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Algorithms begin to replace scientific knowledge

lgorithms have reached such a level of sophistication and precision that some scientists argue that more is known by using these algorithms than by learning science. In other words, artificial intelligence has led to a rethinking of the utility, purposes, and methods of modern science.

It has been said, and with good reason, that modern science is an updated and technologized expression of ancient mythology, understanding 'mythos' as a narrative that, while giving meaning to reality, serves as a basis and guide for thought and behavior. Expressions like "Science says that ..." reveal that mythological aspect of current science.

But now, it seems, science will no longer be necessary because artificial intelligence algorithms will replace it. It may be premature to make such a statement, but, according to leading scientists in the United States, there are clear indications that we are moving in that direction.

Let's put it this way: I don't need to know how a combustion engine works to drive a car, nor do I need to know in detail all the technological elements inside my smartphone to use that phone.

In fact, if I had to first learn how a car engine works to drive the car or first learn what each component of my phone does to use the phone, I would most likely never drive or talk on the phone.

Something similar would be happening in terms of the relationship between algorithms and science, says scientist Hong Qin, from the Princeton Plasma Physics Laboratory of Plasma (PPPL), under the U. S. Department of Energy. 

Basically, Qin argues, it is no longer necessary to learn, as was done before, all the elements of Newtonian physics to calculate the orbits of the planets because those calculations are now made by artificial intelligence algorithms, without the need to spend years and years studying physics or astronomy.

Even more specifically, Qin claims that algorithms are replacing traditional science with a kind of "black box", in the sense of a process unknown to the user, that provides "accurate predictions" and it does it (this is important) "without using any theory or scientific laws."

In other words, not only does the person who wants to calculate the orbits of the planets no longer need to know how or why those planets move, but the algorithms that perform these calculations do not know (nor are they interested in knowing) the scientific laws that they govern the orbits of the planets. Obviously, the example can be extended to almost any other scientific field.

But how does the algorithm do to accurately calculate the orbits of the planets if those calculations have no scientific basis? Because the algorithm teaches itself how to do it.

We are, then, seeing the beginning (I think) of a science without science and of a science without consciousness, in which everything is transformed into something calculable, but not in a materialistic sense, but in the sense that, according to Qin, the whole universe is a simulation inside a computer.

Dr. Hong Qin

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