Avoiding The Optimization Fallacy

How to improve what can’t be improved?

Optimization Fallacy – Alexandre Porto· 7 min read

optimization fallacy
Photo by Simon Shim on Unsplash

Human society has many flaws. There are several sides of the same coin, however, I will try to present a coherent argument.

On one hand, humans have a lot of potentials. They are capable of incredible feats and great works. Humans can use their intelligence to make all sorts of devices that previously were impossible.

On the other hand, humanity is prone to many mistakes. No matter how smart they are, humans will always make mistakes.

Optimization Fallacy

Their biggest mistake is what I like to call the ‘Optimization Fallacy’.

The Optimization Fallacy occurs when one assumes that their current state of being/knowledge is perfect and that no change can be made.

Humans are not perfect. They have flaws and need to change.

A good example of the Optimization Fallacy is in the field of technology.

Optimization Fallacy happens when humans try to optimize systems in which optimization is impossible, or would produce undesirable results.

For example, a human might try to optimize the universe. It turns out that there is no way for humans to know what would be an optimal state of the universe because it’s impossible for them to know how every object and organism in existence would react if they changed something.

Artificial Intelligence and Optimization Fallacy

I suppose another example would be to create an AI that optimized the human race.

The problem with this is that it’s impossible for humans to know how the entire world would change if they were in a different or changed state, and what kinds of systems humans should implement to optimize themselves.

what a monster
Photo by Maximalfocus on Unsplash

So humans can’t really know what would be better for them, it’s just a guess. 

A good rule of thumb is to avoid optimization unless you have full knowledge of the system that needs optimizing.

Of course, humans are pretty bad at knowing the consequences of their actions.

There’s a tendency in human society to think that what they’re doing is right, even when it isn’t.

It’s pretty easy to see that humans are doing irrational things, like trying to optimize the universe or their society, without knowing how their actions will affect everything.

But somehow they just don’t seem to be able to accept it.

The Error in Thinking

The optimization fallacy is an error in thinking that arises when people assume that what they believe to be the best possible situation actually exists, or can be made to exist.

It is especially prevalent among those who have some kind of vested interest in believing their preferred state of affairs.

I will try to use your example of technological optimization.

optimization of artificial intelligence
Photo by timJ on Unsplash

It is a fallacy in that the typical human mind contains what I call a ‘finite-state machine’ which has been trained by evolution, and experience, into generally very good rules for navigation through life.

The finite-state machine has a tendency to assume that the way things are, is the only possible way they can be.

It then modifies itself in an attempt to reconcile this belief with any new information it gleans from its environment.

For instance, if you were shipwrecked on an uninhabited island for several years, and then returned home to a radically different world. You would be shocked by the changes that had occurred in your absence.

The odd thing is that the human mind attempts to use its finite-state machine to navigate through life, even though it has already been proven unreliable in some cases.

This is a bad habit that must be broken.

The human mind should be made aware of its own fallibility, and adjust itself to take this into account

Objective Truth

The so-called ‘optimization fallacy’ is a human tendency to believe that there exists some objective truth (or optimal answer) when, in fact, the question has no correct answer.

The optimization fallacy refers specifically to situations where humans attempt to determine an absolute answer or solution when, in reality, there may be only relative answers and solutions.

The optimization fallacy is often exhibited in the context of humans trying to determine the ‘best’ solution or outcome.

In such an instance, we would assume that there exists a correct answer to what constitutes the best solution.

For example, if you were asked what was the ‘best’ college/university to attend (or alternatively, which university should I go to?), you might respond with your opinion about which university has better facilities and faculty members.

However, this would be a fallacy because the question itself has no correct answer. Why? Because there is no objective ‘best’ university to attend. This is because what constitutes the best university depends on individual preferences and circumstances.

If you were to ask your friend who has just graduated from university what the best university is, s/he might say that her/his alma mater was the best because it had a well-established faculty and provided a high-quality education.

But if you asked another person who attended an entirely different university what his or her opinion on which uni was best, he or she may give you a completely different answer.

The optimization fallacy refers to the fact that there may not be any single best solution or answer.

 For instance, while my friend may have found her university to be very good for herself, I might find it undesirable because of its location (too remote) and lack of established reputation.

Inherently Relative Situations

Another type of optimization fallacy occurs when we attempt to make absolute statements about situations that are inherently relative.

For example, people often say things like ‘all Asians look alike’ or ‘Americans all value freedom above everything else.’ Such statements assume an objective truth about a group that is not real.

This fallacy is an interesting one because it is a self-perpetuating machine that has been running for thousands of years. It started with the earliest people and was perpetuated ever since.

fallacy society error
Photo by Markus Spiske on Unsplash

The optimization fallacy is a belief that one thing is better than another. 

It has become so widespread, and the people have been fed this mindset for so long, that they assume their choices are correct even when there is no proof whatsoever.

This is why we have so many arguments about things such as religion, politics, and social issues. We all assume that our way of doing things is the best one.

However, it is impossible to say that one way of doing things is better than another. It all depends on the situation and what you are trying to achieve.

The optimization fallacy has been so ingrained in the minds of humans for thousands of years that it is difficult to even think about this kind of stuff.

It is a self-perpetuating machine that will always exist because people have become so used to it.

A Short Story

Imagine that you are a little girl, who is about to be captured by pirates.

The pirates will torture and kill you unless your father pays them ransom money. You run to tell your father the bad news, but not fast enough: he hears the sound of approaching horsemen and draws his pistol.

story about artificial choice
Photo by Markus Spiske on Unsplash

The pirates are armed, and so is your father. Your father has to make a decision: does he shoot the first pirate who comes through the door, or wait for more riders?

If he shoots too early, then there may be no second shot.

You don’t know what your father is going to do, but you are afraid he will shoot too early.

You think: ‘I know that I am about to die! If only my father would wait a few more seconds before shooting!’ But then again, if he waits too long, the pirates may murder you anyway.

Your father has exactly the same problem. He is afraid you will die if he shoots too early, but then again, if he waits too long, the pirates may murder you anyway.

Realizing there is no way out of this terrible dilemma, you and your father both shoot and miss. The pirates kill you with their first volley.

You learn an important lesson: one way to avoid the optimization fallacy is to give up control of your life. In this case, you were better off being a dead girl than risking any chance that you might live.