Ethical Competencies in Machine Learning from a Communicational Perspective in Educational Process

Abstract

The term "artificial intelligence" (AI) refers to computer programs equipped with numerous competencies, such as making calculations, grouping and categorizing data, or communicating with the user in ethnic languages. On the other hand, artificial intelligence systems do not have certain properties, and among them, apart from the lack of "creative abilities", is indifference to the moral aspect of actions when searching and compiling data or cataloging phenomena.

This study aims to discuss selected reasons for this state of affairs in the context of machine learning (ML) methodology, including the issues and applications of artificial intelligence from the perspective of scientific communication that occurs in the educational process. Given this goal, a research problem was formulated in the form of a question: How are ethical competencies developed in the machine learning process in the context of communication occurring in the educational process? In order to answer this research question, the text analysis method and the synthesis method were used. As a result of the research, it was determined that conducting machine learning with human participation, as well as using artificial intelligence systems previously learned with human participation, may enable the transmission of moral content in the normative sense to a cybernetic machine. Since human participation allows supervised learning of cybernetic machines, this type of learning, used as the sole method or in combination with another method, offers the opportunity to provide applications with the desired information about socio-cultural rules. Fully independent training of cybernetic machines does not ensure they collect information on ethical aspects desirable in communication during the educational process because open data sets on which machine learning takes place may contain harmful content, amplifying negative social phenomena.