Hello Everyone, I am writing to draw your attention to the special Issue below: *Generative AI Age in Journalism: Unveiling Artificial Intelligence’s Potential and Challenges in the News Industry Worldwide* Link: https://bit.ly/GenerativeAIAgeJournalism. *Guest Editors:* *Allen Munoriyarwa* *Department of Media Studies, University of Botswana* *Department of Communication and Media, University of Johannesburg * *Mathias-Felipe de-Lima-Santos* *Faculty of Humanities, University of Amsterdam* *Digital Media and Society Observatory (DMSO), Federal University of São Paulo (Unifesp)* D*eadlines: * - *Abstract Submission:* January 5th , 2024 - *Paper Submission: *June 30th, 2024 - *Expected Publication Date:* Q4 2024 – Q1/2025 In recent years, the integration of artificial intelligence (AI) technologies in journalism and media production has sparked a global transformation in the way information is gathered, produced, and disseminated (de-Lima-Santos & Ceron, 2021). The term AI broadly refers to a field of computer science methods “dedicated to replicating human intelligence" (Broussard et al., 2019, p. 673). These technologies offer new possibilities for enhancing news gathering, content generation, audience engagement, and data analysis. Furthermore, they possess immense capabilities and offer incredible promises of transformation to media and journalism. Moreover, the AI-driven journalism landscape has witnessed a remarkable boom in the development and utilization of generative AI technologies, such as ChatGPT and DALL-E (Gondwe, 2023). The surge of generative AI has had a profound impact on news production, where AI algorithms can generate articles, summaries, and even assist in investigative reporting. These technologies have provided easy to use tools for media organizations in creating content at scale, automating repetitive tasks, and enhancing data analysis. While AI-driven journalism has garnered substantial attention and analysis in different media landscapes, there is a growing recognition of the unique implications, challenges, and opportunities posed by AI in the news industry worldwide (Broussard et al., 2019). This special issue aims to fill this knowledge gap by exploring the appropriation of AI technologies in news production across different media contexts. The application of AI in different regions brings with it a set of complexities that necessitate in-depth investigation. For example, previous research has indicated that media professionals’ inclination toward AI skepticism in Africa is influenced by concerns about potential job cuts, the expenses associated with such deployment, inadequate training, ethical dilemmas surrounding these emerging technologies, and doubts regarding its effectiveness in the democratic process (Munoriyarwa et al., 2021). Conversely, Latin American practitioners hold mixed feelings, with both optimistic and pessimistic views about the application of AI in journalism. However, they mostly perceive such tools as an opportunity rather than as a threat (Soto-Sanfiel et al., 2022). Within this rich tapestry, media and journalism play vital roles in shaping societies, enabling civic engagement, and reflecting the voices of marginalized communities across the world. The significant influence of AI deployment, as shaped by the dynamics among platforms, governments, and media, is also noteworthy worldwide. This power dynamics could lead to more influential actors gaining control over media production and information dissemination, consequently impacting the media ecosystem (de-Lima-Santos et al., 2023; Kuai et al., 2022). Understanding the nuanced landscape of AI-enabled journalism requires considering a range of crucial factors. These include the vast linguistic diversity, with hundreds of languages spoken, making language processing and content personalization a unique challenge (Gondwe, 2023). Cultural sensitivity is paramount, as news and information production must respect the values and norms of diverse societies, often vastly different across the world (Kothari & Cruikshank, 2022). Furthermore, each region faces specific challenges related to media sustainability, including economic constraints, political pressures, and issues of representation. While AI has the potential to address some of these challenges, its application is far from uniform (de-Lima-Santos et al., 2021). Local news ecosystems, for instance, play a vital role in their communities, and understanding how AI can strengthen local journalism while maintaining cultural relevance is of utmost importance. This special issue seeks to shed light on these intricacies, explore the impact of AI on journalism and media moving beyond “North” and “South” dichotomy, and delve into the challenges and opportunities that arise of AI in news context. While countries in the Global North can actively experiment with AI solutions in their newsrooms (Jones & Jones, 2021; Pashevich, 2018; Stray 2021;), those in the Global South are often either playing catch-up or simply acting as recipients of the experiments conducted by these Western, Educated, Industrialized, Rich and Democratic (WEIRD) nations. Thus, this special issue also aims to address the pressing concern of the “AI divide” across these regions, discussing the unequal access to AI technologies and knowledge, which can exacerbate existing (news production) inequalities within countries and across geographies. This can impose additional constraints on the global expansion of emerging technologies within the news media (Jamil, 2020). Understanding and mitigating this divide is a central concern, and this special issue will be a platform for scholarly inquiry and debates into these critical areas from a global perspective. With an eye on bridging gaps, promoting inclusivity, and narrowing the AI divide, this special issue seeks to gather research and insights that can inform the future of AI-enabled journalism within the “North” or the “South” in socioeconomic and political terms. We invite contributions that address but are not limited to the following themes in the context of the AI and journalism: - *AI deployment:* Comparing the development of AI technologies in newsrooms worldwide. - *Generative AI*: Leveraging this technology across the entire news value chain, transforming traditional processes and enhancing various aspects of news production, distribution, and consumption, while also necessitating careful consideration of ethical, human, and editorial implications - *AI tools for news production*: Exploring the use of AI technologies in newsrooms, including automated content generation, sentiment analysis, and fact-checking. - *Ethical and societal implications*: Examining the ethical considerations and societal impacts of AI-driven journalism in culturally and politically diverse regions. - *AI for media sustainability:* Examining innovative AI applications that promote sustainability in media organizations, revenue models, and content creation. - *AI and indigenous knowledge:* Investigating how AI technologies can promote or affect indigenous knowledge and cultural heritage in media coverage. - *AI for disaster reporting:* Analyzing the use of AI tools in disaster reporting, early warning systems, and response efforts in disaster-prone regions. - *Audience engagement and personalization*: Investigating AI-driven strategies for audience engagement, content personalization, and the role of AI in addressing language diversity. - *Media capture and democratization*: Analyzing the influence of AI on media capture, control, and the democratization of information in the Global North and South. - *Platforms dependence*: Analyzing the influence of platforms on AI deployment in the news industry. - *AI, censorship, and freedom of expression:* Assessing the impact of AI on freedom of expression, censorship, and surveillance in politically sensitive environments. - *AI and local news ecosystems: *Understanding the potential of AI in strengthening local journalism and addressing issues of representation. - *AI in investigative reporting*: Exploring the application of AI in investigative journalism, data mining, and open-source intelligence. - *AI in fact-checking*: Exploring the application of AI in fact-checking practices. - *AI and data-driven storytelling*: Investigating how data journalism is advancing worldwide and the role of AI in helping these practices, such as extracting, analyzing, and visualizing data. - *AI and health communication:* Exploring the use of AI applications in health journalism, pandemic coverage, and the dissemination of public health information. - *AI and environmental and humanitarian communication:* Exploring the use of AI applications in environmental journalism, climate crises, and humanitarian action. - *AI literacy:* Investigating the role of AI literacy in the context of technological innovations and its impact on newsrooms. - *AI and inclusivity:* Exploring how AI technologies can enhance or suppress media inclusivity and accessibility for underserved communities, including issues of language, accessibility, and representation. - *AI divide*: Addressing disparities in AI access, knowledge, and impact in the Global South in comparison to Global North/Western, Educated, Industrialized, Rich and Democratic (WEIRD) countries. - *AI and power: *AI and power dynamics in newsrooms - *AI and journalistic role:* Global perceptions of journalistic roles in the age of AI - *AI and representations*: Exploring how AI represents North-South newsrooms, journalism, and media. We look forward to receiving your contributions and exploring the dynamic intersection of artificial intelligence and journalism. Follow the link here for more details: https://bit.ly/GenerativeAIAgeJournalism. Thank you and regards, Dr Allen Munoriyarwa PhD, Journalism, University of Johannesburg, (South Africa) Google Scholar link: https://bit.ly/3fxdWPp. ORCID: https://orcid.org/0000-0001-5064-3192 Coordinator: British Academy Research: https://www.gla.ac.uk/schools/socialpolitical/research/sociology/projects/wa... Board member: Intelwatch; https://intelwatch.org.za/ Email: allenmunoriyarwa@gmail.com.