The purpose of the work is to study the transformation processes of constructing professional identity under the influence of new information technologies and to consider the evolution of views on the processes of scientific and practical understanding of new media resources in the context of the development of convergent journalism as a phenomenon of the modern information society. It was established based on the conducted research that the values and beliefs of journalists, reflecting the process of professional self-identification, are forming in the process of choosing certain options among a variety of alternatives and transforming further under the current conditions of the information and communication environment. In the process of the study, the article identifies the features, content, and main trends in the transformational processes of professional identity and professional culture of journalists in the context of technological changes in the media industry. The dynamics of the development of media convergence are shown from the point of view of the mutual influence of traditional and new media and the tendency of improving their technological and dialogue features and capabilities in content creation and broadcasting. An assessment is made of the degree of adaptation of regional media to modern conditions of the information and communication environment in the context of organizational, professional, and communicative convergence.
The research addresses the importance of ethics in public administration, focusing on public servants in the municipality of Rionegro, Colombia. Ethics is presented as an essential element to promote transparency and combat corruption in public management. Despite the fact that the 1991 Constitution establishes ethical principles, their application in practice remains a challenge, with a high level of immorality in public service. The study highlights the diversity of professional profiles in public servants, which hinders consistent ethical management. In addition, it mentions that many civil servants lack political training and understanding of the importance of their role, which contributes to corruption. Ethics, according to the authors, is a key tool for strengthening institutions and regaining public trust. The research evaluated the impact of a professional ethics training program on public servants, finding significant improvements in their ethical knowledge and behavior. It concludes that, although ethics will not solve all corruption problems, it is an indispensable component for strengthening accountability and justice in public administration. It underscores the need to implement continuous training programs that promote ethical values as part of a strategy to improve efficiency and transparency in public institutions.
Recent times have seen significant advancements in AI and NLP technologies, poised to revolutionize logistical decision-making across industries. This study investigates integrating ChatGPT, an advanced AI language model, into strategic, tactical, and operational logistics. Examining its applicability, benefits, and limitations, the study delves into ChatGPT’s capacity for strategic logistics planning, facilitating nuanced decision-making through natural language interactions. At the tactical level, it explores ChatGPT’s role in optimizing route planning and enhancing real-time decision support. The operational aspect scrutinizes ChatGPT’s capabilities in micro-level logistics and emergency response. Ethical implications, encompassing data security and human-AI trust dynamics, are also analyzed. This report furnishes valuable insights for the logistics sector, emphasizing AI’s potential in reshaping decision-making while underscoring the necessity for foresight, evaluation, and ethical considerations in AI integration. In this publication, it is assumed that ChatGPT is not entirely reliable for decision-making in the logistics field: at the strategic level, it can be effectively used for “brainstorming” in preparing decisions, but at the tactical and operational level, the depth of the knowledge is not sufficient to make appropriate decisions. Therefore, the answers provided by ChatGPT to the defined logistic tasks are compared with real logistic solutions. The article highlights ChatGPT’s effectiveness at different levels of logistics and clarifies its potential and limitations in the logistics field.
The process management variable and the service quality variable date most prominently from the beginning of the last century, and therefore, in organizations from different parts of the world, whose search was to contribute effectively to administrative tasks, facing the challenges of constant changes and evaluations. In Peru, both variables were implemented since 2018, by technical standards, in order to contribute and improve public institutional work. Thus, the objective was to know the most outstanding characteristics of process management and service quality, using studies from different entities at the ecumenical level and revealing their main benefits of application and contribution. Furthermore, based on the systematic and methodical review of scientific articles from databases indexed to multiple journals, which are registered and organized in databases such as WOS and SCOPUS, thus theorizing their authors and perspectives. For this study, the documentary analysis technique and the data collection guide were considered as an instrument; in accordance with the PRISMA method. Finally, it is concluded that process management are methods available in an organization to provide effective results using resources efficiently, with dimensions of analysis, monitoring, and process improvements, contributing to organizational and strategic productivity; Likewise, the quality of the service is user satisfaction when judging the value of some service, dimensioning, analyzing needs, as well as evaluating, supervising and improving the service, fulfilling needs with knowledge of their expectations.
The expanding adoption of artificial intelligence systems across high-impact sectors has catalyzed concerns regarding inherent biases and discrimination, leading to calls for greater transparency and accountability. Algorithm auditing has emerged as a pivotal method to assess fairness and mitigate risks in applied machine learning models. This systematic literature review comprehensively analyzes contemporary techniques for auditing the biases of black-box AI systems beyond traditional software testing approaches. An extensive search across technology, law, and social sciences publications identified 22 recent studies exemplifying innovations in quantitative benchmarking, model inspections, adversarial evaluations, and participatory engagements situated in applied contexts like clinical predictions, lending decisions, and employment screenings. A rigorous analytical lens spotlighted considerable limitations in current approaches, including predominant technical orientations divorced from lived realities, lack of transparent value deliberations, overwhelming reliance on one-shot assessments, scarce participation of affected communities, and limited corrective actions instituted in response to audits. At the same time, directions like subsidiarity analyses, human-cent
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