Artificial intelligence and intuition

Fuzzy or fuzzy logic, approximate reasoning, there are many advances by experts in artificial intelligence (AI) to simulate natural intelligence with algorithms.
But how to translate intuition, imagination, ambition for knowledge or even human obsessions, perceptible from the earliest ages, to mathematical algorithms? In a materialized, algorithmized science, there is no place for concepts such as intuition or, let us say, the feeling that they are, to a large extent, responsible for achieving the advances that are marking the first third of the 21st century.
Albert Einstein was neither the best physicist nor the best mathematician of his time. He had to ask for help in calculating some of his experiments - many visuals - that he imagined in his walks and conversations with friends-not even colleagues. More than one hundred years later, his theories are being corroborated by the scientific community with the help of the latest computational advances that they include in their software AI.
In every human act and, therefore, before any decision, not only cognition influences. The context can be decisive. Environment, environment, feelings, sensations, expected or unexpected memories, conscious or unconscious. However, depending on the theorists, decisions that are not mediated by distracting stimuli can be considered more intelligent.
Anyway, it is necessary to develop a theory about ethics and even the philosophy applied to AI, and, therefore, the urgent imbrication of the humanities in a world that we are entering fully, that of AI, when not even, until now we have been able to define the concept of intelligence.
Intelligence is a construct, it is not a formula. Its definition is in constant review and scientists have not managed to reach an agreement in centuries. How is an "artificial" production system designed and elaborated correctly from a construct that lacks definition?
The simulation of human intelligence based on algorithms exponentially multiplies capacities such as memory, speed of calculation, processing and interrelation of millions of data, but also, in the case of failed or malicious algorithms, errors. Unknown, latent or immediately explosive errors, already processed, converted into big “misdata”.

Dr. Hesles Sánchez. Phd. Journalist
Dra. Morón-Nozaleda, MD, PhD. Psychiatrist.

10 - ARTIFICIAL INTELLIGENCE AND INTUITION