After nearly eight years of the Love Your Work podcast, I’m quitting. Here’s why, and What’s Next.

This is not the immediate reason I’m quitting, but it is at the root: Podcasting is a bad business. When the indirect benefits of an activity run out, it’s hard to keep doing it if it’s not making money.

I realized long ago podcasting is a bad business, but I kept going for other reasons. I’ll explain why in a bit.

Though I didn’t start my podcast with dollar signs in my eyes, I did at least hope I would grow to earn money doing it. I’ve earned about $32,000 in the eight-year history of Love Your Work. More than half of that has been from Patreon supporters, many of whom support for reasons other than the podcast.

During that time, I’ve spent:

In raw numbers, I’ve made a “profit” on the podcast. But, as I broke down in my latest income report, my “wage” was about $6 an hour. My podcast comprised about 5% of my income over these eight years, and took much more than that portion of my time and energy.

Of course, I don’t think about whether the podcast was worth it in terms of an hourly rate. Creative work happens in Extremistan, not Mediocristan, and I’ve made massive life choices to be free to explore creatively without worrying so much what I’m earning in the short-term.

But there are many different ways to make a podcast a solid business, and none of them worked for me, for various reasons.

Here are some of these business models, as they apply to the “thought-leader” space (I’ll ignore the more entertainment/infotainment space that podcasts like Gimlet’s inhabit).

I flirted with success in a few of these business models. Early on, I hoped my podcast would be famous enough to pick and choose advertisers at high rates. For a while, it looked like I had a chance. I was approached by a podcast network, and I had some reputable advertisers such as LinkedIn, Skillshare, Casper, Audible, Pittney Bowes, and University of California. Various times, I thought I was on the cusp of my “big break” – such as when Love Your Work was featured on the Apple Podcasts home screen.

But the more I tried to go the “get famous” route, the louder the siren-song of the “content machine” route got. There were plenty of opportunities to do “interview swaps” with hosts I wasn’t interested in interviewing. There were a few advertisers that had money, but whose products felt sleazy. Joining a podcast network would have pressured me to crank out content even if I didn’t feel like it. There was (and still is) the never-ending stream of pitch emails for guests. I had too much wax in my ears to go the “content machine” route.

Not included in my lifetime revenue-estimates for Love Your Work is money I made through the “back-end business” route. I was somewhat comfortable with this model, but I haven’t made a course in years, as I’ve been focused on writing books. And as bad a business as people say writing books is, it’s better than making a podcast.

The podcast has helped me sell books in more ways than one. One way is that people who listened to the podcast bought my books. The other way is, making my podcast helped me write my books.

This brings me to the reason I kept making my podcast, even after I realized it wasn’t a good business.

In my sixteen years experimenting with different business models as an independent creator, I’ve settled on one thing that works: Make for what making makes you.

If making a podcast, writing a book, sending a weekly newsletter – you name it – merely makes you money, and doesn’t make you who you want to be, what’s the point?

Sure, sometimes you don’t feel like creating, and you do it anyway. Yes, sometimes you pick one project over another because you think it will be more lucrative. But you can only redirect the river that is your creativity so much before it overflows and returns to its natural path.

When I started Love Your Work, and was struggling to make it big enough to work with an ad model, even if I wasn’t bringing in lots of ad revenue, I was still connecting with and learning from my guests. It was an incredible privilege to have in-depth conversations with people like Seth Godin, Elise Bauer, and David Allen. It was like having my own personal advisory board of heroes.

Talking to them helped me learn how to go off the beaten path and find my calling. I was able to find patterns in their stories that I could apply to my own life and career. I would be a completely different person today if I hadn’t had those conversations.

But there came a point when doing interviews was no longer serving me the way it once had. It was when I had gained the confidence – thanks to my previous guests – to explore further my own ideas.

That’s when I stopped interviewing guests, so I’d have more time to explore. Love Your Work shifted from my personal advisory board to my personal sounding board – a sort of “open mic,” where I fleshed out ideas. I got to see how it felt to effortfully explore each idea. I got to hear how they sounded when I read them aloud. I got to feel how they resonated (or didn’t) with others.

A couple years after I started Love Your Work, I started writing a book called Getting Art Done. Getting Art Done turned out to be three books, two of which I’ve published. Love Your Work has been there to help me explore the ideas in these books. The Heart to Start was full of conversations from my early guests, and came from my very real struggles in gaining the confidence to take my ideas seriously enough to pursue them. Mind Management, Not Time Management came from my very real struggles to harness my creative energy and push my ideas forward.

As I work on the final book in the Getting Art Done trilogy, Finish What Matters, I’m asking myself, What struggle does this book come from? Clearly, I’ve finished a lot of creative work: three books, over two-hundred consecutive weekly newsletters, and over three-hundred episodes of this podcast. But as I’ve dwelt on that final word in the title, matters, I’m asking myself if I’m really working on what matters?

Love Your Work and Getting Art Done have been an exploration in creative productivity. But at some point, writing about Resistance becomes a form of Resistance. I don’t feel I’ve reached that point yet, but I don’t want to. If I’m going to learn enough to write Finish What Matters, I have to really test my ideas of what matters.

I’ve probably explored enough ideas, through Love Your Work, that I want to develop further in Finish What Matters. But for the time being, I need space to explore what matters. That’s the biggest reason I’m quitting Love Your Work. I had considered doing so in the past, but I kept hoping I’d know What’s Next before I quit. I’ve come to realize that I can’t know What’s Next until I have the space to explore.

It’s a little scary to have that void. But it’s also exciting. Furthermore, I’ve faced The Void many times before: when I started on my own, after finishing each book, and a little bit after each podcast episode or newsletter. What’s scarier now than facing the void is that I’ll stick with what’s safe, and distract myself into dying with my best creations inside me.

I could just say I’m taking a break, or not say anything at all and stop until I felt inspired to make a new episode. I’ve talked before about how I struggle to burn my boats and close doors. So, I’m calling it quits, knowing I could always drop another episode in the feed down the line if I wanted to. But I hope I find something that matters more, before that ever happens.

Thank you for listening to Love Your Work. Thank you especially to my Patreon supporters, who can of course feel free to stop supporting, or keep supporting for the bonus content, and to support What’s Next. To learn What’s Next once I find it, be sure to subscribe to my newsletter at kdv.co.

One last time, thank you. Thank you, thank you, thank you.

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You’ve probably heard that, in a blind taste test, even experts can’t tell between white and red wine. Even if this were true – and it’s not – it wouldn’t matter.

I was in Rome last month, visiting some Raphael paintings to research my next book, and stopped by the Sistine Chapel.

I’ve spent a good amount of time studying what Michelangelo painted on that ceiling. There are lots of high-resolution images on Wikipedia.

But seeing a picture is nothing like the experience of seeing the Sistine Chapel. You’ve invested thousands of dollars and spent fifteen hours on planes. You’re jet-lagged and your feet ache from walking 20,000 steps. You’re hot.

When you enter, guards order you to keep moving, so you won’t block the door. They corral you to the center, and you can finally look up.

When you hear wine experts can’t tell between white and red wine, you imagine the following: Professional sommeliers are blindfolded, and directed to taste two wines. They then make an informed guess which is white, and which is red. In this imaginary scenario, they get it right half the time – as well as if they had flipped a coin.

If it were true wine experts couldn’t tell between white and red wine, the implication would be that the experience of tasting wine is separate from other aspects of the wine. That the color, the shape of the glass, the bottle, the label, and even the price of the wine are all insignificant. That they all distract from the only thing that matters: the taste of the wine.

There’s some psychophysiological trigger that gets pulled when you tilt your head back. Maybe it stimulates your pituitary gland. When you have your head back and are taking in the images on the Sistine Chapel ceiling, you feel vulnerable. (You literally are vulnerable. You can’t see what’s going on around you. You’d be easy to physically attack.)

What you see is overwhelming. As you try to focus your attention on some detail, some other portion of the imagery calls out and redirects your attention. This happens again and again.

After a while, your neck needs a rest, and you return your gaze to eye-level. And this is almost as cool as the ceiling: You see other people with their heads back, their eyes wide, mouths agape, hands on hearts, tears in eyes. You hear languages and see faces from all over the world. You realize they all, too, have invested thousands of dollars and spent fifteen hours on planes. They, too, are jet-lagged and hot and have walked 20,000 steps.

You can look at pictures of the Sistine Chapel ceiling on the internet. You can experience it in VR. In many ways, this is better than going to the Sistine Chapel. You can take as much time as you want, and look as close as you want. You don’t have to spend thousands of dollars and fifteen hours on a plane, take time off work, or even crane back your neck.

But seeing the Sistine Chapel ceiling on the internet or even VR is only better than seeing it in person, in the way that a spoonful of granulated sugar when you’re starving is better than a hypothetical burger in another iteration of the multiverse.

We’ve seen an explosion of AI capabilities in recent months. That has a lot of people worried about what it means to be a creator. Why do we need humans to write, for example, if ChatGPT can write?

The reason ChatGPT’s writing is impressive is the same reason there’s still a place for things created by humans.

Anyone old enough to have been on the internet in the heyday of America Online in the 1990s will remember this: When you were in a chat room, most the conversations were about being in a chat room: How long have you been on the internet? Isn’t the internet cool? What other chat rooms do you like? Part of the appeal of the question “ASL?” – Age, Sex, Location? – was marveling over the fact you were chatting in real-time with a stranger several states away.

Or maybe you remember when Uber or Lyft first came to your town. For the first year or two, likely every conversation you had with a driver was about how long they had been driving, about how quickly the service had grown in your town, which is better – Uber or Lyft?, or which nearby cities got which services first.

The first few months ChatGPT was out, it was seemingly the only thing anyone on the internet talked about. But it wasn’t because ChatGPT’s writing was amazing. ChatGPT is a bad writer’s idea of a good writer. It was because of the story: Wow, my computer is writing!

Now that much of the novelty of ChatGPT has worn off, many of us are falling into the Trough of Disillusionment on the Gartner Hype Cycle. We’re realizing ChatGPT is like a talking dog: It’s impressive the dog can appear to talk, but it’s not talking – it’s just saying the words it’s been taught. ChatGPT is very useful in some situations, but not as many as we had originally hoped.

What made us talk about the internet while on the internet, talk about Uber while in Ubers, and talk about ChatGPT while chatting with ChatGPT was the story. Once the story behind the internet or Uber wore off, we started to appreciate them for their own utility.

Part of what’s cool about seeing the Sistine Chapel ceiling in VR is that – we’re seeing it in VR. But even if that weren’t impressive, what would still be impressive about the paintings would be more than just that they’re amazing paintings. It’s incredible to us a human could paint such a massive expanse. We think about the stories and myths of Michelangelo, up on that scaffolding, painting in isolation. Part of our appreciation of the Sistine Chapel ceiling lies outside the ceiling itself. While marveling at it, we can’t help but think of Michelangelo’s other masterpieces, such as the David or the Pietà.

Lloyd Richards spent fourteen years writing Stone Maidens, and had almost no sales for decades. Suddenly, he sold 65,000 copies in a month. He was interviewed on the TODAY show, and got a book deal with a major publisher.

How did he do it? His daughter made a TikTok account. The first video showed Lloyd at his desk, and explained what a good dad he was, how hard he had worked on Stone Maidens, and how great it would be if he made some sales. Then the #BookTok community did the rest.

Stone Maidens is apparently a good book. But it’s no better today than it was all those years it didn’t sell. Most the comments on Lloyd’s TikTok account – which now has over 400,000 followers – aren’t about what a great book Stone Maidens is. They’re about how Lloyd seems like such a nice guy, or how excited each commenter is to have contributed to his success.

The study that started the myth that wine experts can’t taste the difference between white and red wine didn’t show that. The participants in the study literally weren’t allowed to describe the two wines the same way – they couldn’t use the same word for one as the other. It wasn’t blindfolded – it was a white wine versus the same wine, dyed red. The study wasn’t about taste at all: Participants weren’t allowed to taste the wine – they were only allowed to smell. And wine experts? That depends on your definition of “expert”. They were undergraduate students, studying wine. They knew more than most of us, but were far from the top echelon of wine professionals. Most damning for this myth was that the same study casually mentions doing an informal blind test: The success rate of their participants in distinguishing the taste of white versus red wine: 70%.

That this myth is false shouldn’t detract from the point that even if it were true, it wouldn’t matter. What the authors of this study found was not that wine enthusiasts couldn’t tell between white and red wine, but that the appearance of a wine as white or red shaped their perceptions of the smell of the wine.

Once you bake a cake, you can’t turn it back into flour, sugar, butter, and eggs. You can’t extract the taste of a wine from the color, the bottle, your mental image of where the grapes were grown and how the wine was made, or even the occasion for which you bought the wine. Something made by an AI can be awesome, either because it’s really good at doing what it’s supposed to, or because you appreciate it was made by an AI. Something made by a human is often awesome because of the story of the human who made it, and the story you as a human live as you interact with it.

If you want to be relevant in the age of AI, learn how to bake your story into the product. Because AI can’t bake.

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We trust the food we eat, the drinks we drink, and the air we breathe are safe. That in case they’re unsafe, someone is working to minimize our exposure, or at least tell us the risks. In The Triumph of Doubt, former head of OSHA David Michaels reveals how companies fight for their rights to sell harmful products, expose workers to health hazards, and pollute the environment. They do it by manufacturing so-called “science.” Most this science is built not upon proving they’re not causing harm, but by doing whatever they can to cast doubt. Here, in my own words, is a summary of The Triumph of Doubt: Dark Money and the Science of Deception.

Chances are you’ve cooked on a pan coated with Teflon. Teflon is one of many polyfluoroalkyl substances, or PFAS. When introduced in the 1940s, they were considered safe. We now know they’re linked with high cholesterol, poor immune function, cancer, obesity, birth defects, and low fertility. PFAS, it turns out, have such a long half-life, they’re called “forever chemicals.” PFAS can now be found in the blood of virtually all residents of the United States, and have been found in unsafe levels worldwide – in rainwater.

You’ve probably heard that, in moderation, alcohol is actually good for you. But even one drink a day leads to higher overall mortality risk. More than one drink, greater risk of cardiovascular disease and cancer. Alcohol is a causal factor in 5% of deaths worldwide – about 3 million a year. 13.5% of deaths between ages 20–39 are alcohol-related.

If you’re in pain after an injury or surgery, your doctor might prescribe for you an opioid. But the rise in opioid addiction is responsible for the first drop in U.S. life expectancy in more than two decades. It’s sent shockwaves throughout society. It’s helped launch the epidemics of fentanyl and heroin overdoses, and the number of children in foster care in West Virginia, for example, rose 42% in four years.

You might love to watch professional football. But NFL players are nineteen times more likely to develop neurological disorders, and thirty percent could develop Alzheimer’s or dementia from taking so many hits.

How have they done it? How have companies been able to manufacture and sell products that cause so much harm, for so long? They do it by defending their products, when the safety of those products are questioned. On the surface, that’s not so bad. But besides lying and deliberately deceiving, they abuse society’s trust in so-called “science,” and our lack of understanding of how much we risk when we move forward while still in doubt.

There’s an entire industry that helps companies defend their products from regulation: It’s called, appropriately, product defense. The tobacco industry is most-known for its product defense. In 1953, John W. Hill of the PR firm Hill & Knowlton convinced the tobacco industry to start – one floor below his office in the Empire State Building – the Tobacco Industry Research Committee (TIRC). The TIRC was supposed to do rigorous scientific research to understand the health effects of smoking, but mostly they just attacked existing science, doing what they could to sow doubt.

Just a few years earlier, in 1950, a study had found heavy smokers were fifty times as likely as nonsmokers to get lung cancer. With the help of the TIRC, it would take a long time for these health risks to influence public policy. About thirty years later, most states had restricted smoking in some public places such as auditoriums and government buildings.

Smoking had proliferated in American culture when cigarettes had been provided in soldiers’ rations in WWI. Michaels describes one surgeon who, in 1919, made sure not to miss an autopsy of a man who had died of lung cancer, because it was the chance of a lifetime. He didn’t see another case of lung cancer for seventeen years, then saw eight within six months. All eight had started smoking while serving in the war.

Today, more than a century after cigarettes were widely introduced, we’ve finally seen a massive reduction in smoking in the U.S. We can fly on planes and go to restaurants and even bars, without being exposed to secondhand smoke.

Predating the product defense efforts of the tobacco industry is actually the sugar industry. The Sugar Research Foundation was started in 1943. Scientific evidence first linked sugar with heart disease in the 1950s. In 1967, as Dr. Robert Lustig told us, Harvard scientists published in the New England Journal of Medicine an article blaming fat rather than sugar for heart disease. Fifty years later UCSF researchers discovered the scientists had been funded by the Sugar Research Foundation – which they hadn’t disclosed. Even more misleadingly, they had disclosed funding that actually made them look more impartial – from the dairy industry.

The Sugar Research Foundation and the Tobacco Industry Research Committee are are early examples of “astroturfing” organizations. This tactic of the product defense industry involves setting up organizations with innocent- or even charitable-sounding names, then doing low-quality research to defend a company or industry’s interests.

Astroturfing organizations are funded by so-called “Dark Money”. In other words, they do whatever they can to hide where their funding comes from, lest their biases become obvious.

Besides private foundations, straight-up lying, and routing money through a federal foundation, another way of keeping money “dark” is by taking advantage of attorney-client privilege. By having the law firm pay accomplices, even if there’s a lawsuit, the documents are private.

When corporations do get studies published about the risks of using their products, they’re often low-quality studies. If they don’t deliberately conceal their findings, they often use their connections to create what are essentially pseudo-events to prop up their flawed conclusions.

The papers that do get published by the product-defense industry are usually not original studies. They’re often reanalysis of existing data. Industry takes advantage of the Shelby Amendment, which the tobacco industry promoted under the guise of concern over pollution.

The Shelby Amendment requires federally-funded researchers to share any data they collect. In this way, industry can reanalyze the data in ways that arrive at any conclusion they want. So, “re-analysis” has its own cottage industry within product defense. When industry does conduct original studies, they don’t have to share their data, and so it isn’t subject to the same scrutiny.

The Triumph of Doubt goes on and on with examples of deception and collusion from various industries. Some other highlights:

There’s a concept called the precautionary principle. It states that when we know little about what the consequences of an action will be, we should err on the side of caution. If a new chemical is developed, we should wait before we let it get into our food and water. If a new technology is invented, we should wait until we introduce it to society.

In criminal courts, a defendant is innocent until proven guilty beyond a reasonable doubt. We like this, because we hate the idea of someone being thrown in jail despite being innocent. And we can physically remove someone dangerous from society and more or less stop them from continuing to harm others.

But this is also our policy for chemicals, drugs, and potentially dangerous activities. We have an extremely high bar for deciding something is harmful enough we should reduce our exposure to it. OSHA – the Occupational Safety and Health Administration – has exposure limits for only 500 of the many thousands of chemicals used in commerce. Because the regulatory process is so onerous, Michaels says, in the half-century OSHA has been around, they’ve updated only twenty-seven of those 500.

Yet, as with PFAS, even after we start reducing our exposure, the effects of harmful substances keep going. As one Stockholm University scientist has said about PFAS in rainwater, “We just have to wait…decades to centuries.” And, unlike a criminal court, where the only people motivated to keep from punishing a defendant are the defendant’s lawyers and family members, huge networks of people stand to profit from harmful products – executives, shareholders, and entire industries have the incentives to conspire and collude.

On the other hand, the precautionary principle can slow or halt innovation. Many products that may be harmful may also be useful. Teflon and other PFAS have a huge number of applications. Supposedly it’s been replaced by other chemicals in cookware – though they’re probably similar (taking advantage of loopholes in the slow regulatory process). Supposedly exposure potential from cooking is low – but you know now how hard it is to “trust the science.”

As horrifying as some of these abuses of science are, you can’t be horrified by them without at least some sympathy for those who didn’t want to get the COVID vaccine: If a product is immediately harmful to everyone who takes it, that’s easy to prove. But could it harm some people in the long term? It’s nearly impossible to be sure. There’s more money and power behind sowing reasonable doubt than behind exposing sources of harm. Meanwhile, it’s easy to sow and abuse the existence of doubt, and that’s why it’s the main tactic used in product defense.

If you liked this summary, you’ll probably like The Triumph of Doubt. As a career regulator, Michaels comes off as somewhat biased, clearly partisan at times, a little shrill with his use of dramatic terms such as “Big Tobacco” and “Big Sugar.” Get ready for lots of alphabet soup, as you try to keep track of the myriad agencies and foundations identified by acronyms.

Because of media’s key role in the doubt-sowing Michaels writes about, I’ll be adding this as an honorable mention on my best media books list.

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According to philosopher Isaiah Berlin, people think in one of two different ways: They’re either hedgehogs, or foxes. If you think like a hedgehog, you’ll be more successful as a communicator. If you think like a fox, you’ll be more accurate.

In Isaiah Berlin’s 1953 essay, “The Hedgehog and the Fox,” he quotes the ancient Greek poet, Archilochus:

The fox knows many things, but the hedgehog knows one thing.

Berlin describes this as “one of the deepest differences which divide writers and thinkers, and, it may be, human beings in general.”

According to Berlin, hedgehogs relate everything to a single central vision. Foxes pursue many ends, often unrelated or even contradictory.

If you’re a hedgehog, you explain the world through a focused belief or area of expertise. Maybe you’re a chemist, and you see everything as chemical reactions. Maybe you’re highly religious, and everything is “God’s will.”

If you’re a fox, you explain the world through a variety of lenses. You may try on conflicting beliefs for size, or use your knowledge in a wide variety of fields to understand the world. You explain things as From this perspective, X. But on the other hand, Y. It’s also worth considering Z.

Even though this dichotomy Berlin presented has spread far and wide, his essay is mostly about Leo Tolstoy, and the tension between his fox-like tendencies and hedgehog-like aspirations. In Tolstoy’s War and Peace, he writes:

In historic events the so-called great men are labels giving names to events, and like labels they have but the smallest connection with the event itself. Every act of theirs, which appears to them an act of their own will, is in an historical sense involuntary and is related to the whole course of history and predestined from eternity.

In War and Peace, Tolstoy presents characters who act as if they have control over the events of history. In Tolstoy’s view, the events that make history are too complex to be controlled. Extending this theory outside historical events, Tolstoy also writes:

When an apple has ripened and falls, why does it fall? Because of its attraction to the earth, because its stalk withers, because it is dried by the sun, because it grows heavier, because the wind shakes it, or because the boy standing below wants to eat it? Nothing is the cause. All this is only the coincidence of conditions in which all vital organic and elemental events occur.

Is Tolstoy a fox, or a hedgehog? He acknowledges the complexity with which various events are linked – which is very fox-like. But he also seems convinced these events are so integrated with one another that nothing can change them. They’re “predetermined” – a “coincidence of conditions.”

A true hedgehog might have a simple explanation, such as that gravity caused the apple to fall. Tolstoy loved concrete facts and causes, such as the pull of gravity, yet still yearned to find some universal law that could be used to predict the future.

According to Berlin:

It is not merely that the fox knows many things. The fox accepts that he can only know many things and that the unity of reality must escape his grasp.

And this was Tolstoy’s downfall. Early in his life, he presented profound insights about the world through novels such as War and Peace and Anna Karenina. That was very fox-like. Later in his life, he struggled to condense his deep knowledge about the world and human behavior into overarching theories about moral and ethical issues. As Berlin once wrote to a friend, Tolstoy was “a fox who terribly believed in hedgehogs and wished to vivisect himself into one.”

Other thinkers Berlin classifies as foxes include Aristotle, Goethe, and Shakespeare. Other thinkers Berlin classifies as hedgehogs include Dante, Dostoevsky, and Plato.

What does knowing many things have to do with actual foxes? What does knowing one big thing have to do with actual hedgehogs? A fox is nimble and clever. It can run fast, climb trees, dig holes, swim across rivers, stalk prey, or hide from predators. A hedgehog mostly relies upon its ability to roll into a ball and ward off intruders.

What are the consequences of being a fox or a hedgehog? According to Phil Tetlock, foxes are better at telling the future, while hedgehogs get more credit for telling the future.

In Tetlock’s 2005 book, Expert Political Judgement, he shared his findings from forecasting tournaments he held in the 1980s and 90s. Experts made 30,000 predictions about political events such as wars, economic growth, and election results. Then Tetlock tracked the performances of those predictions.

What he found led to the U.S. intelligence community holding forecasting tournaments, tracking more than one million forecasts. Tetlock’s own Good Judgement Project won the forecasting tournament, outperforming even intelligence analysts with access to classified data.

These forecasting tournaments have shown that whether someone can make accurate predictions about the future doesn’t depend upon their field of expertise, their status within the field, their political affiliation, or philosophical beliefs. It doesn’t matter if you’re a political scientist, a journalist, a historian, or have experience implementing policies. As the intelligence community’s forecasting tournaments have shown, it doesn’t even matter if you have access to classified information.

What matters is your style of reasoning: Foxes make more accurate predictions than hedgehogs.

Across the board, experts were barely better than chance at predicting what would or wouldn’t happen. Will a new tax plan spur or slow the economy? Will the Cold War end? Will Iran run a nuclear test? Generally, it didn’t matter if they were an economist, an expert on the Soviet Union, or a political scientist. That didn’t guarantee they’d be better than chance at predicting what would happen. What did matter is whether they thought like a fox.

Foxes are skeptical of grand schemes – the sort of “theories of everything” Tolstoy had hoped to construct. They didn’t see predicting events as a top-down, deductive process. They saw it as a bottom-up, inductive process – stitching together diverse and conflicting sources of information.

Foxes were curious and open-minded. They didn’t go with the tribe. A liberal fox would be more open to thinking the Cold War could have gone on longer with a second Carter administration. A conservative fox would be more open to believing the Cold War could have ended just as quickly under Carter as it did under Reagan.

Foxes were less prone to hindsight bias – less likely to remember their inaccurate predictions as accurate. They were less prone to the bias of cognitive conservatism – maintaining their beliefs after making an inaccurate prediction. As one fox said:

Whenever I start to feel certain I am right… a little voice inside tells me to start worrying. —A “fox”

As for inaccurate predictions, one simple test tracked with whether an expert made accurate predictions: a Google search. If an expert was more famous – as evinced by having more results show up on Google when searching their name – they tended to be less accurate.

Think about the talking-head people that get called onto MSNBC or Fox News (pun, albeit inaccurate, not intended) to make quick comments on the economy, wars, and elections – those people. Experts who made more media appearances, and got more gigs consulting with governments and businesses, were actually less accurate at making predictions than their colleagues who were toiling in obscurity. And these experts who were more successful – in terms of media appearances and consulting gigs – also tended to be hedgehogs.

Hedgehogs see making predictions as a top-down deductive process. They’re more likely to make sweeping generalizations. They take the “one big thing” they know – say, being an expert on the Soviet Union – and view everything through that lens. Even if it’s to explain something in other domains.

Hedgehogs are more-biased about the world, and about themselves. They were more likely than foxes to remember inaccurate predictions they had made, as accurate. They were more likely to remember as inaccurate, predictions their opponents made that were accurate. Rather than change their beliefs, when presented with challenging evidence hedgehog’s beliefs got stronger.

It’s tempting to take that and run with it: The close-minded hedgehogs of the world are inaccurate. Success doesn’t track with skill. Tetlock is careful to caution that hedgehogs aren’t always worse than foxes at telling the future. Also, there are good reasons to be overconfident in predictions. As one hedgehog political pundit wrote to Tetlock:

You play a publish-or-perish game run by the rules of social science…. You are under the misapprehension that I play the same game. I don’t. I fight to preserve my reputation in a cutthroat adversarial culture. I woo dumb-ass reporters who want glib sound bites. —“Hedgehog” political pundit

A hedgehog has a lot to gain from making bold predictions and being right, and nobody holds them accountable when they’re wrong. But according to Tetlock, nothing in the data indicates hedgehogs and foxes are equally good forecasters who merely have different tastes for under- and over-prediction. As Tetlock says:

Quantitative and qualitative methods converge on a common conclusion: foxes have better judgement than hedgehogs. —Phil Tetlock, Expert Political Judgement

As bad as hedgehogs look now, there are some real benefits to hedgehogs. They’re more-focused. They don’t get as distracted when a situation is ambiguous. So, hedgehogs are more decisive. They’re harder to manipulate in a negotiation, and more willing to make controversial decisions that could make enemies. And that confidence can help them lead others.

Overall, hedgehogs are better at getting their messages heard. Given the mechanics of media today, that means the messages we hear from either side of the political spectrum are those of the hedgehogs. Hedgehog thinking makes better sound bites, satisfies the human desire for clarity and certainty, and is easier for algorithms to categorize and distribute. The medium is the message, and nuance is cut out of the messages by the characteristics of the mediums. Which increases polarization.

But, there is hope for the foxes. While the media landscape is still dominated by hedgehog messages that work as social media clips, there are more channels with more room for intellectually-honest discourse: blogs, podcasts, and books. And if many a ChatGPT conversation is any indication, the algorithms may get more sophisticated and remind us, “it’s important to consider….”

If you’re a hedgehog, you’re lucky: What you have to say has a better chance of being heard. But it will have a better chance of being correct if you think like a fox once in a while: consider different angles, and assume you’re wrong.

If you’re a fox, you have your work cut out for you: You may have important – and accurate – things to say, but they have less a chance of being heard. Your message will travel farther if you think like a hedgehog once in a while: assume you’re right, cut out the asides, and say it with confidence.

Image: Fox in the Reeds by Ohara Koson

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Many creators and aspiring creators struggle not because they don’t have enough ideas, but because they have too many. Their situations, in summary, are “Too many ideas, must pick one.” Embedded in this belief are assumptions that, if challenged, can help you feel as if you have just enough ideas.

In my recent AMA, I got a question I’m asked about creativity, probably more than any other:

How can you pick a creative project when you have too many ideas?

I’ve experienced, “too many ideas, must pick one,” many times. I still often do. I of course answered this question in the AMA, but here I’ll answer more in-depth. This is the thought process I guide myself through when I’m in the land of “too many ideas, must pick one.”

There are three assumptions embedded in, “too many ideas, must pick one.”

Let’s look at each of those.

If you feel you have too many ideas, you must think they’re equally likely to succeed, which is the first assumption. That might not sound correct at first, but think about it. If you were starving, and only allowed to eat one of various sandwiches, you would probably pick the biggest and most calorie-rich.

You might not be able to tell so easily which is the biggest and most calorie-rich sandwich. In fact, there may be other factors that play into your decision. Maybe the avocado and pork belly sandwich is the most calorie-rich, but you’re craving roasted duck in this moment, and there happens to be a roasted-duck sandwich amongst the selections.

While satisfying your hunger is one objective of choosing a sandwich, there are other goals in mind, such as satisfying cravings, which may compete with one another. If you have a hard time deciding amongst all the sandwiches, you expect eating one sandwich to be equally likely to succeed as eating any of the others.

As with projects, “success” may come in many forms. We’ll get to that in a bit.

If you feel you have too many ideas, you must think you’re equally capable of succeeding at each of these ideas, which is the second assumption. If assumption one weren’t correct, and you didn’t feel each idea were equally likely to succeed, you would probably pick the one most likely to succeed. The avocado and pork belly sandwich would clearly be more filling than peanut butter and jelly.

Now, if you weren’t equally capable of eating each of the sandwiches, that would make your decision easier. If you’re choosing between avocado and pork belly and peanut butter and jelly, but you’re a strict vegetarian, the decision is easy. Same if you’re not a vegetarian, but allergic to peanuts.

But since you feel each idea is equally likely to succeed, and you feel you’re equally capable of succeeding at all of them, you feel you have too many ideas.

As with projects, you may have little information about your capability of succeeding, which is why, for all you know, your capability to succeed is equal across all ideas. We’ll untangle that later.

If you feel you have “too many ideas,” you feel they’re equally likely to succeed and you’re equally capable of succeeding at each of them. If you feel you “must pick one,” you feel you can’t work on multiple ideas at once, which is the third assumption.

In our sandwich scenario, you’ve been told you have to pick one sandwich. If there’s no one else around and the sandwiches will go to waste otherwise, you might as well taste all the sandwiches, then pick one. Or eat a little of each, until you’re full. But, in that case, you wouldn’t finish any of the sandwiches.

With all three of these assumptions, you’re in a deadlock. Your ideas are equally likely to succeed, you’re equally capable of succeeding at each, and you must pick one. Well, how can you pick one if they’re all equally appealing ideas?

There are five questions that can help you challenge these assumptions:

Let’s look at each of these.

Success can come in many forms. Maybe you want to make the most money possible. Maybe you want the most freedom possible. Maybe you want to do what you’re most passionate about.

You may feel each idea is equally likely to succeed, because each idea is likely to get a different kind of success. One sandwich will fill you up, another will taste great, still another seems like the healthy choice.

If you have a clearer picture of what forms of success are more important to you than others, your many ideas will no longer be “equally likely to succeed.”

Not only can success come in many forms, it can come with various risk profiles. One idea may have a big chance of bringing you mild success. Another idea may have a small chance of bringing you wild success. The overall expected value of each idea may be the same, but the risk profiles may be very different. Some are sure bets, some are wildcards.

There are also various things you may risk in pursuing an idea. Mostly, what I call “TOM” – Time, Optionality, and Money. If you are young, healthy, and with no commitments, you have a lot of Optionality, but you might not have much Money. Making enough Money to live may take up much of your day-to-day Time. You can try a crazy idea, so long as it doesn’t take up too much Time and Money. If you fail, you’ll still have plenty of Optionality.

Or, you might want to make some changes that reduce your Optionality, but free up your Time. For example, I live in South America, which limits my options for anything requiring physical presence, but it has reduced my need for Money, thus freeing up my Time.

On the other hand, you may be in your sixties, retired after a successful career. You have plenty of Money and Time, but less Optionality than when you were in your twenties. You can only take on so many big projects in the rest of your life, and you may not have the energy you used to. But, you may feel you have nothing to lose by trying a wild idea.

If you have a clearer picture of what your risk profile is, not all your ideas will seem “equally likely to succeed.”

Even if all your ideas seem equally likely to fit your definition of success and fit your risk profile, you’re probably better at some things than others.

If you have a clear picture of what you’re good at, the assumption that you’re “equally capable of succeeding at each of these ideas” will no longer make sense.

It may be that you don’t know what you’re good at, likely because you don’t feel you have information to tell you what you’re good at. You probably have more information available than you think. Think about times in the past when someone was impressed with or complimented you on something you did, which came to you naturally. Or, ask your friends what they think you’re good at.

If you really don’t have information on what you’re good at, relative to your many ideas, then the third assumption, “I can’t work on multiple ideas at once,” no longer makes sense. In this case, you can and should work on multiple ideas, to get an idea what you’re good at. If you feel your ideas are too big to work on more than one, scale them back into smaller ideas. Don’t fall for “The Fortress Fallacy,” like I talked about in The Heart to Start. Instead of building a fortress, try building a cottage.

It’s important to remember that what you’re good at is not necessarily what you’re best at, nor what you most enjoy. This will make more sense as we answer the last two questions that challenge the three assumptions.

In reality, you probably don’t have a clear picture of how likely all your ideas are to succeed, nor how capable you are of succeeding at each. You have to ask of each, What’s necessary to succeed?

What’s necessary to succeed at an idea is usually very different from what attracts you to the idea in the first place. You may love to play music. You may even love to play music in front of an audience. But will you love driving around the country, sleeping in a van, lugging gear, and dealing with curmudgeonly AV techs at each venue? You may love the idea of signing books for adoring fans at the local Barnes & Noble. But will you love sitting in a room by yourself, writing several hours a day?

It’s worth noting that what most people in a domain think is necessary to succeed may not be. Lots can change in the industry, and changes in the mechanics of media can open up opportunities to succeed without doing some things that were once necessary. For example, thanks to self-publishing, I don’t have to write boring book proposals or get countless rejection letters to succeed as an author.

You may be really good at what’s necessary to succeed at an idea that has a good chance of meeting your definition of success. But there may be some things necessary to succeed that you don’t enjoy. That doesn’t mean you shouldn’t pursue the idea.

No matter what you do, there will be some parts of it you aren’t crazy about – especially at first. When I was a kid, all I wanted to do was draw. But making a living at drawing as an adult doesn’t fit my risk profile, and what’s necessary to succeed would interfere with parts of my definition of success: I can’t travel if I have to lug around supplies and artwork, and if I do all my work on a computer, then I’m chained to a computer.

I didn’t used to like to write, but I found out I’m reasonably good at it. Forcing myself to write each morning was painful at first, but through building a writing habit, it’s transformed into a strangely enjoyable sort of pain.

Additionally, there are parts of making a living writing that I don’t like, or at least didn’t at first. My first one-star review shook me for days, but now I can brush them off relatively quickly. Same with angry emails from readers. I used to really hate bookkeeping, but now that I write monthly income reports, I actually look forward to tallying up my earnings.

After all this, you may realize you don’t have “too many ideas,” and you don’t really have to “pick one.” If you don’t feel you have enough information to form a clear picture of the odds of success and your capability of success, even after asking these five questions, then you need more information.

You get more information not by choosing one idea, but by pursuing many. You’ll more clearly see what has a chance of succeeding and what you’re capable of succeeding at, and choosing one – or several – will become easy.

Image: Stage Landscape by Paul Klee

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Today I have a special episode for you.

If you missed last month’s AMA/Livestream, I’m delivering it right to your ears. In this AMA, I answered questions about:

There are some parts where I refer to visuals, for the best experience, watch on YouTube.

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Shiny object syndrome can be evidence of a problem, or it can be a normal part of the creative process. If you can identify the four sources of shiny object syndrome, you can tell the difference between being lost, or simply exploring.

The first three of the four sources of shiny object syndrome hold you back from finishing projects. They are: ambition, perfectionism, and distraction.

Before we get to the fourth source, a bit more about these three most dangerous sources.

You probably have a friend with ambitious shiny object syndrome. One day they proclaimed they were writing an epic fantasy novel. A few months later, they had dropped that and had a new plan: a feature film. A few months after that, they were starting a health-tech startup.

All the while, you were shaking your head, because your friend clearly didn’t have the experience or resources to take on these projects. They were writing the epic fantasy novel, yet had never written a short story. They were working on the feature film, yet had never made a short film. They were working on the health-tech startup, yet had no experience in technology, the health industry, nor raising funding.

Delusional optimism can be an asset. Maybe your friend will get lucky, and one of these projects will click. They’re more likely to get struck by lightning.

Instead, you know what’s coming when you ask how the latest project is going. They’ve abandoned that, and are taking on something new. Conveniently, your friend always has a great excuse for why. They find a scapegoat: You can’t get a million dollars for a feature-film without a rich uncle. They claim to have never been serious about it in the first place: Oh, that silly book? I was just dabbling. More likely, they shift the conversation to another subject: Oh my god, did you see the article about the celebrity!

If they had made a public prediction about their potential success in the project, you could hold them accountable. Yet they didn’t, so you have to take their word for it. Interestingly, you’ll never hear, That was foolish taking on that – I didn’t know what I was doing!

Or maybe you have a friend with perfectionistic shiny object syndrome. They endlessly tweak a project that could otherwise be called done. The “shiny objects” in this case aren’t other projects, but rather details within one project.

Your perfectionist friend has one project they’ve been clinging to for years. Their novel has been through eleven revisions. It started as a memoir, but after becoming an urban-fantasy novel, it’s now a thriller. They had a great-looking cover for each of these. But they’ve changed some details about the plot since the latest world-building workshop they traveled to attend, and they want to try a different cover designer. But before they spend money on another cover, they want to decide whether they’re going to publish in places besides Amazon, because that affects the design specs. So they’re taking a cohort-based course so they can ask a successful author what she thinks.

There’s nothing you could tell your friend to get them to ship this project. By now, they could be on their third book, having learned lessons from the previous two. Instead, they’ve convinced themself it has to be perfect.

Or maybe you have a friend with distracted shiny object syndrome. They’re taking on projects they could conceivably complete, given their skills and resources. They don’t seem to suffer from perfectionism, but you can’t tell, because none of their projects get anywhere near the finish line.

Instead, once they make a little progress on one project, they switch to another, then another. Once their screenplay is completed for their short film, they start recording demos for their album. Once they’ve recorded demos for their album, they write their memoir. Once they’ve finished a draft of their memoir, they’re writing a business plan for a non-profit.

This “friend” may be you, and it certainly has been me. Shiny object syndrome is difficult to cure, because these sources are often mixed together. You may take on projects that are too ambitious, but also be distracted by the many other projects you’re taking on. The perfectionism that is keeping you from shipping one project, may divert you to one overly-ambitious project, or a mixture of smaller projects.

Yet there is a fourth source of shiny object syndrome that doesn’t have to keep you from finishing projects: Natural shiny object syndrome.

Natural shiny object syndrome is the diversions and dead-ends that are a natural part of the creative process. When you’re being creative and innovative, by definition, you are going to try some things that don’t work, or need to explore new areas with which you aren’t familiar.

[Projects are like halfpipes.] It’s fun and easy to skate into a halfpipe – to start a project. But once you’re trying to skate out of the halfpipe, you’ve run out of momentum. It’s more fun and easy to skate into a new halfpipe – to start a new project, or tweak a new aspect of the existing project.

But in the natural course of being creative and innovative, you’ll also start new halfpipes. When Leonardo da Vinci developed his painting style, he skated into many halfpipes. To accurately depict light and shade in his paintings, he systematically studied the way light traveled through the atmosphere, and interacted with objects. This led him into other fields, such as optics, fluid dynamics, and geometry.

In fact, one of Leonardo’s most pre-eminent observations in astronomy greatly informed his painting style. He correctly theorized that the light area on the dark side of the moon was created by light reflecting from the sun, off the earth.

By understanding how light worked, he was able to make paintings with an unprecedented sense of realism. The “earthshine” caused by light reflecting from the earth is the same phenomenon that causes a lighter area within the shadow on the underside of the chin of the Mona Lisa. That’s caused by light being reflected off her upper chest.

Left: Leonardo’s sketch of the illuminated area on the dark side of the moon. Right: The illuminated area on the underside of the Mona Lisa‘s chin.

Leonardo of course was an infamous procrastinator. In addition to the natural shiny object syndrome he experienced, he also had shiny object syndrome from the rest of the four sources.

He had ambitious shiny object syndrome, such as when, over the course of decades, he failed twice to cast in bronze the largest-ever horse statue.

He had perfectionistic shiny object syndrome, such as the fact that he never delivered the Mona Lisa to his client. He instead carried it around fifteen years, until he died, and well after it could have easily been called done.

He had distracted shiny object syndrome, which caused him to run around Italy, trying to please his clients in art, architecture, and engineering.

You can do something about most sources of shiny object syndrome.

But even if you clear those sources away, you’ll still have to live with natural shiny object syndrome. To connect ideas from disparate fields, you need to wander into them. To find out what works, you have to try some things that won’t.

Image: Main path and byways, by Paul Klee

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Writing a tweet is a microcosm of writing a book. If you think deeply and carefully about every word in a tweet, and what the tweet as a whole communicates, you can extend those skills to all your writing. In this article, I’ll break down how to think about every word in a tweet, nearly tripling its performance.

The tweet we’ll work on came to me like most tweets, a thought that popped into my head. It was this:

Ironically, strong opinions are the ones that are easily argued against.

I could have just tweeted that. But I’ve made a habit of instead writing down my first-impression tweets in a scratch file, and later working on them before publishing. Here’s what my thought process looks like.

As a tweet, this phrase is a little wordy, and weak. It starts somewhat nonsensically with an adverb: “Ironically.” What action is being performed ironically?

There are also some extra words that could be cut out. Do we have to refer to “strong opinions” again, by using the word “ones”? The word “that” is often not necessary, and it doesn’t seem necessary here.

If we cut out all those extra words, we end up with:

Strong opinions are easily argued against.

That’s shorter, more elegant, and economic. But now it’s weaker. It’s a simple statement of fact, without presenting what’s remarkable about that fact, or how anyone should feel about it. At least when it said, “ironically,” it pointed out the irony that strong opinions are those that are easily argued against.

Also, since I’ve removed the second reference to “strong opinions” by removing the word “ones,” the statement no longer pits “strong opinions” against other types of opinions. Before, I was implying the existence of opinions that weren’t strong, and describing what was different about opinions that were.

Our shortened statement is also in the passive voice, which makes it weaker. “Strong opinions are easily argued against,” by whom? Who is doing the arguing? It would be more direct to say:

It’s easier to argue against strong opinions.

But still, this statement doesn’t pit strong opinions against other types of opinions. Fixing that, we could instead say:

Of all opinions, strong ones are easiest to argue against.

Finally, I think we at least have an improvement over the original, “Ironically, strong opinions are the ones that are easily argued against.” It’s more direct, and pits strong opinions against opinions at-large. It also has the important quality, in tweet format, of delivering the most surprising – or ironic – thing about the statement at the end.

There’s a bit of misdirection in this statement. We’ve addressed all opinions, homed in on the strong ones, which primes you to expect them to be lauded in some way. Instead, the statement points out the irony that what makes an opinion “strong” is that it’s easy to argue against.

But this tweet is still not ready. The most glaring problem is, nowhere in the tweet is the term, “strong opinions,” and, as a tweet, that’s where its potential lies.

“Strong opinions” is a term in the parlance of some sections of Twitter. This term became popular after Marc Andreessen appeared on Tim Ferriss’s podcast, where he advocated for, “strong opinions, weakly held.”

By trying to be economical with words in our tweet, we’ve broken apart this term. In our latest iteration, “Of all opinions, strong ones are easiest to argue against,” it’s simply referred to as “strong ones.”

Depending upon how prevalent the term “strong opinions” is in the minds of our audience members, we could stick with that more subtle hint. Sometimes that’s more effective. In my experience, on Twitter, you have to bash people over the head with what you’re saying to cut through the noise.

So we could instead say:

Of all opinions, strong opinions are easiest to argue against.

We’ve replaced “strong ones” with “strong opinions.” It’s less economical, but includes the term “strong opinions,” pits them against opinions at-large, and delivers the counterintuitive element at the end, like the punchline of a joke.

This is probably as economically as we can write this, meeting that criteria. But it’s still not ready. Now it’s not clear from this observation how the author wants us to feel about strong opinions. It’s, ironically, not a strong opinion.

Is the upshot that you shouldn’t hold strong opinions? Is it that when you hold strong opinions, you have to be comfortable with the fact they are easy to argue against?

What makes an opinion “strong,” anyway? Is it the force with with which you express the opinion? If so, the statement, “strong opinions, weakly held” would mean you express the opinion with force, but are quick to change it if presented with contrary evidence.

Or maybe it means that you should take decisive action on your opinions, and if that action presents you with contrary evidence, you should change your opinion and act accordingly?

Now we’re starting to get to what I, as an author, really think – which is like an excavation to discover, Where did this idea come from in the first place?

My personal opinion is that to hold a strong opinion, you have to be faking. There are few things any of us are qualified to have opinions about. Having a strong opinion is a very “hedgehog” way of being, and hedgehogs are scientifically proven to be wrong.

Yet if you express your honest opinion – which is to be more like a “fox” than a hedgehog – you’re essentially expressing no opinion at all. Instead, you’re exploring thoughts around a potential opinion. Given the mechanics of media today, few who see what you have to say when expressing your fox-like opinion will interact with it. And because few will interact with it, fewer will see it.

So in a way, to be fox-like in media is doing oneself a disservice. Your message doesn’t get seen, and since nobody can disagree with your non-opinion, you learn less. It’s beneficial to masquerade as a hedgehog on social media, but be a fox in your private intellectual life.

It’s at this point in revising a tweet, where I often step back and write plainly the sub-text of what I’m trying to say. One angle is, In your pursuit of learning, you have to pretend to have strong opinions, because strong opinions are the easiest to argue against – which helps you collect information.

Another angle is that When you express a strong opinion, be ready to be disagreed with, because strong opinions are by definition the easiest to argue against.

So now I have two potential angles:

Since this is a tweet, the sub-text of the tweet is very important. Because of the social mechanics of Twitter, people will not like or retweet something that makes them look bad.

The “You should pretend to have an opinion” angle is weak, because to retweet something that espouses being inauthentic is to admit to being inauthentic, and that’s socially repugnant – even if our angle has merit. Also important, it’s not socially-repugnant enough to get people to argue, which would be another way of driving engagement.

The “When you express your opinion, be ready for criticism,” angle is somewhat stronger. It would be a small flex to like or retweet this, because it would show that you’re a person resilient enough to expose yourself to criticism, a quality which has social clout in some circles.

Moving forward with that best angle, in the clearest way possible, we could say:

When you share strong opinions, you will be criticized. Because strong opinions by definition are the easiest opinions to disagree with.

Besides the fact it’s much longer, there’s something weak about this tweet. I think it’s that it makes strong opinions not look good. Why have them if they’re so easy to disagree with? As someone with a fox cognitive style, to me it doesn’t feel right.

So ultimately it seems, I believe a third angle: “Strong opinions aren’t good.” If we put that simply, we’re back to “Of all opinions, strong opinions are the easiest to argue against.”

That still doesn’t express clearly how I feel about strong opinions. It’s just a statement of fact.

Maybe we can make this more economical, while also expressing more clearly my feelings about strong opinions, if we use a rhetorical form. Rhetorical forms are time-tested structures in language that add meaning beyond the simple content of the words.

“Antithesis” is a good rhetorical form for tweets. Mark Forsyth in The Elements of Eloquence describes antithesis as “X is Y, and not X is not Y.”

We won’t use that exact formula, which would essentially be “Strong opinions are easy to argue against, and weak opinions are hard to argue against.” Instead, let’s pit the word “strong” against its antithesis, “weak” – which is part of why the phrase “strong opinions, weakly held” is so memetic.

As it happens, the idea of a “weak argument” is a commonly-used metaphor, so we can add extra power to our phrase by tapping into that existing idiom.

With those elements in mind, we end up with:

Strong opinions are weak arguments.

That’s about as good as we can do. We’ve reduced the phrase from eleven words to only five. It’s now clearer what I think of strong opinions, and it presents the irony I wanted to point out in the first place.

So, how did this tweet do? I published it, making sure to record a prediction that I was 70% sure it would get fewer than 1,500 impressions (in 48 hours). It actually got 1,081.

One month later, I published the unedited tweet I presented at the beginning of this article. I was 70% sure it would get fewer than 1,000 impressions. It got 384.

The data suggest that through all that excruciating detail – more than 1,500 words about writing only five – I nearly tripled the performance of this tweet.

The tweet still didn’t go viral, which isn’t the point of thinking of language in this level of detail. The real point of this exercise is that if you make a habit of thinking carefully about language, you internalize much of this process, which makes all your writing better.

Image: Flower Myth, by Paul Klee

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Every message is shaped by the mechanics of media. Whether it’s a tweet, a TikTok video, a news article, or a movie, the characteristics of the medium determine how it’s made, how it’s consumed, and whether it spreads. If you understand the mechanics of media, you can more effectively communicate in a wide variety of mediums, and protect yourself from being manipulated by media.

As media theorist Marshall McLuhan said, “The medium is the message.” In Understanding Media, he wrote:

The medium is the message. This is merely to say that the personal and social consequences of any medium…results from the new scale that is introduced into our affairs….

In other words, it’s not the content of the medium we should be worried about, but the way the characteristics of that medium determine its content – the mechanics of media.

I propose that there are five characteristics present in any medium, which determine these mechanics. These characteristics affect the creation, consumption, and distribution of media. (In other words, what message is delivered, how that message is received, and whether or not that message spreads.)

Those five characteristics are:

The mechanics of media are so complex, these characteristics naturally interact with one another. I’ll give a brief introduction of each, then show how these characteristics work in the popular mediums of podcasts, Twitter, and TikTok.

The Incentive characteristics of a medium are sources of motivation, whether money or otherwise, that shape the creation, consumption, and distribution of messages in that medium.

The creator of a piece of media is motivated by various incentives, such as money and relationships. Whether or not someone is able to consume a piece of media depends upon whether its affordable or otherwise accessible. Whether or not a piece of media spreads depends upon whether incentives are aligned for the distribution platform to allow it to spread.

So, a journalist may be motivated to write a story that gets page views, because that’s how they’re paid. That’s how they’re paid, because the newspaper doesn’t have paying subscribers and thus relies upon ad revenue. The stories with click-bait headlines spread and get more page views because they increase engagement for the social media platform they’re shared on, which increases the social media platform’s ad revenue.

The Sensory characteristics of a medium are the ways in which the medium engages senses such as sight, hearing, and touch. Marshall McLuhan wrote about how so-called “sense ratios” were engaged by a medium. Sensory characteristics primarily affect the consumption of the medium, but those effects overlap with creation and distribution.

Written content, for example, can be absorbed at a reader’s own pace. As Neil Postman pointed out in Amusing Ourselves to Death, the written word is especially well-suited to careful review and comparison, which makes it easier to convey the truth. Audio content can be replayed to be reviewed, but it’s more work than simply moving your eyes back over the content.

The Physical characteristics of a medium are the ways in which the medium engages the body. The subtitle of Marshall McLuhan’s Understanding Media is Extensions of Man. As a medium extends our abilities, it also removes or “amputates” abilities.

When you listen to a podcast, your entire body is free to do other things. You may be cooking, showering, or fighting your way to the exit of a crowded subway car. So, audio with dense content may not be absorbed as well as if the same content were printed in a paper book – which can still be read on a subway car, but not likely while walking. Podcasts became distributed more widely as they became easier to download on smartphones, which people physically carry around.

The Social characteristics of a medium are the ways in which the medium facilitates interactions amongst people. In the age of social media, these interactions affect creation, consumption, and distribution, in concert.

Algorithms that drive distribution on platforms such as Twitter, Instagram, and TikTok are designed to distribute a piece of content based upon its engagement. Much of that engagement is social. If you comment on, like, or share a piece of content, that social interaction leads to further distribution.

Additionally, the level of privacy involved in consuming or sharing content has social consequences. You may be reluctant to even “like” certain content, for fear of who might see. But you might share the same content with a close friend through a text message – so-called “dark social” – or even a dinner conversation.

The psychological characteristics of a medium are the ways in which a medium interacts with human psychology.

Cognitive biases affect the way people interpret a piece of media, and media platforms are designed to exploit these biases. For example, variable rewards make social media platforms habit-forming for both consumers and creators. You never know when you’ll find something incredibly valuable during a social media session, and as a creator, you’re always checking to see if you’ve gotten more comments and views.

To go back to our example of a journalist paid by the page view, incentives may motivate them or the newspaper at which they work to cover more natural disasters, shark attacks, and terrorist attacks, which grab people’s attention as a result of the availability heuristic.

Here’s a sampling of how these five characteristics shape various mediums.

There are two main ways podcast creators make money: either have a lot of listeners and sell sponsorship, or have few listeners, but make money on some kind of “back-end” business. It’s very hard to get new listeners for a podcast, for reasons that will be clear when we analyze the other mechanics, so this motivates many podcast hosts to do “swaps,” wherein hosts interview one another on each other’s podcasts.

Many listeners listen to podcasts alone, through headphones. Audio can’t be rewound as easily as someone can re-read, so the content should present simple ideas with simple language, and storytelling can keep the listener engaged.

Listening to a podcast doesn’t engage much of your physical body, so listeners may be doing nearly anything while listening. They could be driving, showering, or doing household chores. With AirPods, they could even be hitting golf balls. Listeners may be in distracting situations, so again, the mechanics of the podcast medium lend themselves to simple ideas presented through simple language, and strong storytelling.

A podcast host makes an intimate connection with a listener because they’re often talking right into the listener’s ear, often while they’re alone. In this way, the host becomes like the internal monologue of the listener. This is part of why there are so many podcasts despite it being so hard to attract new listeners. This intimate connection can attract new customers and clients for high-ticket items, and advertisers are willing to pay a lot per listener, especially when the host reads the ads.

It’s hard to attract new listeners to podcasts, because podcasts don’t lend themselves well to social consumption and distribution. Podcast listeners are usually physically occupied when listening, and unlikely to engage through likes, shares, and comments. These features aren’t available in most podcast-listening apps, since podcasts are distributed through decentralized feeds that can be captured by one of many such apps.

Podcast content can be several hours long, with the information presented in the disorganized form of a conversation. Even when pieces of a podcast are presented as clips on social media, there are a few formidable barriers to such clips attracting listeners: Editing long-form content to be interesting in short-form is difficult, audio content has trouble competing with other content on social media feeds, and social media is often consumed in contexts in which it’s not convenient to download and listen to a podcast.

Podcast producers take advantage of the ways in which audio content can affect the psychology of the listener. Narrative podcasts use music and storytelling to manipulate listeners’ emotions and build suspense and engagement. Compelling podcast interviewees know how to talk passionately and persuasively in a way that will excite listeners. Still other podcast hosts deliberately speak in an unpolished way, to make their shows feel more like listening to a friend.

On Twitter, journalists can build followings, which can help them get more page views, which can help them either get paid more, or not rely on their employers at all. Entrepreneurs can grow their businesses. Writers, such as myself, can test out ideas. People, generally, can be entertained, or feel as if they’re heard.

Twitter is still primarily an ad-supported platform, so more engagement with the platform means more ad revenue. While I presented above an example of a social media platform presenting articles with click-bait headlines, the incentive characteristics of Twitter also work against this. If you were to click on a link, you would leave Twitter, where you could no longer be served ads. So tweets that are just links get less distribution.

Twitter is primarily text, which is supposed to be the form of media most-capable of communicating the truth. Yet anyone who has used Twitter has noticed there is a lot of sensational content, with lots of arguing and fighting amongst tribes. How can this be?

Since Twitter is mostly a collection of snippets of text, which can be easily skimmed, it puts people in a “hunting” mode. Unlike reading a book, where the sensory experience locks you into the progression of ideas presented by the author, on the Twitter timeline, the sensory experience is like scanning the landscape for the gazelle in the grass, or the tiger in the bush.

Many Twitter users consume its content on their phones. They’re looking at their hands, often slouched over with neck craned downward. This is a posture that makes you more close-minded and negative, as opposed to say, standing up, with a monitor at eye-level, and shoulders back while typing on a split keyboard.

Users can be in a variety of settings, such as on public transport, or even crossing the street. On Twitter, consumption and creation can be physically the same, which lends itself to off-the-cuff and often reactionary or poorly-thought-out content. So content creators on Twitter who do the majority of their thinking away from the app, and put intention into their creation process, are essentially practicing attention arbitrage.

Twitter has followed the lead of platforms such as TikTok, and decoupled the distribution of content from the follower relationship, in lieu of a feed driven by engagement or relevance of topic. Still, the number of followers greatly influences distribution on Twitter. Thus, savvy Twitter creators know they have to be active “reply guys” – replying to tweets on related accounts – until they gain a following.

Besides followers and the ever-more-rare retweet, the biggest driver of distribution on Twitter is replies. Therefore, tweets that drive conversation get more distribution. Ironically, if a tweet is clear and factual, it won’t get as much distribution as if it is unclear and controversial. So, creators who are either unintelligent in a lucky way, or savvy and machiavellian enough to feign ignorance, see great distribution through “fake takes,” or expressing with great confidence a simplistic opinion people will argue over in the replies.

The “fake take”: Are we supposed to believe a Harvard-educated Wharton professor doesn’t understand what a random act of kindness is?

Almost all activity on Twitter is public by default, so this creates a media environment with a bias toward behavior that’s either prosocial or tribal. There can be social consequences for merely following someone or liking one of their tweets. There’s a lot of what Timur Kuran calls “preference falsification” on Twitter, to signal that one is part of a tribe. The only characteristic that counters this is that expanding a tweet or media within a tweet is private, so this private engagement can help somewhat the distribution of content people may not be comfortable supporting publicly.

Many creators are attracted to TikTok because it’s a platform where it’s possible to have a lot of success very quickly, and seemingly for no good reason. You can get tens of millions of views just dancing in front of your bathroom mirror. TikTok is an ad-supported platform, so the platform distributes content that will overall increase the time spent on the platform. Yet TikTok overall has a more-positive vibe than Twitter. We’ll get to why.

If the sensory experience of Twitter puts the viewer into “hunting” mode, the sensory experience of TikTok is more like the campfire. You’re not skimming a vast sea of text. Instead, you’re immersed entirely in a video – at least for a moment. You’re often face-to-face with a person talking. It’s harder to get angry with someone when you’re looking right at them. This campfire instead of hunting experience makes content on TikTok more positive than on Twitter.

But you’re not immersed in that video for long. Users can quickly swipe and be immersed in the next video. So, there is a lot of pressure for creators to create content that grabs the attention of the viewer. It’s not unusual, when looking at an engagement graph on a TikTok video you’ve created, to see a note informing you there was a drop in viewership at the one second mark.

Bruh, there’s not enough value in the first second.

This is part of why TikTok has a reputation for being all about looks. Indeed their new “Bold Glamour Filter” reshapes women’s faces to an astounding degree (yet they still have nothing for my gray beard hairs).

TikTok, like all social media, is primarily consumed on a mobile phone. So consumers may be in any of a variety of settings, including highly distracting environments where they don’t have control over sound. So, TikTok videos present simple ideas, presented quickly, and videos with captions perform better, as viewers may have audio off.

However, there is some incentive for creators to present complex data associated with their simple ideas. If you flash a data-rich graphic in a TikTok video, viewers will try to pause it, which is a signal of engagement for the TikTok algorithm. You’ll do even better if the graphic flashes so quickly it can’t be paused the first time. The viewer will have to let the video play again, to once again attempt to pause at the right time.

For example:

Since pausing or rewatching a video signals engagement to TikTok, dance videos have performed well on the platform. Consumers can become creators and post “duets”, in which they perform a dance next to its originator. Of course you have to watch the video many times to get your dance moves right, which signals engagement. This physical bias towards dance videos, helped along by the social characteristics of TikTok, may also contribute to its more-positive vibe.

Like anywhere many humans congregate, there is still some negativity on TikTok. But if you’re going to be explicitly negative, you’re going to have to show your face. Comments are limited to 150 characters. Beyond that, you can make a reply video, a “duet” – such as in dance videos, or a “stitch,” where you place your video at the end of the video you’re responding to.

Because simple videos that viewers re-watch get more distribution, videos on TikTok resist the sense of closure humans have been used to since at least the time of Homer. If you summarize what you’ve covered at the end of a video, your engagement will drop and you’ll get fewer views. So videos don’t have the satisfying end we’re used to. Some creators make their videos “loop,” wherein the final thing said connects to the first thing, which hypnotizes the viewer into watching again.

This being an article, it’s not bad for me to take the time to present a conclusion. That’s my overview of what I believe to be the five characteristics that shape the mechanics of media, and how those mechanics shape the mediums of podcasts, Twitter, and TikTok.

The next time you’re creating something for a medium, or feeling highly-persuaded by a piece of media, take time to think about the five characteristics that shape the mechanics of media.

Image: Painting 1930, by Patrick Henry Bruce

Thank you for having me on your podcasts. Thank you to Rachel Roth at The Rachel Roth Show.

As always, you can find interviews of me on my interviews page.

This is the 300th episode of Love Your Work. Something I haven’t asked in years: Can you please rate the show on Apple Podcasts?

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Theme music: Dorena “At Sea”, from the album About Everything And More. By Arrangement with Deep Elm Records. Listen on Spotify »

Making, recording, and evaluating predictions is a simple way to improve your thinking and decision-making. But the way to properly make and record predictions isn’t obvious. In this article, I’ll share some predictions I’ve made, what I’ve learned, and how you can improve your thinking by making predictions.

Five years ago, I had been running my business for ten years, and it wasn’t going great. Then, I started publishing monthly income reports, and along the way, making predictions. My income has nearly doubled, and I attribute much of that success to my habit of making predictions.

I began by predicting how much money I’d make in a product launch, and grew to predicting how much traffic articles I had written would gain, and how many copies books I’d written would sell. I now routinely make predictions for things as seemingly mundane as whether I’ll enjoy a conference, whether I’ll still be publishing on TikTok a year from now, or whether an avocado is ripe.

On the surface, making predictions seems like a pointless game. This is, indeed, true of making predictions the wrong way. But making predictions the right way helps you deal with uncertainty you otherwise have no hope of handling.

Each of us has limited resources, such as time, money, and mental energy. We’re constantly making decisions about how to use these resources, and when we make those decisions, we are expecting outcomes.

As Annie Duke, author of Thinking in Bets wrote:

In most of our decisions, we are not betting against another person. Rather, we are betting against all the future versions of ourselves that we are not choosing. —Annie Duke, Thinking in Bets

Each decision we make is a bet. We bet a resource, and expect something in return. Most of us don’t recognize or express the expectations of our bets. But we should.

If you bet a dollar on a coin flip and only win $1.50 for guessing correctly, you’d easily recognize that as an unfair bet: There’s a 50% chance of guessing correctly, so you clearly should receive two dollars. But the more variable the odds, and the more vague your wager and winnings, the more difficult it becomes to think clearly.

What’s the value of finding the love of your life? What other benefits can you get writing a book besides fame and fortune? What are the chances that during this hour of social media you’ll make a life-changing discovery? Making objective decisions taking into account all these variables becomes so complicated you might as well throw up your hands, surrender to randomness, and do what feels right in the moment.

And that’s what most of us do. Case in point: The multi-billion-dollar gambling industry, propped up by people doing what feels right in the moment – their decision-making shrouded by the smokescreen of ever more complex and variable bets.

The key to making predictions in a way that helps you evaluate your decisions is to avoid what Annie Duke calls “resulting.” If you wager a dollar on a coin flip, with a chance to win $10, and lose, the result of your decision was bad, but your decision was good. The odds were clearly in your favor. Mathematically, you were sure you’d win that bet one of two times. If you had won, you were going to win ten times your money.

Now how do you apply this thinking to more complex and vague situations, such as a product launch, your Saturday night plans, or whether or not your new hobby is a passing obsession? The key is to make a prediction, the right way.

There are two components to making predictions the right way.

First, turn the prediction into a coin flip. I don’t mean in terms of odds, but in terms of result. When you flip a coin, it comes up heads or tails. When you make a prediction about a result, that result must either happen or not. For a prediction to be useful, it has to be falsifiable.

This is not easy to do, which is why few of us make predictions the right way, if at all.

You can define a successful result in whatever measurable way you want. The important thing is that to make a prediction, you need to turn the result into a coin flip. Not in terms of odds, but in terms of how you define the result.

Some actual predictions I’ve turned into coin flips:

With each of these predictions, I was wagering resources. It took, time, money, and energy to run a promotion, write a blog post, and write a book. But what did I expect from those investments? I could have done any of these without making a prediction. Besides the long-term benefits of making these predictions – which I’ll get to in a bit – turning these predictions into coin flips had immediate benefits.

Turning predictions into coin flips helps answer these questions:

When you flip a coin, you of course aren’t sure whether it will come up heads or tails, and when you make a prediction, you aren’t sure whether you’ll achieve that result. And that is how it should be.

The second way to make a prediction the right way is to identify the odds of achieving that result. You’ve turned the prediction into a coin flip, but it’s not necessarily a coin flip with 50/50 odds. It may be more like a die roll, with 1:6 odds, or a roll of four or lower, with 2:3 odds.

If you’ve turned your predicted result into a coin flip by adjusting a range, you can adjust that range according to your expected odds. In this way, if you want to literally turn your prediction into a coin flip, you can pick a range you feel you have 50/50 odds of achieving. For example, I believed I had 50/50 odds of making $3,000–$6,000 on my Black Friday promotion, and of selling 5,000–15,000 copies of my book in the first year. I specifically chose those ranges based upon what I expected to have 50/50 odds of achieving.

If your prediction doesn’t involve a range, such as whether or not you will regret going to a party, then you simply have to identify your expected odds of that result. For all odds, I think it’s easiest to choose a percentage of confidence, such as 50% for 50/50 odds, or 66% for 2:3 odds. For example, I was 70% sure I wouldn’t regret attending a conference in Vegas last year.

Each of these predictions is for one event. But the result will either be achieved, or not. Therefore, what you felt 70% sure would happen will in retrospect look as if it had 0 or 100% odds of happening. So what is the point of choosing odds for your prediction?

There are three benefits of choosing odds:

First, choosing odds of achieving a result helps you gain clarity on a decision. Let’s say you buy your first guitar. Surely you’re picturing yourself being a pretty good guitar player someday. But how do you define that, how sure are you you’ll become a good guitar player, and how soon? A year later, when your guitar is collecting dust in your closet, you might feel pretty bad about yourself.

But suppose that when you bought your guitar you had predicted that you were 50% sure, one year later, you would have practiced guitar at least fifteen minutes in the previous month? Based upon that prediction, it turns out you weren’t so sure to begin with that you’d become a good guitar player.

Which brings us to the second benefit of choosing odds, which is that it helps you distinguish risky decisions from not-risky decisions. You took a chance buying a guitar, and it didn’t work out. That’s easier to live with if you know you were taking a chance.

Some of life and business’s greatest benefits come from taking chances. But you only have so many resources to gamble with. Professional poker players know they need a certain “bank roll” to stay in the game and keep making bets. If they have a lot of bank roll, they might play a riskier bet than if they have little. They’re able to do that because they know the odds.

In business, especially creative business, your “sure bets” keep you in business, while “wildcards” can change your business. As you decide how to invest your resources, and evaluate whether you’ve achieved successful results, you’ll make better decisions if you know ahead of time whether you’re playing a sure bet or a wildcard.

For example, I was 95% sure my Zettelkasten blog post wouldn’t rank in the top ten for the search term, so I was clear going into it I was playing a wildcard. Additionally, while I was 50% sure I’d sell 5,000–15,000 copies of my book in the first year, I was 90% sure I’d sell fewer than 250,000 copies, which helped put a ceiling on my expectations.

Which is the third benefit of choosing odds: improving your decision-making over time. If you had been 90% sure you’d’ve practiced guitar ten hours in a month, you’d still feel bad when it turned out you didn’t, but at least you’d have data to learn from. Without that data, you might say to yourself, “I never finish what I start. I’m a loser.” With that data, you can say, “I overestimated my enthusiasm to play guitar. I’ll keep that mistake in mind in the future.”

Notice you wouldn’t tell yourself you were “wrong.” Because you weren’t. Even if you were 90% sure you’d’ve practiced guitar ten hours in a month and didn’t, you’d only end up 90% wrong. Which means you were 10% right. When you choose odds of your expected results, it’s easier to learn from your mistakes because you’re never totally wrong, and always a little right – which makes your mistakes sting a little less.

But to get enough data to know how good your predictions are, you need to make a lot of predictions over time. If you don’t know the odds of a coin flip, and your prediction turns out wrong, you don’t learn a whole lot. But if you make a hundred predictions, you’ll end up with a pretty good idea of the odds of that coin flip.

The more predictions you make with the same odds, the more quickly you can tell how good your predictions are. I’ve presented to you examples of predictions I’ve made with various odds. But whenever possible, I try to choose “coin flips” I believe have a 70% chance of being correct.

70% is an arbitrary level of confidence. What’s important is that by making many predictions of which I have 70% confidence, I learn how accurate my predictions tend to be at that confidence level.

I’ve made 19 predictions at 70% confidence. Only 63% of those have turned out correct. By making and tracking many predictions, I’ve learned that when I’m 70% confident something will happen, it will generally happen only 63% of the time. I’m slightly overconfident at that range, and so should be more conservative with my future predictions.

I keep track of and publicly display many of my predictions on PredictionBook.com, which is one of those totally free websites with no ads that makes you nostalgic for 2007. Because I’ve made more than fifty predictions, I can see how good I am at predicting at various levels.

My prediction track-record: Decently accurate when I’m confident, wildly inaccurate when I’m not confident.

For example, after fifteen predictions at 90% confidence, 80% have turned out correct. After five at 50% confidence, and five at 60% confidence, those have turned out correct 80% and 100% of the time, respectively. While I should to be more pessimistic about things I’m pretty sure will happen, it seems I should be more optimistic about things I’m not so sure will happen.

It turned out the prediction that my Black Friday promotion would earn between $3,000 and $6,000 was correct. Since I was 50% confident, I was half-right, and half-wrong. I did sell between 5,000 and 15,000 copies of my book in the first year. Again, half-right, half-wrong. And the Zettelkasten blog post I was 95% sure wouldn’t rank in the top ten, actually did! I was happy to be 95% wrong about that – it was a wildcard that turned out.

The next time you’re choosing whether something is worth doing, I highly recommend you make a prediction. If turning the outcome into a coin-flip and picking a percentage of confidence feels uncomfortable to you – it should. Thinking in this way doesn’t come naturally – which is why it’s a superpower.

Image: Ghost of a Genius, by Paul Klee

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