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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.

Despite growing interest in the emergence of technologies in journalistic practices, especially from the production perspective, there is still very little research on organizational structures and professional culture in relation to the deployment of these technologies. Drawing on six interviews and observation in staff meetings, this study aims to explore the nuances behind the professional roles of data journalists and how these relate to structural aspects of news organizations. The study focuses on the case of ProPublica, a news organization internationally renowned for its global excellence in data stories. This work considers boundary-making in the context of journalism and focuses on new professional roles in the news industry to produce a hybrid ethnography study based on qualitative data collected immediately before the Covid-19 pandemic hit the United States. The findings reveal the importance of hybrid profiles at ProPublica. While some journalists have had to expand their knowledge to learn more about new areas, such as coding and design, some non-journalistic professionals have had to develop writing skills, and this blurring of traditional boundaries forms an important aspect of ProPublica’s professional culture. The structure of the organization, divided into two teams engaged in cross-sector activities, helps to promote data skills and collaboration with other journalists, which also serves to mitigate any individual lack of experience on certain topics. The article concludes by suggesting that the growing importance of these new professional roles has broader implications for the development of data skills in the newsroom, and also discusses the limitations that can arise from the increasing overlap between journalistic and non-journalistic roles.

Despite growing interest in the emergence of technologies in journalistic practices, especially from the production perspective, there is still very little research on organizational structures and professional culture in relation to the deployment of these technologies. Drawing on six interviews and observation in staff meetings, this study aims to explore the nuances behind the professional roles of data journalists and how these relate to structural aspects of news organizations. The study focuses on the case of ProPublica, a news organization internationally renowned for its global excellence in data stories. This work considers boundary-making in the context of journalism and focuses on new professional roles in the news industry to produce a hybrid ethnography study based on qualitative data collected immediately before the Covid-19 pandemic hit the United States. The findings reveal the importance of hybrid profiles at ProPublica. While some journalists have had to expand their knowledge to learn more about new areas, such as coding and design, some non-journalistic professionals have had to develop writing skills, and this blurring of traditional boundaries forms an important aspect of ProPublica’s professional culture. The structure of the organization, divided into two teams engaged in cross-sector activities, helps to promote data skills and collaboration with other journalists, which also serves to mitigate any individual lack of experience on certain topics. The article concludes by suggesting that the growing importance of these new professional roles has broader implications for the development of data skills in the newsroom, and also discusses the limitations that can arise from the increasing overlap between journalistic and non-journalistic roles.

The proliferation of data journalism has enabled newsrooms to deploy technologies for both mundane and more sophisticated workplace tasks. To bypass long-term investment in developing data skills, out-of-the-box software solutions are commonly used. Newsrooms today are partially dependent on third-party platforms to build interactive and visual stories – but the business models of platforms are predisposed to changes, frequently inducing losses of stories. This article combines in-depth interviews and an ancillary survey to study the status quo and identify future challenges in embracing out-of-the-box and in-house tools, and their impact on Australian data journalism. Results indicate a dichotomy between commercial and public service media organisations. Commercial outlets are heavily reliant on out-of-the-box solutions to develop stories, due to a lack of skillsets and a shortage of skilled labour. By contrast, public service media are developing their own in-house solutions, which reflects their desire for the continuous digital preservation of data stories despite the challenges identified.

El periodismo se encuentra en un punto de cambio radical que exige a las organizaciones desarrollar nuevas ideas y nuevos formatos para la presentación de noticias. Además, el aumento de los datos, los sensores y los avances tecnológicos, especialmente en el segmento móvil, han traído beneficios inconmensurables a muchos campos de la práctica periodística, en particular al periodismo de datos. Dada la relativa novedad y complejidad de la implementación de la inteligencia artificial (IA) en el periodismo, pocas áreas han logrado implementar hasta ahora soluciones de IA personalizadas en la industria de los medios. En este estudio, a través de un enfoque de método mixto que combina la observación participante y la entrevista, se explican los obstáculos y dificultades de implementar proyectos de noticias mediante la visión artificial, un subconjunto de la IA, en una organización de noticias líder en América Latina como el diario argentino La Nación. Los resultados destacan cuatro grandes dificultades para implementar la IA, más específicamente los proyectos de visión artificial que involucran el uso de imágenes satelitales: la falta de imágenes de alta resolución, la falta de disponibilidad de infraestructura tecnológica, la ausencia de personal cualificado para desarrollar dichos códigos y un proceso de implementación prolongado y costoso que requiere de una inversión significativa. El artículo concluye con una discusión sobre la centralidad de las soluciones de IA en manos de las grandes corporaciones tecnológicas., Journalism is at a radical point of change that requires organizations to come up with new ideas and formats for news reporting. Additionally, the notable surge of data, sensors and technological advances in the mobile segment has brought immeasurable benefits to many fields of journalistic practice (data journalism in particular). Given the relative novelty and complexity of implementing artificial intelligence (AI) in journalism, few areas have managed to deploy tailored AI solutions in the media industry. In this study, through a mixed-method approach that combines both participant observations and interviews, we explain the hurdles and obstacles to deploying computer vision news projects, a subset of AI, in a leading Latin American news organization, the Argentine newspaper La Nación. Our results highlight four broad difficulties in implementing computer vision projects that involve satellite imagery: a lack of high-resolution imagery, the unavailability of technological infrastructure, the absence of qualified personnel to develop such codes, and a lengthy and costly implementation process that requires significant investment. This article concludes with a discussion of the centrality of AI solutions in the hands of big tech corporations., O jornalismo está em um ponto radical de mudança que exige que as organizações abracem novas ideias e novos formatos de reportagem. Além disso, o aparecimento de dados, sensores e avanços em tecnologia, em particular os smartphones, trouxeram benefícios imensuráveis para a prática jornalística e, principalmente, para o jornalismo de dados. Dado o seu carácter novo e a relativamente complexidade de implementar inteligência artificial (IA) em jornalismo, poucas áreas conseguiram implantar soluções de IA personalizadas na indústria de mídia. Neste estudo, através de uma abordagem mista, combinando observação participante e entrevistas, nós explicamos os obstáculos e desafios do desenvolvimento de projetos noticiosos através da visão computacional, um subconjunto da IA, em uma organização de mídia líder na América Latina, o jornal La Nación na Argentina. Os resultados mostram quatro amplas dificuldades para a implementação de IA, especialmente projetos de visão computacional usando imagens de satélite: falta de imagens de alta resolução, indisponibilidade de infraestrutura tecnológica, ausência de pessoal qualificado para desenvolver tais códigos e, um longo e caro processo de implementação que requer um investimento significativo. O artigo conclui com uma discussão sobre a centralidade da solução de IA nas mãos de grandes corporações de tecnologia.