Artificial Intelligence Practices in Everyday News Production: The Case of South Africa’s Mainstream Newsrooms

Munoriyarwa, Allen; Chiumbu, Sarah; Motsaathebe, Gilbert

doi:10.1080/17512786.2021.1984976

Cited by 34 publications

(17 citation statements)

References 29 publications

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“…This cynicism is not new, and similar sentiments have been seen in studies in South Africa (Munoriyarwa et al, 2021) and Nigeria (Guanah et al, 2020;Nwanyanwu & Nwanyanwu, 2021). However, where company structure, leadership, and culture are open to innovation and trying novel technologies, the implementation of AI has been successful and eased the work of journalists and other production team members.…”

Section: Barriers and Facilitators Of Adoption And Use Of Ai In Kenya...supporting

confidence: 67%

“…However, factors determining the newsworthiness of specific contents are also deeply socio-political and difficult to encode in most AI technologies (Stray, 2019). Furthermore, this may explain why we saw only partial appropriation of AIthe use of AI for only specific purposes (Munoriyarwa et al, 2021) -in the media houses that were engaged in this study.…”

Section: The Use Of Ai In Kenyan Newsroomsmentioning

confidence: 91%

“…Traditional media houses have undergone significant reorganization and modifications of newsrooms operations, field and investigative operations, news gathering and writing, and news dissemination and customer engagement by integrating AI and digital technologies. There are three levels of AI integration in media houses depending on the automation of various tasks in the three stages of the news production process: research, production, and dissemination (Munoriyarwa et al, 2021). Further, Munoriyarwa et al posit that the three levels are: (i) Holistic AI appropriation -where most of the news production functions have been delegated to AI with limited journalist functions, (ii) Technological appropriation -where technological hardware equipped with AI features is used in news gathering but editing and writing still used by humans, and (iii) Partial appropriationwhere AI is used for specific functions at different levels of the news production process, and there is considerable human-AI interaction.…”

Section: Introductionmentioning

confidence: 99%

“…Although the emergence of AI and social media has altered the news media landscape and consumption, ethical and professional journalism remains critical in providing reliable, timely, and relevant news information (Nwanyanwu & Nwanyanwu, 2021). From the early times of adoption of AI and the embracement of emerging technologies by media houses in the mid-2000s, the biggest fear in the industry was the future of journalism, given that machines could be programmed to execute any function as humans (Jamil, 2021;Miroshnichenko, 2018;Munoriyarwa et al, 2021;Mutsvairo et al, 2020). Additionally, ethical questions around biased algorithms, data protection, surveillance, and privacy concerns, hacking robots, and lack of clear policies and guidelines on the use, control, and regulation of AI use, especially in the global south, continue to present socio-political barriers to AI integration (Monti, 2019).…”

Section: Introductionmentioning

confidence: 99%

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The Adoption of Artificial Intelligence in Newsrooms in Kenya: a Multi-case Study

Kioko

Booker

Chege

et al. 2022

ESJ

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The deployment of Artificial Intelligence (AI) in newsrooms is gaining prominence worldwide, with the technology being used to enhance the processes of news gathering, packaging, and distribution. The study was guided by two research questions: what factors drive/hinder(s) the adoption of AI or lack of it in newsrooms in Kenya? Moreover, what opportunities do journalists feel are offered by adopting AI in newsrooms in Kenya? A qualitative research approach and descriptive research design were employed to investigate the adoption of AI in newsrooms in Kenya. British Broadcasting Corporation (BBC-Africa) and Radio Africa Group (RAG) media organizations were the target population. As a research strategy, a multi-case method was employed. The researchers conducted in-depth interviews with newsroom-based participants. A purposive sampling technique was used to select participants for the research. Collected data were analyzed thematically. The paper identified six factors driving the adoption of AI or lack of it: management buy-in, cost, technical skills, clarity of user case, perception, and company structure. Further, the study identified three challenges presented by adopting AI: lack of quality data, ethical concerns, and unpredictability of the technology’s impact. The study concludes that AI offers excellent opportunities for newsrooms in Kenya to explore. Still, some obstacles need to be addressed before they can benefit fully from the technology. The study projects that human and automated journalism will become closely integrated in the future and recommends that newsrooms in Kenya prepare to embrace AI by laying the foundation for its adoption. Media schools should update curricula to prepare journalists to work with emerging technologies such as AI. Further research is needed to identify the specific skill sets required for Kenyan digital journalists to embrace AI fully. Scholars should investigate how AI can shape new business models given shrinking revenues in the media.

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Section: Barriers and Facilitators Of Adoption And Use Of Ai In Kenya...supporting

confidence: 67%

Section: The Use Of Ai In Kenyan Newsroomsmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Adoption of Artificial Intelligence in Newsrooms in Kenya: a Multi-case Study

Kioko

Booker

Chege

et al. 2022

ESJ

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“…In our list, only 5.38% (N = 5) of the cases were from Asia, and 2.15% (N = 2) were from Oceania. The application of AI in African newsrooms appears to be very limited, as shown in prior studies (Kothari and Cruikshank 2021;Munoriyarwa et al 2021).…”

Section: An Overview Of the Ai In News Mediamentioning

confidence: 97%

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

de-Lima-Santos

Ceron

2021

Journalism and Media

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In recent years, news media has been greatly disrupted by the potential of technologically driven approaches in the creation, production, and distribution of news products and services. Artificial intelligence (AI) has emerged from the realm of science fiction and has become a very real tool that can aid society in addressing many issues, including the challenges faced by the news industry. The ubiquity of computing has become apparent and has demonstrated the different approaches that can be achieved using AI. We analyzed the news industry’s AI adoption based on the seven subfields of AI: (i) machine learning; (ii) computer vision (CV); (iii) speech recognition; (iv) natural language processing (NLP); (v) planning, scheduling, and optimization; (vi) expert systems; and (vii) robotics. Our findings suggest that three subfields are being developed more in the news media: machine learning, computer vision, and planning, scheduling, and optimization. Other areas have not been fully deployed in the journalistic field. Most AI news projects rely on funds from tech companies such as Google. This limits AI’s potential to a small number of players in the news industry. We made conclusions by providing examples of how these subfields are being developed in journalism and presented an agenda for future research.

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Innovative Journalism Practices: Insights for Reporting Science and Health Issues

Fahmy,

Attia

2024

Palgrave Handbook of Science and Health Journalism

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Artificial Intelligence Practices in Everyday News Production: The Case of South Africa’s Mainstream Newsrooms

Cited by 34 publications

References 29 publications

The Adoption of Artificial Intelligence in Newsrooms in Kenya: a Multi-case Study

The Adoption of Artificial Intelligence in Newsrooms in Kenya: a Multi-case Study

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

Innovative Journalism Practices: Insights for Reporting Science and Health Issues

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