Journal of Biology and Today's World

Editorial Ethics in Code Programming and Deep Artificial Intelligence Algorithms (IAp)

José Luis Garcia Vigil^{* *}Correspondence: José Luis Garcia Vigil, Department of Medical Sciences, National Autonomous University of Mexico, Mexico City, Mexico, Email:

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Introduction

In elementary programming languages, there were two lines of communication; what the user who knew the language of the program she was using wrote or noted in text and numbers; and the response equivalent of the machine, was the text or mathematical calculations that the equipment processed [1-4].

Currently, the codes and algorithms of the so-called IAp, simile of multilayer parallel neural networks and with hybrid chips supported by micro transistors and cells or biological tissue, have the ability to process a large amount of information in text and numbers with high speed , in accordance with the goal and purpose of the initial program; but later, once the machine has learned and internally reports back, it is able to create the following program to improve the process and obtain increasingly complete results [1-4].

As for the risk of reifying human intelligence (IH), favoring Artificial Intelligence (AI) and oversizing the development of the latter to the detriment of the former, it is a real risk if man does not learn to regulate his technological innovations. From the beginning, when the computer scientist makes the AI program, he has to use codes and algorithms that allow predicting the course of the processing to the final result, which the programmer himself already knows.

The risk is greater due to lack of control outside the scope of the programmer when it comes to advanced AI programming, which is called "Deep Learning", with simile or metaphor of parallel and multilayer neural networks; and even more, with processing in hybrid chips (transistor-cell/ tissue); since the same program as it "learns" perfects its codes and algorithms by ways or routes no longer known or identified by the human programmer; hence the need for "alerts" or calls for attention to be programmed when the course the program takes is dangerous due to the final result.

The least thing would be if the program or the robot that works with it were destroyed, the greater risk would be when the result could endanger the integrity and life of humans. For this reason, the need for ethical values and principles to be present at the beginning and during the programming of this type of AI; in addition, the need to adapt laws, rules and regulations on the matter. An example is the standard in the development and use of AI in Europe, called the "Barcelona Bioethics Declaration" [2].

Deep Artificial Intelligence (IAp) Codes and Algorithms for Automatic Programming of your Own Program

It is an AI program with a metaphor of neural networks in parallel and that as they advance in their programming goal, they learn to continue coding their own communication language automatically and therefore autonomously, without the participation of the human being or programmer who created it.

In other words and recreating the above; means that such programs can learn to correctly write their programming language and artificial intelligence (AI) algorithms so that they can follow the initial programming and then automatically create their own algorithmic paths, until they drill down to a maximum degree of improvement, without the presence of the human being in the intermediate steps or in the end of said programming.

In this type of programming language, the design and values or ethical principles of the programmers are fundamental, so that from the beginning they are clear about the direction that AIp programming should take and have codes and calls for attention (alerts) of the program when this deviates from its goals and whose results endanger the safety and life of the humans who will use them as end users.

There are so far several examples of this type of program [5-9].

IAp programs for decision making in different humanistic, technical and scientific fields.

IAp programs for writing classical music books and scores, or making paintings with a characteristic pattern of style and type of pictorial art.

IAp programs to refine gene editing with CRISP-Cas9.

AIp programs for synthetic biology and cell bioengineering.

References

1. Mántaras, R. L. “Ethics in artificial intelligence.” Res Sci. 491.11(2017): 11.
2. “Barcelona Declaration for the Adequate Development and Use of Artificial Intelligence in Europe.” (2020).
3. García-Vigil, J. L. “Reflections and conjetures around the development of Artificial Inteligence.” Do Robots Dream. (2020).
4. García-Vigil, J. l. “Reflections on Ethics Human Intelligence and Artificial Intelligence.” (2020).
5. García-Vigil, J. L. “Editorial Ethics and Good Practices in Scientific Publications: Cases of Publications in Medicine.” (2020).
6. Nuñez-Acosta, E. “Edición genética en humanos, la gran controversia”. (2020). 
7. “Machine learning takes on synthetic biology: Algorithms can bioengineer cells for you.” Lawrence Berkeley National Lab. (2020).
8. “El cerebro humano congela el tiempo para facilitar la toma de decisiones.” El Universal. (2020).
9. Medina, A. “Intel: El boom millonario de la Inteligencia Artificial está cerca.” Forbes México. 2(2020).