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Ethyka offers artificial intelligence “of ethical component” for the automotive

Acuilae has created Ethyca, a “pioneer” system in artificial intelligence designed for the automotive sector, which helps autonomous driving systems to make decisions “of ethical component”.

Ethyka also helps manage dilemmas and behaviors in the face of unpredictable situations and predictable patterns following different ethical standards, decision criteria, and human behavior, the company said in a statement today.

For example, Ethyka can act in the detection of “unethical” behavior of drivers of vehicles such as sleep- induced sleep, potential fading or strange behavior.

In these situations, Ethyka communicates the incidence and activates all the immediate emergency protocols to park the environment “in the safest manner and in the shortest possible time”.

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According to the company, in the development of robotics it is necessary to know how to “include ethics in artificial intelligence”, that is why the launch of this system tries to introduce a program that “emulates” certain human behaviors or functions and responds to the question of “what should be the ethical behavior that robots, machines, and automated systems should follow”.

This module “pioneer” in incorporating the ethics to the technology in the automotive based on artificial intelligence has been thought and developed to help in the decisions before ethical dilemmas of the society in the professional, social, cultural and transport environments (subway, trains, planes, cars, motorcycles), among others.

Ethyka is born from the study of the human brain
The research and analysis of this Spanish project come from the study of the functioning of the human brain and its decision-making process, the company pointed out.

In a first phase, Ethyka receives all the information that comes from cameras, audios, sensors, applications or programming structures (frameworks).

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In the second stage, it uses a catalog of dilemmas with predetermined factors depending on the subject treated to determine the existence or not of the dilemma and the actions to be taken depending on the scenario.

After that, he analyzes the dilemma in three phases and determines what kind of ethics will be used (the approbative, the autonomous and heteronomous, the evolutionary, the theological, the social, the civic and the professional) to decide which principles must be met. (depending on the scenario and the type of ethics assigned).

Then, it uses automated learning techniques ( “machine learning” ) to generate predictions that will help contrast the ethical decision making of the dilemmas raised based on the information stored.

After this scrutiny, the decision criteria are divided into three models: “low certainty”, “low risk” and “low uncertainty”, solutions that, according to the company, are valid in all circumstances for each sector, culture or country determined and under different and specific rules of behavior of each society.

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