Month: July 2024

Abstract

Mis- and disinformation pose substantial societal challenges, and have thus become the focus of a substantive field of research. However, the field of misinformation research has recently come under scrutiny on two fronts. First, a political response has emerged, claiming that misinformation research aims to censor conservative voices. Second, some scholars have questioned the utility of misinformation research altogether, arguing that misinformation is not sufficiently identifiable or widespread to warrant much concern or action. Here, we rebut these claims. We contend that the spread of misinformation—and in particular willful disinformation—is demonstrably harmful to public health, evidence-informed policymaking, and democratic processes. We also show that disinformation and outright lies can often be identified and differ from good-faith political contestation. We conclude by showing how misinformation and disinformation can be at least partially mitigated using a variety of empirically validated, rights-preserving methods that do not involve censorship.

Recent advances in artificial intelligence (AI) have introduced transformative capabilities that are revolutionizing the process of scientific research and communication. AI tools can assist researchers in designing studies, analyzing data, and drafting manuscripts, enhancing both efficiency and analytical rigor. This allows researchers to focus cognitive resources on higher-level conceptualization and interpretation. Furthermore, AI holds promise for steering research towards more impactful directions by aiding in the identification of critical knowledge gaps and research questions with potential societal benefits. Collaboration platforms powered by AI facilitate connections between researchers across domains and institutions, accelerating discovery and promoting convergence around global health priorities. However, responsible development and application of AI in research is essential. Transparency, explainability, data privacy, and human oversight must remain priorities to ensure ethical AI practices. While AI offers transformative capabilities, researchers must maintain agency and responsibility over the scientific process. With thoughtful governance and participatory design, AI can become a powerful tool for advancing science in the service of society. Overall, AI ushers in new potentials for improving the rigor, relevance, and reach of scientific inquiry. Yet realization of this potential necessitates proactive efforts to address emerging risks and challenges.

Abstract

Background

The COVID-19 pandemic initiated a great global crisis, during which media influenced society and social interactions affected media use. Researchers from various research fields have studied the pandemic both globally and locally. This study aims to summarize the research on COVID-19 pandemic within communication studies, taking into account 358 articles published in SJR best ranked journals in 2020–2022.

Methods

The study uses both qualitative and quantitative methods. Using manual coding and qualitative content analysis, we investigate articles’ distribution according to journals, time, accessibility (either open, free or restricted) and methodological approaches. We also provide a qualitative summary of trending research themes. Using quantitative social network analysis (SNA) we present the distribution of institutions and countries in articles’ affiliations, and the collaboration network at institutional and country level.

Results

Results show an in-time increase of COVID-related publications. Articles were affiliated with 490 institutions from 68 countries, with the USA having the greatest representation. There was an underrepresentation of African and South American countries, which reflects the core-periphery challenge in knowledge production. The network analysis revealed that very few of possible connections were actually achieved. There is an observable trend of using quantitative methods. A growth on the gap between qualitative and quantitative studies was observed each year. More than a half of articles using qualitative methods were published in restricted access. Our qualitative summary of the addressed topics and main findings in articles related to COVID-19, media and society revealed a wide research interest in pandemics impacts on news consumption, media use and journalism, as well as infodemic, conspiracy narratives, science mistrust and discrimination and inequalities increased by the pandemic.

Conclusion

To provide a wider perspective on the worldwide impact of pandemic, more studies from underrepresented countries are needed. The collaboration between institutions and countries requires strengthening. Qualitative studies were conducted considerably less than quantitative studies and they were usually published in restricted access, which leads to a methodological gap.

Abstract

Latinx cisgender sexually minoritized men (SMM) and transgender women (TW) in the U.S. are disproportionately affected by HIV. Although pre-exposure prophylaxis (PrEP) is a highly effective strategy for HIV prevention, rates of PrEP use among Latinx SMM and TW remain suboptimal. The main purpose of this systematic review was to (1) describe engagement in the various stages of the PrEP care continuum among Latinx SMM and TW, and (2) identify multilevel determinants that function as barriers or facilitators to engagement in the PrEP continuum of care for Latinx SMM and TW. This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement (PRISMA). Five databases (MEDLINE, CINAHL, PsycINFO, Embase, Scopus) were searched to examine the available qualitative, quantitative, and mixed method studies relevant to the research question. A total of 56 studies were included, with the majority focusing on SMM and being cross-sectional in design. Barriers included PrEP knowledge, risk perception, intersecting stigma, and structural conditions. Community resources, social support, and PrEP navigation services facilitated engagement in the PrEP continuum of care. This review highlights the complex factors that influence PrEP care engagement among Latinx SMM and TW. These findings call for comprehensive, multilevel approaches to address inequities disparities in PrEP care engagement among these groups.

Abstract

Rawls famously argues that the parties in the original position would agree upon the two principles of justice. Among other things, these principles guarantee equal political liberty—that is, democracy—as a requirement of justice. We argue on the contrary that the parties have reason to reject this requirement. As we show, by Rawls’ own lights, the parties would be greatly concerned to mitigate existential risk. But it is doubtful whether democracy always minimizes such risk. Indeed, no one currently knows which political systems would. Consequently, the parties—and we ourselves—have reason to reject democracy as a requirement of justice in favor of political experimentalism, a general approach to political justice which rules in at least some non-democratic political systems which might minimize existential risk.

Abstract

Will the challenges faced by both the European Union and a candidate country during a future enlargement process be ‘new’ challenges, or will they be reiterations of challenges successfully overcome during previous enlargements, notably during the ‘Big Enlargement 1.0’ in 2004? This contribution argues that many of the challenges (institutional, political, economic, legal, and linguistic) are indeed not new; but that a future EU enlargement is likely to take place within a far more uncomfortable global environment. In particular, the presence of a hostile and aggressive near neighbour in the shape of Russia will require a concerted and intelligent response.

Abstract

This survey paper explores the transformative role of Artificial Intelligence (AI) in information security. Traditional methods, especially rule-based approaches, faced significant challenges in protecting sensitive data from ever-changing cyber threats, particularly with the rapid increase in data volume. This study thoroughly evaluates AI’s application in information security, discussing its strengths and weaknesses. It provides a detailed review of AI’s impact on information security, examining various AI algorithms used in this field, such as supervised, unsupervised, and reinforcement learning, and highlighting their respective strengths and limitations. The study identifies key areas for future AI research in information security, focusing on improving algorithms, strengthening information security, addressing ethical issues, and exploring safety and security-related concerns. It emphasizes significant security risks, including vulnerability to adversarial attacks, and aims to enhance the robustness and reliability of AI systems in protecting sensitive information by proposing solutions for potential threats. The findings aim to benefit cybersecurity professionals and researchers by offering insights into the intricate relationship between AI, information security, and emerging technologies.