This study explores the socio-technological barriers to the adoption of artificial intelligence (AI)-powered solutions in three countries of the global south – South Africa, Lesotho, Eswatini, Botswana and Zimbabwe. Through 20 in-depth interviews with key stakeholders, it examines the distribution and circulation of AI technologies within selected newsrooms. Furthermore, the article explores socio-technological obstacles to the integration of AI among journalists. Lastly, it examines the consequences of these socio-technological obstacles to journalism. The article specifically seeks to answer three questions: How are AI technologies integrated in southern African newsrooms? What are the socio-technological barriers attendant to the use of AI in selected news organisations of sub-Saharan Africa? What are the implications of these socio-technological barriers to the process of news production in these newsrooms?
Category: Hard Questions: Media
Hard Questions: Media
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Digitization and Political Participation in the MENA Region: Egypt, Kuwait, and Tunisia
The article highlights the link between digitization and political participation in three Middle Eastern countries: Egypt, Kuwait, and Tunisia. The role of the Internet and social media in political engagement is thoroughly discussed from a historical-comparative perspective. Using micro and macro level data, the study analyzes the usage of new online technologies and online political participation.
The findings provide valuable insights for understanding the intricate nature of online political participation and the paradox between digital engagement and traditional political involvement. Despite the expansion of digital media, traditional political interest and participation has decreased. Egypt and Kuwait demonstrate advanced stages of digitization with widespread Internet access, while Tunisia’s progress is varied. -
Artificial intelligence skepticism in news production: The case of South Africa’s mainstream news organizations
This chapter demonstrates that the celebratory acceptance of artificial intelligence (AI) appropriation, popular in mainstream scholarly discourses of AI, is often colored by an emerging, strong pushback by skeptical journalists. Using the case of South African journalists, we make two broad but related arguments. First, we argue that skepticism about AI among journalists in South Africa should be linked to the broader debates about the future and purpose of journalism in post-apartheid South Africa. Second, we argue that journalists view themselves as a peculiar community with a specific role of serving democracy—a role that will not sync neatly with AI practices. This chapter contributes to debates on AI and news production practices in less-explored global South contexts.
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Data journalism and investigative news reporting practices during the pandemic: The case of Zimbabwe and South Africa
This chapter interrogates the opportunities and challenges provided by data journalism to investigative journalists during the pandemic. Our findings reveal a paradoxical contribution of data journalism to investigative journalism. On the one hand, unprepared newsrooms and journalists found it hard to understand the practice, whose demands were “foreign” to some journalists. Yet on the other hand, data-driven journalism provided immense opportunities to investigative journalists to play their monitory role more effectively – holding the ruling elites to account, providing “lively and real-time” fact-based news on the pandemic, countering state propaganda on the pandemic and widening investigative journalists’ news sourcing routines.
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Artificial intelligence practices in everyday news production: The case of South Africa’s mainstream newsrooms
This article explores artificial intelligence (AI) uptake in selected South African mainstream newsrooms. It seeks to determine the extent to which AI has been adopted and how journalists and editors perceive its appropriation in newsmaking practices. To address these two broad aims, the study used in-depth interviews with journalists and editors. Our findings suggest a slow, varied but methodical uptake of AI practices in South Africa’s mainstream newsrooms. We deduced three uses of AI in these newsrooms. The first is what we call the holistic appropriation of AI. The second one is the exclusively technological appropriation of AI, and the last one is the task-specific appropriation of AI. This varied uptake of AI is taking place against a deep-seated skepticism with this technology.
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Exploring data journalism practices in Africa: data politics, media ecosystems and newsroom infrastructures
Extant research on data journalism in Africa has focused on newsroom factors and the predilections of individual journalists as determinants of the uptake of data journalism on the continent. This article diverts from this literature by examining the slow uptake of data journalism in sub- Saharan Africa through the prisms of non-newsroom factors. Drawing on in-depth interviews with prominent investigative journalists sampled from several African countries, we argue that to understand the slow uptake of data journalism on the continent; there is a need to critique the role of data politics, which encompasses state, market and existing media ecosystems across the continent. Therefore, it is necessary to move beyond newsroom-centric factors that have dominated the contemporary understanding of data journalism practices.
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Google news initiative’s influence on technological media innovation in Africa and the Middle East
The Google News Initiative (GNI) aims to collaborate closely with the news industry and financially support the creation of quality journalism in the digital age. It also aims to bring technological advancements and innovation into newsrooms’ operations. Drawing on journalism innovation and responsible innovation theories, this study examines GNI beneficiaries in Africa and the Middle East. To address this, we analysed GNI projects’ descriptions combined with thirteen (n= 13) in-depth interviews with leading actors and beneficiary news organisations to answer two main questions:(a) What are the main characteristics of the technological innovations proposed by GNI Innovation Challenge grantees in Africa and the Middle East? and (b) How are these news media organisations becoming increasingly dependent on these platforms’ technological and financial aspects? Anchored in journalism innovation, responsible innovation, and platformisation theories, our findings show that funded organisations heavily depend on Google’s technological and financial infrastructure to innovate. Furthermore, we note that some projects do not offer a clear path for sustainability in the future. We further argue that this initiative builds an infrastructure of power and dependency that poses risks to responsible innovation in journalism. Our study contributes to extant scholarship on digital platforms and their role in the infrastructure of news organisations, creating power asymmetries between those who serve as the backbone for data flows and technological processes and those dependent on these institutions.
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Diving into data: Pitfalls and promises of data journalism in semi-authoritarian contexts
This paper calls for greater scrutiny of data journalism as a practice in the semi authoritarian context of Zimbabwe. Based on in-depth interviews with practising journalists in Zimbabwe, this paper answers two main questions: In what ways is data journalism practised in the Zimbabwean context? To what extent are newsrooms in Zimbabwe “tooled” and capacitated for data journalism practices? We note that data journalism is widely understood by individual journalists in this country but paradoxically less practised due to many challenges. By answering these two questions, we sustain an argument that data journalism appropriation in semi-authoritarian contexts can be instrumental in promoting monitorial democracy and reversing media decadence.
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From the classroom to the newsroom: A critical route to introduce AI in journalism education
From a computer vision application to monitor elections transparency in Argentina to automated real estate texts in Norway, and everything in between, Artificial Intelligence powered tools are changing journalism. Scholars have taken note, and the academic production of AI in journalism has gained considerable ground in the last five years. However, research on how journalism education deals with AI influence in the industry is scarce. Based on a self-training method using available online free courses for journalists and a review of university teaching initiatives, this article proposes key elements to trace teaching trajectories to introduce AI into journalism curriculum. Included are recommendations for drawing a path to teaching journalism students to think critically about AI and, at the same time, to understand the available tools for reporting and investigating in a complex context where journalism lives in a profound state of crisis.
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Data journalism in the age of big data: An exploration into the uptake of data journalism in leading south African Newspapers
The growing capacity to generate large quantities of data as a result of rapid technological change in the recent past has meant that increasingly, journalists everywhere are under pressure to find new ways of handling this information deluge, processing and packaging it in ways that allow ease of access for their readers. These data blizzards have been further intensified by the ever-expanding social media networks that keep churning out large volumes of information at unprecedented speed, making gathering, processing and packaging information in visualisable form all the more important. The rise of data journalism is in part a direct response to this, as it provides journalists the critical tools to manipulate data on complex issues such as national budgets, election manifestos and national census for innovative storytelling. This chapter explores the emergence of data journalism in South Africa and analyses its …
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Deep Learning based Automatic Image Caption Generation
The paper aims at generating automated captions by learning the contents of the image. At present images are annotated with human intervention and it becomes nearly impossible task for huge commercial databases. The image database is given as input to a deep neural network (Convolutional Neural Network (CNN)) encoder for generating “thought vector” which extracts the features and nuances out of our image and RNN (Recurrent Neural Network) decoder is used to translate the features and objects given by our image to obtain sequential, meaningful description of the image. In this paper, we systematically analyze different deep neural network-based image caption generation approaches and pretrained models to conclude on the most efficient model with fine-tuning. The analyzed models contain both with and without `attention’ concept to optimize the caption generating ability of the model.
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The impact of India-UK co-production agreement: A systematic review of transmedia storytelling and business models in films
The concept of transmedia storytelling is unique in the sense that it entails telling different portions of a story on separate media platforms. Furthermore, it varies from other forms of cross-platform distribution. The adaption of transmedia storytelling perspectives and business models in creative co-production ventures is an evolving phenomenon, which presents scarce evidence in extant studies. In the light of the recent India-UK co-production treaty, this paper is aimed at offering a thematic analysis of evidence concerning the transmedia storytelling and business models in films and co-production ventures. The paper reviews existing studies and published work over the past fifty years to suggest a thematic map of research for future research ventures in this fairly under-researched area. Along with several crucial findings, the study confirms that more focused studies in the area will help to form clear assertions about the cultural, artistic, and economical possibilities of the film co-production agreement between the Republic of India and the United Kingdom and bilateral impacts of the same in creative agendas. The study offers crucial practical and theoretical implications for future analysis of the creative progression of co-production elements, which will also map the developmental graph of transmedia evolution, and also the variables involved in the exchange of practice facilities and infrastructure between the two countries.