Aphoristic Ascendancy
It is tempting to think that everything we need to know and all that needs to be done can be captured by computer programs. After all, algorithms are used to map our cognitive models of reality. These hierarchical, interdependent and sometimes non-deterministic entities offer a deep metaphor for such types of thinking.
We have many algorithms for self-help: losing weight, taking and studying for tests, driving for work, quitting drinking and smoking, etc. It is understandable that algorithms should present themselves as a reasonable approach to life's problems that involve emotions. We equate algorithmic thinking to rational thinking. After all, it is systematic, has clear outlined steps toward a defined goal. What can be wrong with this?
Every plan of [multi-step] action involves various algorithms. Political campaigns and sentient AI have misplaced confidence in algorithms. They suffer from algorithm addiction. Oftentimes, the best plan of action is no plan of action for events to work themselves out for a while and check what results present themselves. These tasks are non algorithmic. Every practical man knows this. Algorithms have this cognitive power to exert over our culture. The problem is that one cannot be. He has to do something and for the seeming lack of an alternative employs algorithms that suppress human idiosyncrasies.
Our algorithmic culture can only conceive this influence of algorithms in the rational form of mechanical means. We need to understand there is a universe of plan of no-action larger than the plans, programs and questions posed by algorithmic culture. This is the universe of aphorisms. It offers a wonderful approach to the world and goes way back before even writing existed. The approach is to know and act based on the aphorism.
The beauty of this aphoristic approach is its meaning and depth may not be clear at once. Nor can it be completely understood. Questions from algorithmic culture like, "Can everything be modeled by algorithms?", "Can things be made explicit to be symbolized by programs?", etc. wouldn't exist here. "That way which can be written or spoken of is not the way", replies the aphoristic thought.
"What about political plans?", you ask. "Take no action, people reform", replies aphoristic thought. "More plans means more restrictions, it brings more misery", it says. Non-algorithmic models of action state that reality is not computable and cannot be reduced to algorithms. Algorithms do have room in the world of aphorisms. But their application is never mechanistic. Rules for behavior, steps for yoga, techniques for meditation are propounded to be followed.
Relying on algorithms alone deprives us of our ability to assess a situation on its own terms. We often end up choosing between algorithms -- which fits better for our tasks? That is because no system can work in all situations it will be exposed to. Hyperparameteric optimization of metamodels for AI for example, is a big business today. To sense, to intuit and to determine what is unique to each situation is a space that is beyond what our algorithms can cover.
We should rise above the algorithm. Aphorisms are superior to algorithms here. They are capacious and do not nail meanings down. Aphorisms should not be looked at as algorithms. When solving a problem or dealing with an issue, we should look to aphorisms. These cannot be applied like an algorithm. An aphorism should be discussed, mulled over with different perspectives and considered in conjunction with different aphorisms. It makes no sense to take an aphorism, treat it like an algorithm -- to be interpreted only one way and applied the same way at all times.
There is an art to applying aphorisms to specific situations. For a given situation, aphorisms should form the core of discussions about what is to be done. Interpreting these most insightfully begets great solutions and fine leaders. It is rational to return to the wisdom encoded in an aphorism. Aphorisms did last thousands of years suggesting only one thing: aphoristic thought is antifragile.