Search results

This study explores how the national artificial intelligence (AI) strategies and policies in four sub-Saharan African countries – Mauritius, South Africa, Ghana and Gabon – influence the adoption of AI in journalism. In the journalistic world, AI have been mainly used for news gathering, production and distribution. Irrespective of the prospects, the pervasive nature of AI brings with it a host of challenges concerning privacy, gender, and ethnic bias. Despite its relevance to journalism, the challenges associated with using AI necessitate the need for policy frameworks that guide the development and usage of these technologies. At a global level, UNESCO has established a normative framework which lays out principles and standards regarding how member states formulate policies that ensures ethical and healthy development of AI. Using document analysis and the technological determinism theory, the study investigated how the national AI policies and strategies of these countries is impacting journalism and highlights the challenges to the adoption of the technology in the field. In lieu of the AI-specific laws, the countries seem to loosely rely on their data protection acts to govern aspects of AI use involving automated decision making. Mauritius was found to be the only country in the study with a set national AI strategy.

The advent of data-driven journalism has transformed the field of journalism globally, offering new ways to collect, analyse and communicate stories and information. In contexts such as Africa, where socio-political and economic contexts differ significantly from those in the Global North, the need for critical data literacy in journalism education is particularly pronounced. This chapter proposes and argues for developing critical data literacy skills among journalism students. It suggests that fostering a critical approach to data is essential for producing impactful, contextually relevant, and unbiased data-driven journalism. The chapter addresses the unique challenges faced by journalism education and presents strategies (an agenda) for integrating critical data literacy into journalism curricula.

This chapter focuses on data journalism, a relatively new brand of journalistic practices that take advantage of the growing availability and application of digital data and computational tools for news production. Although this brand of journalism has been on in some advanced democracies, it is still a relatively new development in Africa, especially Nigeria. Journalists still rely mostly on eyewitness reports and interviews to write their stories, thus leading to lack of depth in media reportage of critical issues. This chapter explores the nature of data journalism conceptualised as a social science pragmatic approach to news gathering and reporting, tracing its history and inherent strengths and weaknesses. It examines the windows of opportunities it provides towards guaranteeing transparency and accountability in Nigeria's nascent democracy. It concludes that, though data journalism complements the conventional investigative reporting to enhance good governance system in Nigeria, strengthening other institutions of government such as the police, judiciary, Economic and Financial Crimes Commission (EFCC), and Independent Corrupt Practices and other related offences Commission (ICPC) becomes imperative in entrenching accountability and transparency in Nigeria.

This study examines three significant collaborative journalism projects in the Americas: The Panama Papers, from the United States-based International Consortium of Investigative Journalists (ICIJ); “América Latina, Región de Carteles,” by Colombian-based Connectas; and the first phase of the Brazilian-based project, Comprova, supported by Brazilian Association of Investigative Journalists (Abraji) and First Draft. The work investigates what encompasses collaborative journalism; and explores whether it is a recent phenomenon of the news ecosystem, a consequence of the institutional crisis of journalism, and if it is influenced by a network-based and platformed society. A mixed-method approach is applied in a three-stage analysis: (1) desk research; (2) quantitative content analysis; and (3) qualitative semi-structured in-depth interviews. To gain a broader picture of the organizations and their respective projects, documental and bibliographical research was carried out with a focus on data from press releases, corporate reports, and articles published on the websites of the organizations coordinating the projects. Furthermore, a quantitative content analysis of 10 news articles published by each of these collaboration partnerships was completed. Finally, qualitative semi-structured in-depth interviews were conducted with the directors, managers, and professional journalists’ part of the organizations and project. This study emphasizes the importance of collaborative practices, demonstrates how collaborative practices contribute to a new modus operandi of the news ecosystem; and considers why journalists and media organizations have turned to collaborative journalism as a model of production, circulation, and distribution of journalistic investigations.

In the current post-human society, artificial intelligence (AI) and algorithms are rapidly being deployed in newsrooms around the world to enhance processes of news idea conception, newsgathering, writing, packaging and dissemination. Although AI adaptation has been ongoing especially in Western Newsrooms over the last decade, this process is only budding in sub-Saharan newsroom contexts. This study explores perceptions, use, prospects and challenges in the adaptation of AI and algorithms in newsrooms. This qualitative survey draws insights from 33 respondents from newspapers, radio stations, online media and community media in Uganda, Tanzania, Rwanda and Ethiopia. The study found varied levels of AI adoption in several newsrooms with some newsrooms not yet using AI while others were fully experimenting with a variety of tools, functionalities – even producing their own AI tools and also in change employment patterns to accommodate the skills needed within this new field. In some of the ‘inactive AI newsrooms’ individual journalists took the onus on themselves to learn and use the disruptive technologies and while the general attitudes towards AI were positive among journalists, the attitudes among management was generally considered poor. The study concludes for the benefits to be maximally leveraged, several of the bottlenecks in application must be addressed. These include the integration of ‘humans-in the loop’, journalistic principles, decolonial and local contextual perspectives in AI development and use. Such perspectives and synergies would need to be drawn from media ecosystems – including journalism education, research, policy, industry and developers.

This paper constitutes the first academic study to be made of Google Discover as applied to online journalism.

This paper constitutes the first academic study to be made of Google Discover as applied to online journalism. The study involved conducting 61 semi-structured interviews with experts that are representative of a range of different professional profiles within the fields of journalism and search engine positioning (SEO) in Brazil, Spain and Greece. Based on the data collected, the authors created five semantic categories and compared the experts' perceptions in order to detect common response patterns.

This study results confirm the existence of different degrees of convergence and divergence in the opinions expressed in these three countries regarding the main dimensions of Google Discover, including specific strategies using the feed, its impact on web traffic, its impact on both quality and sensationalist content and on the degree of responsibility shown by the digital media in its use. The authors are also able to propose a set of best practices that journalists and digital media in-house web visibility teams should take into account to increase their probability of appearing in Google Discover. To this end, the authors consider strategies in the following areas of application: topics, different aspects of publication, elements of user experience, strategic analysis and diffusion and marketing.

Although research exists on the application of SEO to different areas, there have not, to date, been any studies examining Google Discover.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2022-0574

The appropriation of artificial intelligence (AI) into everyday workplace practices is becoming pervasive. Some of the industries that have seen the improved appropriation of AI include the automotive industry, food chains and other retail businesses. The media industry in developed countries has also been appropriating AI into newsrooms ecologies. This development has left news media workers, especially in developing countries, questioning the viability of their jobs in the foreseeable future as machines take over and disrupt newsmaking and production processes. The unknowns that come with AI adoption have been met with both utopian and dystopian views in African newsrooms, especially in countries that understand less on how to deploy AI affordances. Premised on the technology acceptance model and the concept of technological appropriation and a qualitative methodology that used structured interviews with community media journalists from the Western Cape province of South Africa, this chapter examined journalists' perceptions of AI deployment in the community media space. The findings of the study show that community media journalists hold both utopian and dystopian views on the utility of AI in the community media space. While most journalists perceive AI as enhancing the efficiency and accuracy of the newsmaking process, there is a significant number of journalists who perceive AI as inimical to the legitimacy and credibility of the profession. Furthermore, AI is also seen as a threat to jobs within the journalism profession. These findings resonate with previous studies that have shown that journalists are divided on the perceived utility of AI in newsrooms.