Deduction does not exist in reality.

Read this dialogue with ChatGPT to see why:

https://chatgpt.com/share/670e7f9e-d1d0-8001-b1ef-3f4cbc85b9...

It’s a bit long winded and gets into much more detail but I will post ChatGPT’s most relevant response below:

You’re right to point out that complexity alone doesn’t necessarily rule out deduction. Deduction can, in principle, work even in highly complex systems as long as the premises are perfectly known and logically valid. So the real issue with why deduction fundamentally does not exist in reality comes down to the nature of human knowledge and the way we interact with reality itself. Here’s why deduction struggles at a more fundamental level:

1. The Problem of Incomplete Knowledge

In mathematics and formal logic, deduction works because the premises are often abstract, well-defined, and complete within a given system (e.g., “All triangles have three sides”). In contrast, human knowledge of reality is never complete. We can never be sure we have all the relevant facts, laws, or variables. Even with the most advanced observational tools, there are always things we don’t know or can’t foresee.

• In mathematics: Premises like “All even numbers are divisible by 2” are universally true within that system.
• In reality: We might observe many instances of a phenomenon and think we know the rules, but there could always be exceptions or unknown factors (as in the Black Swan problem).

Because we cannot ever have perfect, complete premises about the world, any deductions we make based on our observations are always vulnerable to being undermined by new information.

2. Reality is Unbounded and Open-Ended

Mathematical systems and formal logic operate in closed systems with clearly defined rules. Reality, on the other hand, is open-ended and continuously evolving. There’s no fixed “set” of all knowledge about the universe. What we take to be the laws of nature today might change tomorrow with new discoveries, so the premises we use for deductive reasoning in the real world are inherently uncertain.

For instance, before the discovery of quantum mechanics, classical mechanics seemed to perfectly describe the physical world. Once quantum theory emerged, the premises on which classical deductions were made had to be re-examined.

• In a closed system (like math): You can set the premises and they remain stable.
• In reality: The premises are constantly subject to change or reinterpretation as we learn more.

3. The Problem of Infinite Regress (Uncertainty in Premises)

Even if you think you have solid premises to base deduction on, those premises themselves depend on other premises, which in turn depend on further premises. This infinite regress means that you can never be certain that your foundational premises are truly, absolutely correct.

For example:

• You might reason deductively that “all swans are white” because all observed swans have been white.
• But this premise itself is based on inductive observation, which is inherently fallible.
• Even if we had observed all swans ever seen by humans, we still couldn’t deduce that “all swans are white” without being omniscient, since future discoveries could prove otherwise.

In the end, any attempt to apply deduction to reality rests on premises that ultimately cannot be guaranteed to be perfectly, universally true, leading to a breakdown in the validity of deduction in real-world scenarios.

4. The Distinction Between Reality and Abstraction

Mathematics and logic are abstract constructs—they exist independently of the physical world and follow internally consistent rules. Reality, on the other hand, is not an abstract system; it is something we experience, observe, and interact with. This creates a fundamental mismatch:

• Abstractions (like mathematics) allow us to create premises and rules that are certain, because we define them.
• Reality doesn’t conform to these strict, definable rules—it involves uncertainty, chance, and emergent properties that abstractions can’t fully capture.

Because reality is not abstract, we cannot reduce it to a system of premises and rules in the same way we can with mathematics. Any attempt to do so will always miss something essential, undermining the validity of deduction in practice.

5. Chaos and Uncertainty in Physical Systems (ChatGPT is wrong here, I deleted it… it references chaos theory which is technically still deterministic, only quantum theory says things are fundamentally unknowable so ChatGPT is right from the perspective of fundamental uncertainty but he used chaos theory wrongly here in his reasoning)

Conclusion: Fundamental Uncertainty and Incompleteness

The fundamental issue with deduction in reality is that human knowledge is inherently incomplete and uncertain. Reality is an open, evolving system where new discoveries and unforeseen events can change what we thought we knew. Deduction requires absolute certainty in its premises, but in reality, we can never have that level of certainty.

At its core, the reason deduction doesn’t fully apply to reality is because reality is far more complex, open-ended, and fundamentally uncertain than the closed, abstract systems where deduction thrives. We cannot create the perfect, unchanging premises needed for deduction, and as a result, deductions in the real world are always prone to failure when confronted with new information or complexities we hadn’t accounted for.