Why does the public misunderstand science and its philosophy?
To be a scientist is to be naive.
We are so focused on our search for truth, we fail to consider how few actually want us to find it. But it is always there, whether we see it or not, whether we choose to or not.
The truth doesn't care about our needs or wants. It doesn't care about our governments, our ideologies, our religions. It will lie in wait for all time.
And this, at last, is the gift of Chernobyl. Where I once would fear the cost of truth, now I only ask: ‘What is the cost of lies?’”
— Valery Legasov1, Chernobyl, Miniseries: Open Wide, O Earth
I’ll be upfront; I’m not a philosopher.
I’m an engineer covered in copious amounts of cat hair.
Philosophy asks a lot about what is, what isn’t and why. I know I’m covered in cat hair. That’s a fact. But how do you know I’m covered in cat hair? Because I wrote that sentence in ASCII and published it online? There’s something rather odd about the fundamental nature of our perception.
The philosophy of science precedes any discussion of scientific methods or findings.
What is science?
What does the science “say”?
Should we trust and follow the science?
Many residents in our technologically advanced society misinterpret science as “knowing the truth” instead of “searching for the truth.” Consequently, the word science transforms into a homonym that publicly carries two vastly different meanings, which becomes indistinguishable throughout conversation. In regard to scientific methods, literature, researchers, findings and products, we are often talking past each other.
A simple example of language ambiguity
How many circles are there?
3?
According to the SVG file on my computer there are 4, where one is the same colour as the background. If the circle is the same colour as the background, does it exist?
Well, it exists for me.
This is what the photo would look like if all circle objects were the same colour.
When the SVG is rastered as a PNG, the 4th circle vanishes. Which image is the correct image? The PNG or SVG? Am I correct when I say there are 4, or are you correct when you say 3? What does “correctness” even mean?
This is the curious nature of observation and the language game. What is the semantic difference of “image” between my observation and your observation? What about the word “circle”? Consider this scenario modelled using Wittgenstein’s2 private language argument, where each individual observer uses their own language. The difference is only apparent when the semantics for each label is spelled out explicitly.
From the diagram, it becomes apparent that the two parties have vastly different interpretations, but communicate using the same symbols. Below is functional pseudo-code illustrating how the number of circles (i.e., count_circ) differs depending on the semantics (i.e., Ʃ) used to interpret the image (i.e., img). Which one is “correct”?
What does it mean to be “correct”?
Correctness depends on what symbols mean, because symbols on their own carry no inherent interpretation in a system of private languages. Correctness also requires consistency (i.e., no contradictions), and is determined through a series of reductions (i.e., deduction, induction, etc.) to show correspondence with a truth premise.
There is no correct answer without an agreed upon frame of reference.
(Normally the customer is always right, which is the reader in this case — i.e., 3 circles.)
How does this tie in with the philosophy of science?
A framework for scientific models
If correctness requires a frame of reference, and there are innumerable perspectives and interpretations, then science is not “knowing the truth,” because an absolute truth is imperceivable. Instead, science is the practice of “searching for the truth” by constructing a model consistent with an observable subset of behaviours.
A model is a pair of symbols and their meaning (syntax, semantics) that can be tested through observation by constructing actions that stimulate predictable behaviour.
AXIOM 1: There exists an imperceivable absolute truth.
We live in a world bound by tangible laws.
Put your hand into fire and get burned.
Jump into a pond and get wet.
Put your genitals into a blender and become a liberal.
Why do we get burned? Why do we get wet? Why do we become liberals?
(I jest :p)
The absolute nature of our world is unknowable, because we cannot perceive every possible state or frame of reference and omnipotently observe all effects from all causes. Our only option is to form reproducible models, observations and actions.
This leads into the second principle regarding our perception.
AXIOM 2: Perception is a symbolically bound model.
We are limited to symbolic images created through our actions and observation.
The real world is a propositionally consistent and complete space that is unknowable and symbolically unbound, whereas our perception is inconsistent, incomplete and bound by symbols formed through observation and action.
And unfortunately, our perception is not exclusively an image of reality.
If you read a scientific model, that has tables, charts and nice little pictures from a fancy journal, your new perceptual model is not that scientific model, but a derivative of it. Likewise, a friendly conversation can change your perception to form a new model derived from dialogue. Both of these cases are dialectics, where a dialectic is a persuasive dialog using linguistic and rhetorical devices, which alters our perception. These dialectic produced models are not guaranteed to be consistent or in correspondence with the true state of reality, but are nominally how we develop our understandings of the world. The image reflected in your mind is not reality.
Carefully consider this concept, because it has an unsettling implication.
Inherently, we are all perceptually separated from the truth and the real world. This implies that everything “you think you know” is an illusory model that may not have any correspondence with reality. Of course, we do get periodic reflections from reality through observation and action, but there is no way to tell what is, or is not, an illusion.
Or is there?
(Daniel Dennett3)
AXIOM 3: Models must be consistent with reproducible interpretations.
Firstly, scientific models must be consistent, where its symbols are unambiguous and precisely correspond to a well defined meaning. A model that has any internal contradiction cannot be used to predict behaviour.
Secondly, interpretations, which include observations and actions, must be reproducible. Interpretations must use consistent measurement systems with a fixed point of reference and an inductive scaling relative to this reference. Numeric measurement systems naturally satisfy this requirement, and are anchored to immutable physical properties in the case of physical measurements. Non-numeric measurements typically use a control (or baseline) as the point of reference.
Example 1 : Control group vs experimental group.
A control group is the fixed point of reference to compare all observations collected from experimental groups. The experimental groups are defined with model(s) and parameters, and use the control group as a reference to validate observational significance.
Example 2: Temperature measurements in Celsius.
The fixed point of Celsius is 0°C (0 is also a numerical fixed point), which references the freezing point of water at 1 atm. The scaling is created by defining the boiling point of water as 100°C. Every measurement in Celsius is a scaled reference to heat energy stored in water at a reference, which is a practical measurement for many thermofluid processes.
Example 3: Thermoelectric thermometer.
A thermocouple is a device that places two different electrically conducting materials in a junction (e.g., Fe / Cu), and uses the Seebeck effect to generate a voltage across the junction. The ratio between the temperature difference and generated voltage (i.e., ∇V) is called the Seebeck coefficient (i.e., S), which depends on the materials selected. Temperature is determined by using a known voltage at a reference temperature, and calculating the temperature (i.e., ∇T) by measuring the voltage using ∇V = - S∇T. This voltage can be amplified through circuits to provide analog or digital readings.
Returning to the example
From the prior SVG vs PNG example, there are two distinct models that interpretations are performed on, which is represented by the difference in value from the count_circ function parameterized by the frame of reference.
AXIOM 1 is usually trivialized, but it’s important to recognize that some answer exists and work is required to model the problem in a frame of reference.
AXIOM 2 helps us recognize the language game problem, which in this case requires two models for the author and reader respectively.
AXIOM 3 is the count_circ function applied to the image for both models. The implementation of the SVG interpretation could use the SVG XML schema as the point of reference, and digitally count the number of circle tags in the document. There are a few options for the PNG implementation.
For example, I could:
Overlay a Cartesian grid and compare y² + x² = r² within some acceptable error.
Use a "unit circle” template and compare the scale difference.
Use a group to manually recognize circles, and conduct a circle recognition control.
Use validated and certified image recognition software.
(I would certify it myself via control.)
(This is obviously overkill but you get my point.)
The specifics of what is an acceptable interpretation is outside of the description of this framework, but the primary requirement is that interpretations are reproducible. I should be able to document each model and its observational methods, and use an independent group to reproduce the results.
Scientific models in the real world are complex and nuanced. They are not laid out explicitly using a framework like this, and tend to be tribally encoded through best practice, experience and domain specific jargon. However, by understanding the overarching philosophy behind the scientific discourse of “searching for the truth,” this framework helps alleviate the discrepancy with the silly notion of “knowing the truth.”
Discussion
It’s easy to label someone as ignorant or a conspiracy theorist, and recognize how disconnected their perception of reality is from yours. But what if culture, and society itself, fell into a perceptual dialectic trap, where it disconnected itself from reality. Living in a technologically advanced society does not imply that any social norm corresponds with the true nature of reality.
Consider some words like “schools,” “hospitals,” “teachers” and “doctors.”
Do the meanings we socially assign to these words align with their behaviours in reality?
Are schools teaching appropriate material that helps kids become functioning adults?
Are hospitals operating the way we think they operate?
Are teachers the kind of people we think they are?
Doctors …?How would we know if the rest of society doesn’t ask these questions?
Does our government operate the way we think it operates …?
When someone says “trust the science,” what exactly are we trusting? Which set of syntax, semantics and interpretations do we trust? Which frame of reference do we trust? Are we trusting a tested technical model or a dialectical interpretation?
Science is built on the premise of systematic doubt, because our perception has an inherent separation from truth and the real world. All scientific claims must be met with doubt and skepticism, because the purpose of any scientific model is to reproducibly demonstrate these claims to reveal the true nature of reality. If not, then any so-called “scientific model” is no better than a dialectical, which is not real.
Scientific models are not replacements for reality. When we recognize something unusual, a problem or a risk, then modelling can help us precisely identify the problem using structured language and measurements, but people often get confused by titles, credentials and other fancy names.
Credibility4 is not correctness.
In the exposition Tweet, it’s easy to pick sides and start throwing around names, accusations and credentials, but none of that is correctness. Using the private language argument, it becomes clear that picking sides based on perceptual bias has absolutely nothing to do with correctness. Public dialogue is a drama played out along a dialectic, where tension and conflict further separates us from reality.
Reality matters.
Dr. Kim McGrail5 provides some informal reasons explaining the excess death in 2021, which were classified as not COVID-19 related. However, these reasons do not carry through into 2022, which was relatively less restrictive than 2020 and 2021.
What is that massive spike in Jan. / Feb. of 2022?
Was there any event in the fall of 2021, possibly beginning with “man” and ending with “date” that could have contributed? How would we know? There is also a massive increase in Jan. / Feb. 2021; is it related or not? Shouldn’t the vaccines be flattening out the curves closer to the “expected” line? While these graphs and data are not reality, they are a closer reflection than subjective interpretations. My bias is a model, just as any bias from UBC is also a model. Clearly this data calls for thorough technical modelling, analysis, and financially independent investigations free from conflicts of interest. Why does it matter so much?
These were real people who died.
They are not just numbers to be measured as some data aggregated “excess” event.
The acceptance or rejection of a paper doesn’t matter. What matters is the search for the truth, and the recognition that fully knowing the truth is an impossible feat that we can only model through our limited capabilities. Despite those limitations, we should never stop reaching for that light, because only darkness awaits us in lies.
Too many are comfortable with their little lies that they easily accept bigger and bigger ones. Eventually we find ourselves living in a false reality run by master playwrights of fiction. Your friends, neighbours, and the structure of everyday life itself becomes nothing more than a scene in someone else’s twisted fantasy.
Recognizing our false reality is painful, because the truth doesn’t care. The truth will burn away all the lies the moment they’re exposed, which is something most egos cannot bear. Is it worth exposing the truth? Is it worth living a lie? At what costs?
We should not fear the cost of the truth, but rather the cost of lies.
Valery Legasov (Sep. 1, 1936 - Apr. 27, 1988) was a Soviet inorganic chemist and a member of the Academy of Sciences of the Soviet Union.
Ludwig Wittgenstein (Apr. 26, 1889 – Apr. 29 1951) was an Austrian philosopher who worked primarily in logic, the philosophy of mathematics, the philosophy of mind, and the philosophy of language.
Daniel Clement Dennett III (born Mar. 28, 1942) is an American philosopher, writer, and cognitive scientist.
Credibility — “capacity or condition of being believed.” i.e., Believability.
Kimberlyn McGrail is a Professor in the UBC School of Population and Public Health and Centre for Health Services.
Yup. The religious impulse doesn’t go away even after god is dead. People have been filling the god shaped hole in their being with all kinds of nonsense, but we’re in this weird in between place where we can’t really go backwards to the old-timey religions, but there’s nothing sophisticated to run towards yet
Very interesting and intellectually stimulating essay. Lot of work! I love the “Put your genitals into a blender and become a liberal.”