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Francis Bacon never saw a cryptocurrency ad. He never sat through a keynote where a CEO in a black turtleneck promised to change the world. He never scrolled past a sponsored post claiming that some new platform would “democratize” something that was working fine already. And yet, if you dragged him into the present day, he would probably look around at our tech landscape and say something like: yes, this is exactly what I warned you about.
Bacon, writing in the early 1600s, was obsessed with a single question. Why do smart people believe stupid things? Not just ordinary people. Smart ones. Educated ones. People who should know better. He concluded that the human mind is not a clean mirror reflecting reality. It is a warped one. It bends light. It distorts what it receives. And unless you learn to identify the distortions, you will keep falling for the same tricks dressed in new clothing.
He called these distortions “idols.” Not the golden calf kind. The mental kind. Patterns of thought so deeply embedded that you do not even notice them operating. And four centuries later, those same patterns explain why millions of people keep handing their money to tech ventures that have no product, no revenue, and no plan beyond a website with a lot of gradient colors.
Let us walk through them.
The Idol of the Tribe: We All Want to Believe
Bacon’s first category was the Idol of the Tribe. These are the errors that come standard with being human. They are not personal flaws. They are factory settings. And the most dangerous one, from a tech hype perspective, is our tendency to see patterns and intentions where none exist.
Humans want things to make sense. We want stories. We want cause and effect. When a tech founder stands on stage and draws a straight line from “where we are now” to “a trillion dollar market,” your brain wants to follow that line. It feels good. It feels like understanding. But a line drawn between two points is not evidence. It is a drawing.
This is exactly how hype cycles work. Someone identifies a real problem. They propose a solution that sounds plausible. They project growth numbers that assume everything will go right and nothing will go wrong. And because the human brain is wired to complete patterns, you fill in the gaps yourself. You become a co-author of the fantasy without realizing you picked up the pen.
Think about the metaverse pitch from a few years ago. The story was clean and compelling. Physical space is limited, digital space is infinite, therefore the future of human interaction is virtual. It sounded like a pattern. It sounded like progress. What it actually was, was a company with a declining core product looking for a new story to tell investors.
Bacon would have spotted this instantly. He argued that the human mind “is rather like an enchanted glass” that mixes its own nature with the nature of things. When you look at a tech pitch and feel excited, it is worth asking: am I excited because the evidence is strong, or because the story is good? Those are not the same thing.
The Idol of the Cave: Your Personal Blind Spot
The second category is the Idol of the Cave. This is the personal version. Where the Tribe distortions affect everyone, Cave distortions are yours specifically. They come from your education, your experiences, your professional background, and what you happen to have read last Tuesday.
This one is sneaky in the tech world because it works differently depending on who you are. Engineers fall for technical elegance. They see a clever solution and assume it will find a problem worth solving. Business people fall for market size numbers. If the addressable market is large enough, the product almost does not matter. And regular consumers fall for novelty. If something is new, it must be better. Otherwise, why would it be new?
Here is the counterintuitive part. Your expertise can actually make you more vulnerable, not less. A software developer is more likely to overvalue a technically interesting blockchain project because they understand the architecture. They mistake comprehension for validation. Understanding how something works is not the same as confirming that it should exist. A lot of beautifully engineered products solve problems nobody has.
This is why the most successful tech investors are often generalists. They are less likely to be seduced by the details because they are not equipped to be. They ask blunt questions like “who is paying for this” and “why would someone use this instead of what they already use.” These are Cave questions. They cut through personal bias by refusing to engage with it.
Bacon recommended a kind of intellectual humility that is remarkably rare in the tech industry. He suggested that whenever you feel strongly drawn to an idea, you should examine your own reasons for the attraction before examining the idea itself. In modern terms: before you evaluate the startup, evaluate why you want to evaluate the startup. Your enthusiasm is data. It is just not data about the startup.
The Idol of the Marketplace: When Words Do the Lying
The third category might be the most relevant to the current moment. Bacon called it the Idol of the Marketplace, and it concerns the way language itself can deceive. Words, he argued, are not neutral containers for meaning. They shape thought. They create categories. And when the wrong words get attached to the wrong things, confusion follows as reliably as thunder follows lightning.
The tech industry is, to put it gently, a masterclass in this particular idol.
Consider the word “disruption.” Originally, it meant something specific. Now it means “we made an app.” Every pitch deck describes itself as disruptive. The word has been emptied out and refilled with pure marketing. It signals nothing except the desire to signal something.
Or take “AI.” Two letters that currently function as a kind of financial magic spell. Attach them to any company description and watch the valuation change. Never mind that what most companies call AI is statistical pattern matching that has existed in various forms for decades. The label does the work. The technology is almost beside the point.
Bacon was remarkably clear about how this works. He wrote that words “plainly force and overrule the understanding, and throw all into confusion.” When a tech company says it is building a “platform,” that word carries implications of openness, scalability, and network effects. But many so called platforms are just websites. The word does the heavy lifting that the product cannot.
This is not always intentional deception. Sometimes founders genuinely believe their own language. They use big words because they have big ambitions and the gap between the two has not yet become obvious. But the effect on you, the reader or investor or customer, is the same regardless of the speaker’s intent. You end up evaluating the language instead of the reality.
One useful exercise borrowed from the philosophy of science: try to restate any tech pitch using only simple, concrete language. Replace every abstract term with what it actually means in practice. “We are building a decentralized autonomous organization that will revolutionize governance” becomes “we are making a group chat where people vote on things using cryptocurrency.” Both descriptions might be technically accurate. But they create very different impressions. The gap between them is where the hype lives.
The Idol of the Theater: The Grand Performance
Bacon’s fourth and final category is the Idol of the Theater. These are the distortions that come from received systems of thought. Grand theories. Ideologies. Comprehensive frameworks that explain everything and therefore explain nothing.
In the tech world, the Theater idol shows up as what you might call “narrative capture.” It is the tendency to adopt a complete worldview from a charismatic source and then interpret all new information through that lens.
Think about how Silicon Valley cultures produce their own orthodoxies. There was a period when “move fast and break things” was not just a motto but a philosophy. An entire generation of founders internalized the idea that speed was inherently virtuous and caution was inherently cowardly. This was not a conclusion they reached through careful analysis. It was a doctrine they absorbed through cultural exposure. It came pre installed, like bloatware on a new laptop.
The current version of this is the techno optimist framework, which holds that all technological development is inherently good and that skepticism is a kind of moral failure. Within this theater, questioning whether a new product is useful makes you a pessimist. Asking whether a company can actually deliver on its promises makes you a hater. The framework insulates itself from criticism by reclassifying criticism as a character flaw.
There is an interesting parallel here with religious history. Bacon himself was writing during a period when received intellectual authority, specifically Aristotelian philosophy filtered through the medieval church, was being challenged by direct observation. The old system was beautiful, internally consistent, and wrong about a remarkable number of things. The tech world’s grand narratives function similarly. They are elegant, self reinforcing, and frequently disconnected from observable reality.
Putting It All Together: A Practical Bacon Filter
So how do you actually use Bacon’s framework when you encounter the next wave of tech hype? Here is a practical approach.
First, check for Tribe distortions. Is this pitch appealing because of evidence, or because of narrative? Are you being shown data, or being told a story? Stories are how humans have communicated since we lived in caves, which is precisely why they are so effective at bypassing critical thinking. A good story is not evidence. It is a delivery mechanism for claims that may or may not be true.
Second, check for Cave distortions. Why are you personally drawn to this? Does it flatter your existing beliefs? Does it align with your professional identity? If you are a tech enthusiast, you are more susceptible to tech optimism. This is not a character flaw. It is a statistical likelihood. Account for it.
Third, check for Marketplace distortions. Translate the language. Strip out the jargon. What is actually being described here? If the plain language version sounds underwhelming, that is information. The gap between the fancy version and the plain version is a rough measure of how much work the marketing is doing relative to the product.
Fourth, check for Theater distortions. Are you evaluating this specific thing on its specific merits, or are you applying a general framework that says things like this are always good (or always bad)? Both reflexive enthusiasm and reflexive cynicism are Theater idols. The goal is not to be positive or negative. The goal is to be accurate.
Why This Matters Now More Than Ever
We are living through what might be the most hype dense period in the history of technology. The combination of social media amplification, a culture that celebrates founders as visionaries, and a genuine acceleration in certain technologies has created an environment where distinguishing signal from noise is genuinely difficult.
Bacon could not have anticipated the internet, but he anticipated the internet’s core problem with remarkable precision. The issue was never information scarcity. The issue was always filtering. How do you sort the real from the persuasive? How do you resist the human tendency to believe what feels good, what sounds smart, what everyone else seems to believe?
His answer, developed four centuries before the first spam email, still holds. You learn to see the distortions. You study your own biases the way a pilot studies weather patterns. Not because you can eliminate them, but because you can compensate for them. You accept that your mind is not a clean mirror and you adjust accordingly.
The next big tech hype cycle is already forming. It always is. The names change. The slideshow fonts change. The promises stay remarkably consistent. And the people who avoid getting burned will not be the ones who are smarter or better informed. They will be the ones who, like Bacon, took the time to understand the machinery of their own belief.
And that, in the end, is worth more than any token.
