In this chapter, we explore the intersection of data journalism practices with issues of (governance) transparency and accountability. We advance the argument that data journalism can be instrumental in helping journalists seek accountability in opaque regimes that have an uneasy relationship with watchdog journalism. We use the Zimbabwe’s post-coup regime to demonstrate that at the centre of political authoritarianism, is a refusal to account, and a culture of non-transparency. Faced with such, the media can utilise publicly available sources of data journalism to exercise their responsibility. Data journalism is, hence, critical as a media practice that provides avenues for journalists in semi-authoritarian regimes to continuously pursue their mandates as accountability seekers. Our chapter contributes to emerging literature on data journalism in Africa, especially in semi-authoritarian contests like that of Zimbabwe.
Category: Sector: Media
Hard Questions: Media
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Evaluating Online AI Detection Tools: An Empirical Study Using Microsoft Copilot-Generated Content
Our findings reveal significant inconsistencies and limitations in AI detection tools, with many failing to accurately identify Copilotauthored text. Examining eight freely available online AI detection tools using text samples produced by Microsoft Copilot, we assess their accuracy and consistency. We feed a short sentence and a small paragraph and note the estimate of these tools. Our results suggest that educators should not rely on these tools to check for AI use.
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Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems
Artificial Intelligence (AI) has paved the way for revolutionary decision-making processes, which if harnessed appropriately, can contribute to advancements in various sectors, from healthcare to economics. However, its black box nature presents significant ethical challenges related to bias and transparency. AI applications are hugely impacted by biases, presenting inconsistent and unreliable findings, leading to significant costs and consequences, highlighting and perpetuating inequalities and unequal access to resources. Hence, developing safe, reliable, ethical, and Trustworthy AI systems is essential. Our team of researchers working with Trustworthy and Responsible AI, part of the Transdisciplinary Scholarship Initiative within the University of Calgary, conducts research on Trustworthy and Responsible AI, including fairness, bias mitigation, reproducibility, generalization, interpretability, and authenticity. In this paper, we review and discuss the intricacies of AI biases, definitions, methods of detection and mitigation, and metrics for evaluating bias. We also discuss open challenges with regard to the trustworthiness and widespread application of AI across diverse domains of human-centric decision making, as well as guidelines to foster Responsible and Trustworthy AI models.
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Unravelling socio-technological barriers to AI integration: A qualitative study of Southern African newsrooms
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?
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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.