We all want to know what’s coming. It’s a survival mechanism. Whether you’re looking at the stock market, wondering if AI will take your job, or just trying to figure out if it’s going to rain during your outdoor wedding, humans are obsessed with the "next." But honestly? Most of us are terrible at it. We look at a straight line on a graph and assume it’ll just keep going up forever. It won’t.
Prediction isn't about having a crystal ball. It’s about probability. Experts like Philip Tetlock, who spent decades studying "superforecasters," found that the people who are actually good at this don't have magic powers; they just have a specific set of habits. They don't make grand, sweeping proclamations. They adjust their views constantly. If you want to learn a few rules for predicting the future, you have to start by admitting you’re probably biased, wrong, and overly emotional about the outcome.
The Base Rate is Your Best Friend
Think about a startup. Most founders think they’re the next Steve Jobs. They’ve got the vision. They’ve got the hustle. But if you look at the "base rate"—the statistical reality of how many startups actually succeed—the numbers are grim. About 90% fail.
If you're trying to predict if a specific company will survive, start with the 10% success rate. That’s your anchor. Don't move away from that number unless you have a very, very good reason. This is what's known as "outside view" thinking. Most people get trapped in the "inside view," focusing only on the specific details of their own project or situation. They ignore the history of everyone else who tried the same thing.
History doesn’t repeat, but it definitely rhymes. Mark Twain supposedly said that, and even if he didn't, the sentiment holds up. If you want to know how a housing bubble ends, don’t listen to the guy selling you a house. Look at how housing bubbles have ended every single time for the last 200 years. The data is right there. It’s boring. It’s math. But it works.
Forget the "Black Swan" and Watch the Trends
Nassim Taleb made the "Black Swan" famous—those totally unpredictable, high-impact events like the 2008 financial crisis or a global pandemic. You can't predict those. By definition, they are outliers. So stop trying.
Instead, look for "Grey Rhinos." Michele Wucker coined this term to describe highly probable, high-impact threats that we see coming but choose to ignore. Climate change is a Grey Rhino. The aging population in Japan and Italy is a Grey Rhino. These aren't surprises. They are slow-moving stampedes.
Why we miss the obvious
We miss them because they are uncomfortable. Or they move too slowly for a 24-hour news cycle. If something changes by 1% every year, nobody notices. But over 30 years? That’s a 30% shift. That’s a revolution.
When you're applying a few rules for predicting the future, look for the things that are already happening but haven't reached their logical conclusion yet. William Gibson, the sci-fi writer, famously said, "The future is already here—it's just not very evenly distributed." Look at the edges. Look at what the hackers, the weirdos, and the early adopters are doing today. In ten years, that's what your grandma will be doing.
Break Everything Down into Tiny Pieces
If you ask someone, "Will there be a war in the Middle East next year?" they’ll give you a "yes" or "no" based on their politics. That’s a useless prediction. It’s too big.
Superforecasters break big questions into "cluster" questions.
- Will there be a specific border skirmish by March?
- Will the price of Brent Crude oil cross $100?
- Will a specific treaty be signed or revoked?
By answering these smaller, more objective questions, you build a mosaic. You’re not guessing; you’re calculating. This is how the Intelligence Advanced Research Projects Activity (IARPA) changed how the US government looks at threats. They realized that small, frequent updates to a prediction are more valuable than one big "I think so."
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The Danger of the "Expert" Mindset
Here is a weird truth: famous experts are often worse at predicting the future than regular people who are well-informed.
Why? Because experts are often "hedgehogs." They know one big thing. They have one big theory about the world (e.g., "The economy is headed for a collapse" or "Technology solves everything"), and they try to fit every piece of news into that theory. They become blind to evidence that they’re wrong because their reputation depends on being right about their "One Big Idea."
The winners are "foxes." Foxes know many small things. They are skeptical of grand theories. They are happy to change their minds when the facts change. If you find yourself saying, "I've always believed X," you are in danger. To predict the future, you have to be willing to kill your darlings. You have to be okay with being "kinda" right and "sorta" wrong simultaneously.
The Feedback Loop
You need a scorecard. Most people make a prediction, it doesn't happen, and they just forget they ever made it. Or they say, "Well, I was almost right."
In the world of professional forecasting, that’s called "hindsight bias." You have to write it down.
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- What do I think will happen?
- What is the probability (0% to 100%)?
- Why do I think this?
- What would it take to change my mind?
If you don't track your "Brier Score"—a way of measuring how close your probabilistic predictions were to reality—you aren't forecasting. You're just venting.
Technology isn't a Straight Line
In the tech world, we love Moore's Law. We think everything gets twice as fast every two years. But physics eventually hits a wall.
When you're trying to figure out what a few rules for predicting the future look like in a tech context, remember the S-curve.
- The Beginning: Slow growth, lots of failure, high cost.
- The Middle: Explosive, exponential growth. This is where everyone gets rich and thinks it'll never end.
- The End: Maturity. Growth flattens out. The technology is "solved."
We are currently in the middle of the S-curve for AI, which is why everyone is panicking or overhyping. But look at smartphones. We’re at the top of the curve. The new iPhone is basically the same as the last one. Predicting the future of smartphones is now boring because the "future" happened ten years ago.
Actionable Steps for Better Forecasting
If you want to actually use this, don't just read about it. Change how you process information.
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Stop watching cable news. It’s designed to make you reactive and emotional. It focuses on the "now," which is almost always noise. Read long-form analysis. Look at data sets. Search for "counter-signals"—information that contradicts what you want to happen.
Think in ranges. Never say "The price will be $50." Say "There is a 70% chance the price will be between $45 and $55." This forces your brain to acknowledge uncertainty.
Update early, update often. If new data comes in, change your percentage. Don't be stubborn. Being "consistent" is for politicians. Being "accurate" is for people who want to actually understand the world.
Check your incentives. Are you predicting something because you want it to be true? If you own Bitcoin, you’re going to predict Bitcoin goes to a million. That’s not a prediction; it’s a prayer. Real forecasting requires you to step outside your own wallet and your own ego.
Find the feedback. Find a group of people who disagree with you and ask them why. Not to argue, but to see what they see. If you can’t argue the opposing side’s position as well as they can, you don’t actually understand the problem.
Start small. Predict something low-stakes, like the box office numbers for a movie or the outcome of a local election. Write down your percentage. Check it in three months. You’ll probably be humbled. And that humility is the first real step toward actually seeing what’s coming around the corner.