The current work aims to analyze the main themes related to artificial intelligence (AI) and sustainable development during the pandemic period. This study provides an overview of the specialized literature related to AI and sustainability from the beginning of the pandemic through 2023. The present paper analyses scientific literature emphasizing both artificial intelligence's positive and negative impacts on sustainable development objectives (SDGs). To conduct the research, we employed bibliometric analysis and text-mining techniques to identify the major themes in the literature indexed in the Web of Science and Scopus databases. Firstly, we used descriptive measures to identify the authors' impact, the article production by country, the main keywords used, and other descriptive data. We further used data reduction methods based on co-word analysis (such as multiple correspondence analysis) on authors' keywords to show patterns in the themes explored in the literature. Bibliometric analysis was supplemented by text mining using Latent Dirichlet allocation (LDA) and structural topic modeling on abstracts to provide a comprehensive view of scientific debates on AI and sustainable development. Our research has identified various themes in the literature related to AI and sustainable development. These themes include social sustainability, health-related issues, AI technologies for energy efficiency, sustainability in industry and innovation, IoT technologies for smart and sustainable cities, urban planning, technologies for education and knowledge production, and the impact of technologies on SDGs. We also found that there is a significant positivity bias in the literature when discussing the impact of AI on sustainable development. Despite acknowledging certain risks, the literature tends to focus on the potential benefits of AI across various sectors. In addition, the analysis shows a growing emphasis on energy efficiency, which is facilitated by the use of AI technologies. Our study contributes to a better understanding of current scholarly discussion trends and emerging scientific avenues regarding AI and sustainable development. It also highlights the areas where research is needed and the implications for practitioners and policymakers.

The new challenges caused by the SARS-CoV-2 pandemic forced the entire World to stop some activities, including educational activities. This situation pushed educational system to move its space of work in an online environment. In this article, we aim to present some of the measures that have been taken by the Romanian Government and universities in an effort to mitigate the potential risks that threatened the education system. We also intend to present some issues that arose during this educational migration to online learning. The measures adopted include providing technical support for teachers and students in supporting them on how to access and how to use the online resources and tools made available to ensure the continuity of the educational process. Other measures include online courses addressed to students in final years for their training in oral presentations for final exams, and also provision of financial support for students with limited financial possibilities to help them purchase a computer. One problem that would hinder the educational process in the online environment would be technical aspects specific to the online platforms, but also the way students and professors use them. Other difficulties include the lack of digital skills, as well as the lack of involvement in the online learning activities of some professors.

Artificial Intelligence (AI) has begun to transform the labor market, allowing technologies to perform some of the tasks previously performed only by humans. Previous studies have shown that artificial intelligence technologies have reshaped workplaces and tasks structures, generating new skill demands in the labor market. However, there is limited research on how the required skills and underlying epistemic orientations of AI-related academic jobs are communicated during the hiring process. The present study explores this discursive construction of the researcher role by analyzing the skills and competencies prioritized in AI-related academic job postings. To achieve the study's goals, we used data on job descriptions from around 800 jobs posted on the EURAXESS platform until January 2024 using descriptive text mining methods and Latent Dirichlet Allocation (LDA) topic modeling. The findings revealed a strong demand for research and digital skills, as well as career development, communication, mobility, and enterprise skills. The results also reveal seven distinct thematic clusters, which we interpret as representations of different epistemic cultures being signaled to prospective candidates. The results can be valuable for policymakers, research institutions, and universities.

Like other postmodern structures, post-industrial labour markets display more frequent and rapid changes and higher unpredictability. In these conditions, the world of work is less capable in providing individuals stable signals for the construction of their behaviours. This paper aims to examine both macro and micro factors that shape labour market participation and expectations related to employment outcomes. We explore statistical data from the World Values Survey Wave 7 (2017-2020) collected from almost seventy thousands individuals around the world. Focusing on subjective evaluations of expected employment outcomes, our results are relevant for better understanding labour market participation from a postmodern perspective.