In a world saturated with data, we’re used to thinking of information as something we store, process, and exchange. But what if information doesn’t just describe the world—what if it explains how thoughts become meaningful in the first place?
Welcome to the world of informational semantics—a theory in the philosophy of mind and language that asks a deceptively simple question: What makes a thought about something? How does a pattern of neurons, or a spoken word, carry the meaning it does?
Informational semantics suggests that the answer lies in causal information-carrying relationships. In other words, a mental state has content because it correlates in a certain way with the world. Meaning, in this view, is not assigned or invented—it’s grounded in natural information.
In this post, we’ll explore the key ideas behind informational semantics, how it accounts for mental content, and what it reveals about how minds hook into reality.
The Problem of Mental Content
To think at all is to think about something: the weather, your plans, a memory, a person. But what makes a thought represent what it does? Why does your belief that “the sky is blue” point to the sky, and not to something else?
This is known as the problem of intentionality—how mental states come to be about things. It’s central to understanding language, consciousness, and cognition.
Informational semantics offers a naturalistic answer. It was most famously advanced by philosopher Fred Dretske, who argued that representation is a matter of carrying information.
The Core Idea: Meaning as Information-Carrying
Informational semantics begins with the insight that natural systems carry information. For example:
- Smoke carries information about fire.
- Tree rings carry information about age.
- Thermometers carry information about temperature.
Dretske extended this idea to mental states. If your belief that “it’s raining” was caused by the fact that it’s raining, then that belief carries information about the rain. The belief’s content is determined by what it reliably indicates in the environment.
So, in this model:
- Beliefs are internal states that carry information about external conditions.
- A state means what it has been naturally selected or trained to indicate.
This allows for a naturalistic theory of meaning—one that doesn’t rely on mysterious mental stuff, but on informational relations that science can study.
Informational Semantics in Action
Imagine a frog that snaps at small, dark, fast-moving dots. These dots are usually flies. The frog’s perceptual system has evolved to detect and respond to visual patterns that indicate prey.
According to informational semantics:
- The frog’s neural state represents “fly” because that’s what it has historically carried information about.
- Even if the system misfires (and the frog snaps at a pebble), the intended content is “fly” because of the informational relationship built through evolution.
This same logic can be applied to humans:
- If your visual system detects a red light and you stop your car, it’s because that sensory input reliably carries information about a traffic signal.
- Your belief that the light is red is informationally grounded in a causal process.
Advantages of Informational Semantics
1. Naturalism
Informational semantics fits neatly into a scientific worldview. It avoids appeals to mysticism or metaphysical dualism and offers a framework that neuroscience and AI can use.
2. Explains Misrepresentation
You can believe something false—just as a thermometer can misread the temperature. Informational semantics explains this by saying that a system can misrepresent when it fails to carry accurate information, even though it was designed or evolved to do so.
3. Links Mind and World
It helps explain how mental states are anchored in reality. We don’t invent meaning in a vacuum. Our thoughts are formed through interaction with an information-rich environment.
Challenges and Refinements
Informational semantics isn’t without its difficulties.
1. Disjunction Problem
What if a neural state is caused by multiple things? Suppose the frog’s snapping behavior is sometimes caused by flies, but sometimes by shadows or pebbles. What does the state really represent?
This is the disjunction problem: how do we decide which cause the content refers to when many are possible?
2. Context Sensitivity
Information can be context-dependent. A red light means “stop” in traffic, but “recording” in a studio. Informational semantics needs help from pragmatics or social norms to fully capture meaning in language and thought.
3. Normativity of Belief
We evaluate beliefs as true or false, justified or unjustified. Can an informational state carry this normative force, or does that require a richer theory of rationality and intention?
Many philosophers have tried to address these issues by integrating teleology (evolutionary purpose), inferential role semantics, or computational models into the informational framework.
The Broader Picture: From Signals to Sense
Informational semantics helps us see the mind not as a ghost in a machine, but as a signal processor rooted in nature. Our thoughts don’t float free from the world—they’re shaped by it, responsive to it, and (ideally) accurate reflections of it.
In an age of artificial intelligence and cognitive science, this view becomes ever more relevant. When we build machines that respond to the world based on input signals, we are—whether we realize it or not—designing systems with informational content.
The difference, of course, is that in us, information doesn’t just move. It matters. We don’t just react to signals—we interpret, question, and transform them.
Final Thoughts: From Signals to Meaning
Informational semantics offers a powerful idea: that meaning arises not from magic, but from patterns of reliable correlation between mind and world.
It reminds us that to think is to be connected—to take in the shape of things and hold that shape, in some fragile but functional way, inside our minds.
And perhaps that’s all we need for meaning to begin: a system that tracks the world, a perspective that holds onto patterns, and a self that slowly learns what matters, and why.