Much debate in the public domain centers around what is ‘the truth’, I call these type of debaters ‘truth claimers’. Much of the appeal to truth is an attempt to win a debate by exceeding the level of personal opinion. After all, no one can argue with the truth, right?
The words ‘facts’ and ‘reality’ are used as robust-sounding support for the truth claim, however when inspected more closely, all these terms appear to be rather vague/general/broad: Let’s see …
Reality
In the appeal to the reality, often facts are intended, especially when people look at the world from a materialistic viewpoint.
To the materialist, reality is limited to ‘facts’, the visible/palpable/measurable stuff . How facts are interpreted by people is simply not considered part of the materialist’s concept of reality.
Typical quote: “a stone remains a stone, regardless your perception of it. Q.E.D. the materialist”
Scientifically/technically, the materialistic line of reasoning is 100% proof, but philosophy has some interesting things to say about what reality is.
Nietzsche for example, denies objective reality by pointing out man’s dependence on interpretation.
I personally don’t consider objective & interpreted reality as mutually exclusive. I’m fine with acknowledging both aspects, only the objective aspect is usually not that interesting. After all, people rarely dispute objective aspects, they tend to dispute the interpretative aspects. Whether a stone is beautiful/ugly, mine/yours .. is usually a much more heated question then whether a stone is actually a stone.
That’s why I consider interpretative aspects as part of reality, because people follow up on their interpretations with action. We all know that differences in interpretation have real effects in the physical world: Discussions/ disputes/ arguments and even wars have been started because of a difference in interpretation.
The facts
First of all what is a fact?
->Wikipedia: Something that is verifiable real
Scientific proof is seen as the gold standard for fact verification, so what can we say about science? Well, outsourcing things to science has consequences. People tend to forget that
- Scientific instruments have an evolving sensitivity, so what is not a fact today may become fact tomorrow. Facts may not be as definitive as thought
- Science often delivers probabilities, not absolute certainty
- What you read about scientific research is usually the interpretation of the research data
- Scientific research is performed by people you don’t know
- ..in a way you don’t understand, and therefore cannot verify
- ..for reasons you cannot be sure of (e.g. corporate influence /financial interest). Of course a peer review system exists to ensure some quality and build trust in science, only this system is seen as flawed by criticasters.
So the very act of outsourcing facts to science already adds a layer of uncertainty to the result. Additionally, bullet 1. adds fluidity, bullet 2. adds a margin of error, bullet 3. adds actual interpretation, bullet 4->6 require trust and bullet 7. challenges this trust.
Hence, although facts are usually thought of (and used as) definitive truth, a closer look at how we define them (science) results in a level of uncertainty. Facts appear much less definitive then thought of.
The amount of facts is an issue by itself
Many people pride themselves on making ‘rational decisions based on the facts’. However, the sheer amount of facts making up all aspects of reality (and their potential interactions), is truly staggering. Taking all these facts into account with every decision we make is impractical, as taking a decision would take much more time then we have at our disposal.
The need for strategies
Because there are too many facts for us to process in realtime, we need to get creative and come up with strategies. The good news is that we can!
First of all we can aim to reduce the amount of facts somehow. Having less facts to consider, we can make our decisions faster.
Another strategy could be to upgrade our fact processing speed somehow.
Strategy 1: Determining relevance or priority, and filter non-relevant/ low-prio facts
This is an often used fact-reduction strategy. Non-relevant can be filtered out, and the rest can be ordered by priority and we only consider the top 10. As a result we end up with less data! 🙂
An example on relevance: When you you want to meet someone on the other side of the street, you better be aware of the cars while crossing the street, otherwise the cars might make you aware of their relevance to your reality.
In order to use the strategy ‘relevance’ to define ‘objective truth’, we should determine the ‘most relevant’ subset of ‘everything’ and assign that to ‘objective truth’. However, in doing so we immediately run into several problems:
- We don’t know what ‘everything’ is, stuff we are currently unaware of might still be very relevant
- Relevance often depends on the context, but objective truth is not supposed to depend on anything
- Even if 2. would be solved somehow, who defines ‘the most relevant subset’ , the ministry of relevance?
- The parts that are not relevant now might become relevant later, for any reason. This adds fluidity to our definition of ‘objective truth’, but the whole idea of ‘objective truth’ is that it does not depend on circumstances, that it’s always there and immutable: Hmm..
To avoid an Orwellian ‘ministry of relevance’, people should be left free to define their own relevance and filter out ‘irrelevant’ facts accordingly. The consequence of this freedom is that people’s selections will differ, and their subsets of reality too.
Therefore, application of the strategy ‘relevance’ will not lead to one ‘objective truth’ that can be shared and referred to in case of a dispute.
Leads to objective truth: #FAIL
Strategy 2: Taking a point of view
This one is related to relevance, because a point of view (or angle, or perspective) is a way to look at a situation that helps to define relevance.
Infinite points of view can be taken, each resulting their own set of relevant facts. Therefore, to actually end up with less data we need to favor a limited number of pov’s. In making these choices we face similar issues as with relevance (above), and an undesirable Orwellian ‘ministry of pov’ will be needed as well.
Leads to objective truth: #FAIL
Strategy 3: Making assumptions
Another, often used fact reduction strategy is making assumptions. Making generalizations based on ‘experience’, labels or stereotypes is a common way to do this. Problems are of course that assumptions can be wrong, as experience may not apply everywhere, and people will rarely completely satisfy a particular label or stereotype. Also personal ‘experience’ is subjective, and therefore different between people, so the resulting assumptions will be different too.
While making assumptions is a valuable and necessary tool to reduce the data set, it doesn’t lead to a unified ‘objective truth’. Next to a required ministry of assumptions, they are a too rough estimate to be a substitute to truth.
Leads to objective truth: #FAIL
Strategy 4: Outsource the fact processing
This strategy is based on upgrading the data processing speed. To do this, we outsource the interpretation of the facts to machines and the people that operate them. (E.g. scientists, or the tech industry using an Artificial Intelligent System (AI) ).
Note that outsourcing the fact processing implies outsourcing the conclusions as well.
Regarding AI
Note that an AI with sufficient capabilities isn’t built yet
But even when the AI gets more capabilities in the future, there are still many potential issues.
- How does the AI reason? The reasoning mechanisms will be programmed by humans, so what is their (corporate) interest/view point?
- Self learning AI has no pre-programmed reasoning, but what it has learned cannot be verified. Can it be trusted without this verification?
- Will the AI correctly handle important aspects like ‘context’? The same data leads to different conclusions, depending on context.
- Does the AI have access to all the facts? Are these facts correct? Will they remain correct??
- How to guarantee fact correctness over time, in such a way that the staggering amount of facts is not a constraining factor?
I don’t see this path leading to one objective truth, at best I see the emergence of an AI-powered ‘ministry of truth’.
Regarding science
I’m totally a fan of science, but first of all: Science doesn’t solve problems on the philosophical level. Second: Science is materialistic, which means:
That which can be observed objectively, and preferably measured, exists, the rest, does not.
Science has more limitations, which are listed above (under ‘the facts’). Again, I value scientific conclusions, but I still allow reasonable doubt. The uncertainties associated with science prevent definitive conclusions, and therefore I don’t reference science as the next bible. I definitely take note of scientific results, but I keep evaluating/matching each case with my own experiences & intuition.
..and yes, that leads to my own private subset of reality.
Leads to objective truth: #FAIL
Concluding
This investigation into the feasibility of ‘objective truth’ has shown that it is not a workable concept. The gold standard of fact verification, science, already introduces uncertainties in the definition of facts. The sheer number of facts & perspectives require strategies just to enable us to keep up with information processing in realtime.
Most strategies do not lead towards one shared objective truth. Some strategies cannot even be applied centrally, and when they can, doing so would require an ministry of truth. Facts & reality are supposed to make up objective truth, but both concepts have uncertainties in their definition.
Bottom line is that the sheer amount of facts forces us to make selection in realtime,. Any central selection leads a ministry of truth, and the only way to avoid it is to work with all the facts all the time. However, we can’t, as there are simply too many. -loop
As a result, allowing people free choice regarding info processing strategies inevitably leads to differences in perceived reality.
Photo Credit: diana_robinson Flickr via Compfight cc
