Epistemology: What can we know at all?

What can we know at all? Is the scientific method based on empirical observations a reliable way to gain knowledge, an understanding of the truth? Or is the method fundamentally imbued with uncertainties? Is an objective reality possible at all? In this provocative talk, I will challenge your belief systems and rock the foundations of your knowledge. Fasten your seatbelts!

Good morning ladies and gentlemen,

Welcome to my presentation on the topic of Epistemology.
For those who don't know me, my name is Antonin Tuynman, I am an examiner in biotech in the field of clinical diagnostics.

A couple of months ago Liz asked me to give a talk on my book "Transcendental Metaphysics" and later on my co-authored book "Is reality a simulation?" As the topics discussed in this book border on the esoteric, I was a bit hesitant, but there are actually a number of topics I deal with in these books, which might be of relevance to you. I decided to split my originally prepared talk in 2 parts: the first on Epistemology or the study of what we can know at all and the second about From Information to a Theory of Everything.

When you hear the word "metaphysics" you probably think of topics like "soul", "afterlife" or perhaps even "consciousness". The title of my book Transcendental Metaphysics is actually an intended pun. It was my intention to build a bridge between science and spirituality, by showing that they are connected rather than completely independent from each other. I actually argue that we should redefine these terminologies.

The reasoning goes as follows:
If Reality includes everything which influences reality, there can be no real things or things of relevance outside of reality. For if they would influence reality, they would be included by definition and if they wouldn't, they are of no relevance to us at all and not worthwhile to be considered "real".

Meta means beyond or outside of and metaphysics beyond or outside of physics. In a similar reasoning as I just made for reality, if there is anything beyond the physical which influences the physical, it should be considered to be physical and if it does not influence the physical, it is of no relevance whatsoever.

The terminology transcendental also means "going beyond". A certain branch of theology has hijacked the terminology "transcendental" by postulating that there is a God who is wholly independent from our reality. If it/she/he has no connection with our reality, it is of no relevance, if it does it is not transcendental in their definition.

In these talks I will show you that we can perhaps redefine these terminologies slightly so that they can still be useful.

After this introduction I now start with the actual topic of today: Epistemology: or the study of what can we know at all.

How do we know things, facts? We may read, learn or hear certain facts and believe these on the basis of an authority, such as "it has been scientifically proven.." or "the sacred book is the word of God...", but such knowledge gathering is second hand, we haven't actually been able to verify it ourselves.

The most general direct ways we have of gathering knowledge are based on empirical observations and the logical inferences we can make on the basis thereof.

Logic, a tool of reason, has three modes: deductive, inductive and abductive:

A deductive reasoning starts with a factual premise which is true for all members of a class such as:

All men are mortal.
To this an instance of the class is compared: Socrates is a man.
and then the general rule is applied to this instance and an inference is made:
Hence Socrates is mortal.

In the inductive mode we start from an observational premise such as:

The sun rises every day.
We compare this with an instance: Tomorrow is another day.
and infer a prediction: tomorrow the sun will rise.

In the abductive mode the starting premise is often conditional:

If it rains, the grass gets wet.
instance: the grass is wet.
inference: it has rained.

But this mode is a logical fallacy, because the grass maybe got wet because the sprinklers were on.

Deductive reasoning claims to start from facts, but except for mathematics, if we look at the physical world, all facts we know were once gathered by observation. In other words, all deductive premises are the result of empirical observations as well. So it seems that all knowledge we can rely on, is ultimately grounded in observations:

We have a hypothesis, we gather data, we observe a pattern by connecting the dots and we come to a predictive theory.

But there are a number of problems with this approach.

First of all we are biased by our hypothesis: we look at reality in a certain way, because we expect it to be in a certain way. R.A.Wilson, one of my favourite authors used to say: "The prover proves, what the thinker thinks": What you are looking for, you'll find evidence for. Or you'll try to make your observations match your ideas.

Secondly, there are multiple ways to connect the dots. I'd like to illustrate this with a few slides: There is for instance the famous problem of aliasing, whereby more than one sinusoid curve can perfectly fit a set of data.
Usually, when we try to fit a curve to a set of data we use statistics. but what kind of curve should we apply to connect the dots? a linear? a sinus? a polynomial? Scientists often use the principle of "Occam's Razor", which states that the hypothesis with the least number of assumptions is the most likely. But this can unduly cast away complex explanations where complexity is involved.

Scientists adhere to certain theories as beliefs. A ruling scientific theory is called a paradigm. But paradigms can be challenged by anomalous data. These are often called "outliers". What to do with such points? Are they artefacts? Should we disregard them? Or do they reveal more complex mechanisms?

As the body of anomalous data increases, it becomes more difficult to maintain a paradigm. Yet it often takes until a complete generation of scientists has died until a new paradigm is accepted. Why? because of dogmatism.
Furthermore, there is also nepotism in the scientific world. It's easier to get your article peer-reviewed, if you're friends with one of the peer reviewers or if you know one of the editors of a journal. And there is the problem that here are more and more pseudo-scientific journals claiming to be scientific, where scientists pay to get published without proper peer-review.

Moreover, science is analytical: we only look at parts of a problem, from a certain perspective. We fail to see the whole picture. This reminds me of the Elephant parable from Hinduism and Buddhism:
There were a number of blind men touching an object: One said it's a hose, the other one said no, it's a pillar, yet another one said it's a broom, and in fact they were all touching different parts of the same object, which was an elephant.
This notion of perspectivism is also clear from this slide: The same image is considered as rabbit and duck depending on the way you look at it.
Even better here, we see that seemingly mutual exclusive perspectives of a circle and square can be reconciled and transcended in the higher truth of a cylinder. And it is in this way that I'd like to redefine the word transcendental:
A higher dimensional fact that includes and reconciles seemingly mutually exclusive perspectives thereof. Science is analytical and not holistic, so that we usually don't observe the whole truth of a phenomenon.

Then there is also the problem of measurement uncertainties and inaccuracies: Is our set-up correct? Are our instruments well calibrated? Is our calibration method valid and accurate?

Moreover certain phenomena have inherent uncertainties, such as the Heisenberg uncertainty in physics: You can't know exactly the position and the speed of a subatomic particle simultaneously. You can determine either of them exactly, but never both together.

There are incomputability problems: Certain numbers cannot be reduced to a simple algorithm that takes fewer digits than the number of digits the number takes itself. Certain problems cannot be decided computationally to lead to a correct yes-no answer and there is no algorithm possible that correctly determines whether arbitrary programs eventually halt when run.

Linked to this is Gödel's incompleteness theorem: There are certain mathematical statements which can be true (or not) but for which it cannot be proven that they are true or not. However this fact can be proven, which is this theorem. This means that even mathematics is not capable of leading to a complete knowledge.

Why is this important? Because it shows that we can fundamentally never get a complete picture of reality, we'll always be looking at parts from a certain limited perspective. We can't even be certain about the "truth" of most patterns. Worse, certain quantum mechanical experiments, which I'll discuss in the next talk, even strongly challenge the notion of a so-called objective reality. If you change the way you look at things, the things you look at change, meaning that there is a subjective influence of the observer, which implies that physical truth is relative.

Apart from the truth that everything is relative, there may not be an absolute truth. It is sometimes said that Epistemology looks for the overlap between belief and the truth. But if there is no such absolute truth, how can we be so sure we have found this overlap? How can we be sure that we are not hallucinating or dreaming up our reality? Or that we are maybe living in a computer simulation as Neo in the film the Matrix?

Can't we be sure about anything? Well, if we have a technological application of a theory, at least we have lifted our knowledge to a higher level than a mere predictive theory. The application shows that we master at least this part of what we call real. This is why in my book I speak of Tech-know-logy or Technovedanta, in which Vedanta stands for the Hindu word of the complete body of all knowledge.

Buddha once said doubt everything, but then doubt the doubt.

Having said this, in my next talk I'll try to come to a more solid foundation of knowledge based on Information Theory.

Thank you for your attention.

Any questions?

By Antonin Tuynman Ph.D. Talk given on 18-09-2018 in Rijswijk, The Netherlands.