With the increasing global interest in the field of artificial intelligence, a disturbing phenomenon has emerged represented in the spread of inaccurate or misleading information that is circulated by individuals who lack experience or deep understanding of this field. Many of these seek only to keep pace with the event, and they translate foreign articles or repeat the terms traded without awareness of the context or nuances of concepts, driven by a desire to achieve professional or commercial benefits, and not with scientific responsibility or knowledge awareness. The capabilities of artificial intelligence and its borders, especially among decision makers or the general public. The risk of this effect increases when it reaches young people, as they constitute the most interactive category with digital content and the most open to new technologies; This misleading discourse can lead them to adopt unrealistic perceptions, or to seek inappropriate professional paths. Who are the individuals who are qualified to talk about artificial intelligence? Civil intelligence to talk about artificial intelligence is not only related to the job name, but to the depth of understanding, and the link of practical or academic experience in the fields of artificial intelligence. Among the most prominent qualified categories: 1. Artificial intelligence engineers and developers: They have a direct technical experience in developing algorithms and models, and they know their capabilities and boundaries. 2. Data scientists and automated learning engineers: specialized in data analysis and predictive models using artificial intelligence technologies. 3. Researchers and academics in the field of artificial intelligence: they contribute to developing scientific knowledge through in -depth studies and experiences. Specialists in artificial intelligence ethics: they discuss sensitive aspects such as privacy, bias, and legal responsibility. 5. Technology policymakers: They put an organizational framework a balance between innovation and community protection. 6. Practitioners in the various sectors (health, education, law, … etc.): They have direct experience in applying artificial intelligence solutions on the ground, which gives them a valuable applied understanding. Technology educators and intellectuals: They contribute to simplifying concepts and spreading awareness of responsibility and professionalism, especially among the non-specialists. Examples of unhappy categories: 1. Those who confuse artificial intelligence and science fiction: they present unrealistic expectations or dramatic scenarios that are not based on scientific reality. 2. Those who deal with artificial intelligence with the logic of commercial tools or public relations opportunities: this category includes individuals or bodies that deal with artificial intelligence as a mere way to achieve immediate marketing or commercial gains, without a deep understanding of its techniques or long -term effects. 3. Those who depend on repetition or transport without developing an authentic understanding: are satisfied with re -publishing translator content or post -scrutiny contents, and depend on common terms without building a systematic understanding, which leads to misleading the audience or publishing inaccurate perceptions. 4. Those who make recommendations or consultations based on personal positions or non -scientific beliefs: promote opinions about adopting artificial intelligence in institutions based on general impressions or unaccounted convictions, which may lead to wrong strategic decisions. 5. Those who lack awareness of the field developments and basic sources: depend on old or unreliable information, without following up on approved research, or without understanding the rapid changes in the global artificial intelligence, which makes their interventions inaccurate or disconnected to reality.
