Four years ago, the Trusted News Initiative (BBC 2020) joined forces to combat disinformation surrounding the COVID-19 vaccine. At the same time, First Draft revealed that 84% of content on Facebook and Instagram was misinformation about the vaccine. In 2018, a study identified 16 media outlets, 13 news agencies, and 21 leading news organizations that were transitioning to algorithmic information control mechanisms. In the meantime, Project 2061, from the American Association for the Advancement of Science (AAAS), has been operational for 35 years. For the general public, science is conveyed through the lens of journalism, where the encoding process is more pronounced because it occurs between non-peers. It is therefore evident that the quality of journalistic content, particularly in the audiovisual domain, and the competence in its transmission are of paramount importance. In order to ensure the implementation of its basic quality, namely the know-how to communicate science, it is essential to implement the aforementioned quality. In the field of media, trust is synonymous with credibility. Since the advent of software capable of producing texts in natural language, technical and technological knowledge has been imposing solutions that should facilitate the development of a new anthropology of rescue, taking into account AI’s role as a screening tool and a builder of bridges and contents towards human ecology. This study, based on the narrative bibliographic review (Rother 2007), has as its primary objective an understanding of how the competencies of this algorithmic journalism, which Túñez et al. (2019) have termed “artificial journalism,” contribute to the construction of scientific literacy and the dissemination of information. It also aims to facilitate further research on this system, which effectively translates function and textuality into journalistic information.