When everything becomes “AI”: the rise of Artificial Ignorance

It’s official, “AI” is the new “turbo”. If you lived through the 90s, you might remember everything from razors to shoe soles claiming to be “turbo-powered”. Today, we’re living through a similar marketing epidemic, except this time, it’s Artificial Intelligence. Or so they say.

Pots and pans are now “AI-enhanced.” Electric screwdrivers tout “AI torque adaptation.” Even bathroom scales are suddenly “smart” thanks to “AI-powered body analysis”. Never mind that most of these products have no connection to what AI actually means, for the average consumer, the label alone is enough to trigger curiosity, and for marketers, enough to justify a price bump.

What is and isn’t AI?

Artificial Intelligence, at its core, refers to the simulation of human intelligence processes by machines, learning, reasoning, and problem-solving. This includes technologies like machine learning, neural networks, natural language processing, and computer vision. These systems are designed to adapt and improve over time based on data.

What most of these “AI-powered” household tools are actually using is fuzzy logic, a concept that dates back to the 1960s. Developed by Lotfi Zadeh, fuzzy logic is a way to handle imprecise or approximate reasoning, for example, how a rice cooker might adjust cooking time based on internal temperature. It’s useful, yes, but it isn’t learning, it isn’t improving, and it isn’t AI.

In other words, fuzzy logic is a set of fixed rules for managing grey areas. AI, by contrast, is about dynamically learning from experience. That’s a massive difference, yet today’s marketing strategies have blurred the distinction to the point of erasure.

To illustrate this: a device using fuzzy logic might adjust heating levels based on a temperature range it was preprogrammed to understand, “if it's around 70°C, keep warming”. An AI-powered device, however, could analyze your usage patterns, food types, ambient temperature, and user feedback to optimize performance over time, learning and improving with every interaction. That’s not just semantics, it’s a functional, architectural gulf.

The price of misunderstanding

Why does this matter? Because the average consumer has no way to tell the difference. “AI” has become a magic word. It implies futuristic technology, intelligent behavior, and innovation, even when none of those things are present. This creates a false sense of advancement and leads people to overpay for products that are simply riding a wave of hype.

To make things worse, some of these claims go completely unchecked. Regulatory bodies in most regions haven’t yet developed clear frameworks to define what qualifies as AI in consumer products. This leaves the door wide open for manufacturers to make exaggerated claims, and they do.

A recent example: a certain “AI air purifier” that went viral online. Upon closer inspection, its “AI” feature was simply an air quality sensor triggering different fan speeds, something ionizers and smart fans have been doing for over a decade without the label. Yet the AI branding made it appear innovative and worth a 40% price premium.

Meanwhile, truly intelligent systems, actual machine learning models, language generators, or computer vision tools, get lumped in with glorified toasters. This cheapens the term and muddles the conversation about how AI is really impacting the world.

Fuzzy Logic vs AI: why it matters

Let’s go deeper. Fuzzy logic was revolutionary in its time. It offered an elegant way to express things in degrees rather than binary yes/no logic. “It’s warm” became quantifiable. It allowed appliances to act with some nuance, but it was always rule-based. There’s no “thinking”, no learning. It doesn’t adapt unless a human reprograms it.

AI, real AI, is capable of surprising its creators. It’s probabilistic, non-deterministic, and capable of generating insights or decisions from data patterns that weren’t explicitly defined. Systems like ChatGPT or image recognition tools learn from vast datasets and can adapt to new inputs in ways fuzzy logic never could.

Yet today, that distinction is ignored in favor of a single sticker: “AI Inside”.

It’s as if someone sold you a painting marked “original oil on canvas”, only to find it’s a low-res print with brush strokes added by machine.

The real danger of hype

There’s also a deeper danger: technological complacency. If people believe we already live in an AI-driven world, they stop asking critical questions. They stop learning. They stop distinguishing between innovation and marketing sleight of hand. And in that vacuum, companies are free to define “intelligence” however it suits them.

This miseducation isn't just about appliances. It creeps into broader social expectations. We start believing we’re surrounded by thinking machines, and that belief feeds paranoia, dystopia, or blind optimism depending on the narrative. It also leads to policymakers making decisions based on hype rather than technical reality.

In fact, we’re already seeing legislative proposals globally aimed at “controlling AI”, but many of these don’t distinguish between true AI systems and basic automation or analytics. The consequence? Overregulation of benign tech, and underregulation of genuinely risky systems.

The illusion of progress

The irony is that while marketers are racing to put “AI” on everything, many companies aren’t investing in actual AI at all. Why would they? It’s cheaper and faster to simulate the appearance of intelligence than to develop it.

A toothbrush that changes vibration speed based on pressure can be built with a $2 sensor and a control chip. Add the AI buzzword, and suddenly you’re selling a “smart oral health system” for 129 €. The customer feels like they’ve bought into the future. But they’ve really just bought the past, dressed in algorithmic cosplay.

This isn’t innovation. It’s inflation by illusion.

A call for literacy, not labels

We’re in a moment where technological literacy matters more than ever. The AI revolution is real, but it's happening in labs, in datacenters, in code. It’s not in your frying pan. And unless we learn to separate fact from fiction, we risk drowning in a sea of buzzwords, mistaking shallow gimmicks for deep intelligence.

If your screwdriver claims to be "AI-powered", ask yourself: what exactly is it learning from you? If the answer is nothing, well, you’ve got your answer.