How meditation can improve our problem-solving skills
The goal of this article is to try to explain easily, how the practice of meditation affects our problem-solving skills. To do this, I use a mathematical logical method to characterize problems based on the number of their possible solutions. In this way, it easy to explain the two primary approaches that the mind uses in solving problems. The first approach is iterative, optimal in solving simple problems (problems with a low number of solutions). The second approach is the logical one, optimal in solving complex problems (problems with a high number of solutions). The interesting aspect of these two methods is that their mode of action is the opposite. The iterative method is based on action, while the logical method is a reflective approach, in which any unnecessary action takes us away from solving the problem. Consequently, we will see how through the practice of meditation, we can shift our mental predisposition towards the logical approach by inhibiting our propensity for the iterative approach. This is a very important result because it can allow us to improve our ability to solve complex problems. This type of attitude is fundamental in a society where technological progress is making all simple and repetitive jobs less indispensable.
The two fundamental methods used by the mind in solving problems
From a mathematical logical point of view, the problems can be divided according to the number of possible solutions they can have. Therefore, using this approach, we can define two classes of problems:
1) “Simple” problems: the problems in which the space of possible solutions is constituted by a small number of elements. Where the time required to try all possible solutions iteratively, is limited and acceptable. Example: a padlock that has 100 possible combinations, if I can try a different combination every 5 seconds, I will try all the combinations in an acceptable time.
2) “Complex” problems: the problems in which the space of possible solutions is constituted by a large number of elements. Where the time to try all possible solutions iteratively, tends to infinity or to an unacceptable time. Example: proving a mathematical theorem, doing it iteratively trying random solutions, takes a time that tends to infinity.
Thanks to this classification, we can study, in a simple way, the two fundamental approaches that the mind uses in solving problems.
The first approach is iterative, the mind does not try to solve the problem but tries all possible combinations. This approach is the optimal one for solving “simple” problems and was fundamental in the initial part of human evolution.
The second approach is the logical one; the mind creates a model of the problem and tries to solve it. This approach is the optimal one for solving “complex” problems, and its importance has increased in the course of human evolution. Consequently, this category of problems is also the one that most characterizes our problem-solving skills.
Comparing these two methods, the interesting thing we notice is that they act oppositely. The iterative method is based on action, faster I act, faster I solve the problem. Instead, the logic-based method is thoughtful; any incorrect action takes us away from the solution.
To explain the importance of not acting irrationally, when trying to solve a complex problem, I like to give the following example: imagine that you are a hiker who got lost in the jungle, what are you going to do? If we try to ask this question to a survival expert, he will answer that the best thing to do is to do nothing, and wait for help, because any of your actions will only tire you and put you in danger. The same thing happens in solving complex problems, in which every irrational action is not only useless but it makes us lose energy and time. This example makes us understand how different the two mental approaches are, and how fundamental our mental predisposition is to be successful in situations where a type of problem predominates.
Another useful point of view, to understand the importance of these two mental approaches, is to comprehend why there is so much interest in algorithms based on artificial intelligence. The reason for such interest stems from the fact that through artificial intelligence the algorithms are moving from an iterative approach to a logical approach. In fact, for example, the software developed to play chess, until recently used iterative approaches. In practice, the software simulates all possible combinations and chose the best move. This method had two important limitations: it needed a very powerful computer and could not be applied to games like the “go” in which the possible move combinations are very high. With the advent of artificial intelligence, these virtual players have gone from an iterative approach to a logical approach with incredible results. Google’s Deepmind research team has developed the first software capable of beating the human champion of “go”, on this topic I recommend reading the article published on nature “Mastering the Game of Go without Human Knowledge”.
Now you can understand why the knowledge of these two different mental approaches is fundamental for studying the dynamics that involve our problem-solving skills.
Meditation as mental training to improve the problem-solving skills
In this section, we will try to explain the implications of meditation on problem-solving skills. The term meditation refers to a large number of techniques, even very different from each other, whose task is to bring complete awareness of the present moment. One of the oldest and best-known techniques, and consequently among the most practiced, is called vipassana. The practice of this meditation is performed by sitting cross-legged while remaining completely still in a mental state in which we observe everything that happens. Mainly the observation is directed towards thoughts that tend to manifest themselves and towards one’s breathing.
If we now analyze the two mental approaches, described in the previous paragraph, it is easy to understand how the practice of this type of meditation tends to be in contrast with the iterative method used in solving problems. As described in the previous paragraph, this approach is based on action, in practice, I act as quickly as possible without ever stopping. Hence, sitting still for no purpose represents the opposite of this method.
Consequently, the constant and repeated practice of this type of meditation leads over time to inhibit our propensity to act impulsively. There are many scientific studies on this topic that show how meditation reduces our propensity to multitasking (hyperactivity) and all those irrational and emotional behaviors. This is an important fact because the iterative approach is based on random (irrational) and continuous actions with a strong emotional component.
Meditation in this way modifies our problem-solving skills making us more reflective, consequently increasing our propensity towards the use of the logical approach in solving problems. This result is significant because when we talk about problem-solving we are talking, in most cases, about the ability to solve complex problems. In fact, in a society where technological progress has an exponential trend, our ability to solve problems of this type becomes an increasingly important and requested skill.
Another fundamental aspect to keep in mind, regarding the importance of training the mind to a more reflective approach, is to understand the impact that new technologies have on our minds. To answer this question, we need to understand how most of the applications that are used on smartphones, tablets, etc. are developed.
The main purpose of these applications is to create an addiction, and to do this they take advantage of the iterative approach that the mind uses to solve simple problems. This is done because, in this situation, the person is forced to perform a continuous series of actions, which will correspond to a series of results, the consequence of which is a stimulation of the reward system present in our brain. With this technique, the user of the application will compulsively experience a succession of emotions, the result of which is to create a real addiction.
In conclusion, this type of technology is changing the approach to solving the problems of the new generations, favoring the iterative approach over the logical one. For this reason, it is essential to counteract the conditioning caused by these applications with techniques such as meditation, which inhibit our propensity to solve problems iteratively.
Conclusion
In this article, I have used a simple mathematical logical analysis to relate our problem-solving skills and the practice of meditation. In this way, we find a similarity between two very different realities. On the one hand, we have a scientific formalism, in which through the analysis of a mathematical data the optimal approach is found to solve a class of problems. On the other hand, we have meditation, which represents a topic mainly studied in the philosophical field. So we have two extremely distant points of view which, however, as we have seen, tend to have incredibly similar elements of convergence. Indeed, the practice of meditation represents a way of acting contrary to the iterative approach. Consequently, meditation acts by inhibiting our propensity to act iteratively, making us prefer the logical approach, fundamental in solving complex problems. We have also seen how modern technologies are influencing new generations to hyperactive and compulsive approaches. So, it becomes essential to contrast this type of mental conditioning, with something that goes to act in the opposite direction leading us to act more thoughtful. Meditation, from this point of view, can be seen as a practice that acts on some primary aspects used by the mind in many of its processes, such as problem-solving. In this way, we can partly understand why something so simple has such profound implications in many areas of the brain. For these reasons, I believe that meditation will become an increasingly important formative practice.
