Truth is a Myth


The useful invention

Truth is a useful invention. However, often times it lacks precision when used in philosophical conversation. Many of us experience cognitive dissonance when trying to wrap our head around what truth actually is. Not which truth is true, but the nature of truth itself.

I’ll partially admit that the title of this post is clickbait. But on the hand, it is descriptive. “Truth is a myth” is simply saying that truth doesn’t seem to exist…explicitly!

It seems to be in the same class of terminology as perfection. It is a hypothetical idea of…well exactness. Perfection does not exist. Only in the imagination can one hypothetically reckon with the reality of perfection (this last sentence is more philosophic-poetry than anything, although true, don’t think too hard).

Truth exists

Truth exists, but the modern usage of the term is more often than not a convoluted expression of one’s instance of belief. But rationally, truth’s trueness can only be known through the trueness of its calculation.

“How can you say that ‘truth can only be known through calculation,’ if you yourself are making a statement of truth without providing its calculation.”


And this is the point I wish to make. There is truth and there is truth.

The first idea of truth (T1), and the most popular one, is truth being its practical and probable usage (T1 probable has accuracy, but doesn’t necessarily have precision). The second form of truth (T2), is truth being the hypothetical concept of exactness (T2 would have both accuracy and precision). While everyone wants what they believe to be T2, it is probable that most truths are of type T1. In the real world, it is impossible to calculate all of the variables. So we do our best to estimate so we can come up with an accurate truth statement. Especially in philosophy.

2 + 2

If I say 2 + 2 = 4, I believe we would both say it is a T2 statement. And I would say evidence for that would be in a capacity to make utility of that concept with precision. Say we were given 21.5698783 + 3.1415926. I would say we could both do the math and have the exact same answer. T2-type truth.

But if we bring such values into the real world and expect them to be T2-type, we have to account for so many different variables, that when we use such a true statement it is under the assumption that we are accounting for all relevant variables and quantities to give us a true answer. Where did we get 3.1415926? How did we qualify it as an accurate value? Did we “round up”? If we did, then even if 3.1415926 is an accurate value, it wouldn’t be exact. That is to say, it would be be precise enough to represent the original value. Which, in this case, is infinite: π


And this is where the other kind of truth exists. It exists in a real world with infinite numbers and uncountable variables that cannot all be accounted for. But over the millennia, we’ve come up with solutions that give us a probability of understanding something with varying degrees of accuracy and precision. It is here that we use the term truth. It is here that truth can be so complicated and infinite that it has to be presumed and is often convoluted and contradictory. We can deem a belief as true to convince ourselves and fellow thinkers that the idea is so probable that we we ought to inflate such an idea to a state of inconvertibleness—like 2 + 2 = 4, or that π is an infinite number.

What is truth?

I believe the best way to understand truth is to understand its types. I used T1 and T2 to briefly distinguish two types of truth that I found meaningful—as they seem like two popular but polar types within western-American culture. And when defining, or identifying a type of truth, one should understand its quality (its accuracy and precision), and its probability (the calculable possibility of the idea).

And while most of us participate in the concept of T1 (this blog post is an example), I believe not being able to distinguish T1 from T2 misses the trueness and utilities of both, and what the nature and function of truth really is. That is why I say “truth is a myth.” What I mean is that it is an over simplification and convolution of the scope and domains of trueness, belief, and knowledge. I’d prefer to call T1 possible truth, or stick with the terms we’ve already created for it: belief or theory.

I hope I’ve conveyed that the popular notion of truth really is an imprecise idea to communicate radical conviction of a theory—at least in the popular majority—but understanding truth as a logical theory for idea prioritization will grant its theorists (people) a key to successive evolution; both in technological advancement, and wisdom in impartial leadership.

To summarize and expand

It would make sense that this idea, which is not my own, would only hold validity if successive evolution is a value. If it’s not, enjoy your coffee, your work, and life—and know at times…I envy you.

For many of those whom understand the value of T2-type truth, you will find them investing time and resource into learning, teaching and developing methods and theories of calculating sound probabilities. And today, this is done with computers. This is the age of enlightenment through calculating probability using true statements: 1 or 0.


Key-terms with my own definitions

Belief – conviction of an intuitional probability

Popular “truth” (T1) – radical conviction of an intuitional probability

Logical “truth” – sound calculation

Probability – the degree to which something is probable based on calculation (logical or intuitive)

Logic – boolean calculations that can be performed apart from their theorist(s)

Intuition – cognitive calculations based on the theorist’s correlation of experiences

My intuition believes this is the best way to understand the nature and function of truth:

  1. The distinction between logical truth (math + data) and  belief (conviction of idea)
  2. The distinction between accuracy and precision
  3. The strengths and pitfalls of human calculation (specifically memory and error rates)