion that the company wasn’t on a sustainable path, despite its outward appearance of success. He did what everyone thought was insane and shut the company down, even offering to make his investors whole and helping employees who wanted to leave to do so. He pivoted to an entirely different product, monetizing an internal tool they had built for communication across offices. That tool is Slack, and that founder is Stuart Butterfield.

It’s not just an alls-well-that-ends-well story. Butterfield’s willingness to turn towards uncertainty allowed him to discover something that was greater than what he could have possibly dreamed beforehand.

For me, success for How Not To Know looks like more people willing to sit with uncertainty long enough to discover their potential—the global maxima rather than the local maxima. If we were all a little more comfortable with uncertainty, I think we’d see more people achieve their dreams, more communities come together across cultural differences, more innovation within organizations. And the world would be far more interesting.

ALLISON: What is the most entrenched obstacle to that vision?

SIMONE: Economic uncertainty—the fear of losing it all.

There’s data from the Great Resignation showing that people weren’t just leaving their jobs to sit on their couch; they were looking for better ones. In my opinion, the root cause of the Great Resignation was a collective confrontation with honor and mortality; faced with the prospect of death, people realigned their work around their values and what they wanted out of life. Unemployment insurance was also expanded during the pandemic, giving people more air cover. When we have that security, we can take risks and dream.

People cling to unfulfilling jobs because leaving puts their healthcare at risk. If you’re an immigrant, you’re risking your ability to stay in the country. Students avoid risks in making career choices for fear of failure—I studied both poetry and economics for exactly that reason. To become more tolerant of uncertainty as a society, we need structures that make it safer to do so.

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On What Today’s Predictions Can and Cannot Tell Us About A Future With AI

ALLISON: How do you understand the way our society is trying to process the uncertainty that AI is bringing to our lives? How are we collectively wrestling with this relatively new and emergent vector of uncertainty that feels so existential? What predictions are we making about our future with machines, and why?

SIMONE: The vector is definitely new, but our desire to predict the future is not. And in many ways this is certainty-seeking behavior. If we knew exactly what percentage of entry-level jobs will no longer exist in 2030, or how much GDP would be affected by AI, or what the most critical skills are, then we could plan, then we could feel safe and secure.

Our brains are essentially prediction machines, making inferences about what is to come so that we can survive. And yet, as a species, we are very bad at these predictions. The canonical example comes from Phil Tetlock, a professor at Penn who collected two decades of predictions from the smartest people in the world—economists, politicians, journalists—and compared them to what actually happened. His finding did not mince words: the average expert is roughly as accurate as a dart-throwing chimpanzee. That desire to know the future is an expression of our biological need for safety and security. But predictions tell us more about what we want and need in the present, rather than what the future will look like.

That’s why I’m wary of most AI predictions, particularly from people like AI executives who have a vested interest in the future looking a particular way. If you’re familiar with the parable of the Chinese farmer, you’ll understand my meaning: he describes no event in his life as either good or bad luck—from the loss of a horse to the finding of several others, to his son’s wounding in battle and eventual return—and when his neighbors say “what a tragedy” or “you’re so lucky,” his response is always simply, “maybe yes, maybe no.”

That’s how I feel about AI. It’s easy to feel certain about how the world will look and be pulled into pro-AI or anti-AI tribes. Maybe it will lead to a golden age of creativity; maybe it will lead to massive class warfare. Maybe yes, maybe no. It behooves us to plan for different contingencies without being too attached to any particular one.

ALLISON: Let’s talk about leadership, especially institutional leadership. States, governments, universities, school districts: leaders are rewarded for sounding certain, especially in times of crisis. AI is forcing a crisis, and panic is setting in across our society—among young people graduating college, people who fear their work will soon be automated, and communities where data centers are being planned and built.

How should leaders lead through this moment? What is your advice to them?

SIMONE: Leaders need to find their anchors. What do they hope will remain constant amidst change? That could be a set of values, a mission, serving a particular customer, preserving a process. I’ve been inspired by leaders willing to treat government more like a lab or innovation studio, and thus entertain a change of mind.

We also need leaders to trade hubris for humility, to admit what they don’t know and run experiments to find out. Mamdani does both well: I don’t agree with all of his politics, but he has a vision for what he’s fighting for, not just what he’s fighting against, and is willing to explore options beyond his initial policy platform.

We also need leaders who acknowledge the struggles of leadership and are more transparent about what it means to lead through transition. It’s not true that the most credible leaders are those who speak with the most conviction about the future—the research doesn’t bear that out. The most inspiring leaders are those willing to state what they know, what they don’t know, and how they plan to find out. That’s more credible than peddling a false sense of certainty.

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On How Anyone Can Learn How To Sit With Uncertainty

ALLISON: How should we prepare people of all ages, but especially young people, to thrive in an increasingly ambiguous future? You’ve referenced Elizabeth Gilbert’s framework distinguishing jobs, careers, hobbies, and vocations across your writing: perhaps start by telling me why this distinction is meaningful to you right now, especially as we think about preparing young people to build lives of stability and agency in this changing economy.

SIMONE: I love this framework for a couple of reasons.

One: We all need money, we all need a job. That might seem crass, but it’s also a way of de-romanticizing work as your only source of passion, vocation, or calling. At the end of the day, we just need to pay the rent. As I say in my first book, some people do what they love for work, while others do what they have to do so they can do what they love when they’re not working. I like it because it takes the pressure off young people in particular to find their one true calling.

Two: The data shows that people will have many different jobs—12 or more—over the course of their careers. Knowing that your next job isn’t necessarily your last lowers the stakes in a helpful way: it helps you treat your life and career more experimentally and provisionally. That’s an important, adaptive skill.

What I’d rather tell young people is to get good at something, then find out how you want to help people. Building skills and finding what impact means to you is far more actionable and attainable than the idea that you have to find a calling or follow your passion.

ALLISON: Purpose is certainly re-entering the conversation around the goals of high school and college, in large part because as AI changes entry-level roles to be less rules-based, we need more people who can drive their own learning, define their own problems, and marshal resources to solve them. That requires a level of agency and motivation often derived from purpose.

My view is aligned with yours, but I want to test it: rather than putting the burden on students to find their singular purpose, we should give them the opportunity to cultivate meaning and purpose around a set of problems they can then apply across different problem spaces over the course of their lives. I want purpose, meaning, and relevance cultivated in formal schooling at all levels—but not as a dogma that limits how students see their futures and themselves.

SIMONE: The important distinction there is that purpose is cultivated. The same is true with passion. Passion is often the result of hard work, getting good at something, or following your curiosity, not necessarily a precursor for doing any of the above.

Young people need faith in their ability to figure things out, and a willingness to try things, so that purpose, passion, or mission can emerge. They also need to know that these can and will evolve: you can have many different purposes across different realms of your life.

ALLISON: How should we teach or coach tolerance to uncertainty in school? And are there any strategies that you’ve seen really work?

SIMONE: Most importantly, educators can help increase students’ exposure to uncertainty without judgment. That looks like letting students wander around questions, admit they don’t know an answer, and rewarding sitting with ideas that challenge them. It enables exceptional learning: wisdom comes from asking questions without distinct right or wrong answers.

Like any phobia, tolerance is built through exposure, bit by bit. That might look like discussing a poem or an artwork, sparking a conversation with a classmate you don’t know, running true experiments, developing a prototype. The idea is to build confidence in uncertain situations and reward the risk that comes from trying different solutions or posing different hypotheses.

We all need these skills—mid-career professionals will have to reinvent themselves too. We have to be willing to run the test and figure things out in practice rather than in theory. That means doing the actual work and learning through experience. It’s the fastest way to develop uncertainty tolerance.

ALLISON: That’s such a great connection to the work we’ve done on what our field calls the experience gap. We have this provocation that 50% of formal learning should be experience based, precisely because of what you’re suggesting here. We think work will increasingly look less routine, less rules-based, less ready answers. It will require that everyone knows a methodology for figuring out the answer. That’s not what’s happening in formal schooling, even at elite levels.

Your view here is also aligned with our views on the future of assessment, and how we assess learning: you’re advocating that we should care more about someone’s process, rather than being hyper-focused on the output or the deliverable.

And so two ways that we might start teaching uncertainty tolerance would be to do more experiential learning, on the one hand, and to refocus assessment on how students think, rather than what they actually create.

SIMONE: Totally. The good news is it’s never been easier to be empowered to try things, to “come to the meeting with a prototype,” as we say at IDEO. That’s one of the great potentials of generative AI tools—anyone with an idea can make it tangible, and test it out in the market.

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One Small Signal

ALLISON: What’s a small signal to which we should be paying more attention?

SIMONE: I’m fascinated by the idea of cognitive time under tension. Like strength training for muscle development, our brains need time under tension. You have to sit and wrestle with ideas without opting out of that struggle. The allure of avoiding that tension with AI tools is real—I’m not immune to it myself. But the knowledge economy will need gymnasiums where we can put those muscles to work. Some startups are branding themselves as cognitive gyms, so attention is settling on this issue. But the ease with which we can opt out of thought is an existential threat requiring urgent, collective attention.

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