When we hear about artificial intelligence, we often think of language models like ChatGPT, computer vision, or humanoid robots. But there is a branch of AI less known to the general public, which has been influencing our daily lives for decades: Fuzzy Logic.
An unappealing name, but a fundamental technology. Behind the automatic transmission of your car, the autofocus of the camera, or the intelligent climate control systems, there is often it: fuzzy logic.
What is Fuzzy Logic?
Fuzzy Logic, or “logica fuzzy,” is a mathematical system developed to handle uncertainty and imprecision, introducing the idea that something can be true only in part. Unlike classical binary logic (true/false, 1/0), fuzzy logic allows for degrees of truth. For example: saying that a room is “warm” does not imply a fixed temperature, but a fuzzy range – exactly how a human being reasons.
Invented in the 1960s by Lotfi Zadeh, it struggled to establish itself in the United States, despite being born there. As recounted during a panel of the AI Week 2025, American culture does not align well with “fuzzy” concepts, while countries like Japan have been able to leverage its potential more quickly and widely.
From the abstract to practice: where you use Fuzzy Logic every day
Many are unaware that the applications of fuzzy logic are already around us:
- Automatic transmission of the car: every time an automatic car decides when to change gear, it does so thanks to a chip that uses fuzzy logic to interpret speed, slope, pressure on the accelerator, and other factors.
- Cameras and smartphones: the frames that appear in the viewfinder when you take a photo? They use fuzzy logic to automatically focus on different areas in an “intelligent” way.
- Air conditioners: advanced climate control systems use fuzzy logic to dynamically adapt to the perceived temperature, the presence of people, and other environmental signals.
In short, every time a device makes a “nuanced” decision, with a margin of uncertainty, there is a good probability that it is using fuzzy logic.
Why it was underestimated
As highlighted in the panel, the name “fuzzy” – which in English sounds like “confused”, “vague” – did not help its spread. Alternatively, a name like “cloud logic” was proposed, which could have evoked more modern and less negative concepts.
Furthermore, the initial lack of practical applications slowed down academic and industrial interest. Only with the arrival of complex electronic devices and the need to automate non-rigid decisions did fuzzy logic find its space.
What is its role in today’s AI?
Although today there is much talk about AI based on neural networks and deep learning, fuzzy logic has not disappeared. On the contrary, it has been integrated into chips of many smart devices and still represents a valid approach for systems that need to make quick and interpretable decisions, often in real environments where data is uncertain or imprecise.
Furthermore, it connects to emerging streams such as possibility theory, which goes beyond probability to model uncertainty in a way that is closer to human reasoning.
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Conclusion
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Fuzzy Logic is the perfect example of a “silent” technology: it doesn’t make headlines like chatbots or robots, but it works behind the scenes to make our devices truly intelligent. It is a bridge between mathematics and human language, between precision and intuition.
In a world increasingly driven by AI, remembering that there are also different approaches – less spectacular but more human – is essential. And fuzzy logic, with its ability to reason “in shades,” still has much to teach us.