[Air-L] CFP:Generative AI Age in Journalism: Unveiling Artificial Intelligence’s Potential and Challenges in the News Industry Worldwide

[allen munoriyarwa]

Hello Everyone,

I am writing to draw your attention to the special Issue below:

*Generative AI Age in Journalism: Unveiling Artificial Intelligence’s
Potential and Challenges in the News Industry Worldwide*

 Link: https://bit.ly/GenerativeAIAgeJournalism.

*Guest Editors:*

*Allen Munoriyarwa*

*Department of Media Studies, University of Botswana*

*Department of Communication and Media, University of Johannesburg  *

 *Mathias-Felipe de-Lima-Santos*

*Faculty of Humanities, University of Amsterdam*

*Digital Media and Society Observatory (DMSO), Federal University of São
Paulo (Unifesp)*

 D*eadlines: *

   - *Abstract Submission:* January 5th , 2024
   - *Paper Submission: *June 30th, 2024
   - *Expected Publication Date:* Q4 2024 – Q1/2025

 In recent years, the integration of artificial intelligence (AI)
technologies in journalism and media production has sparked a global
transformation in the way information is gathered, produced, and
disseminated (de-Lima-Santos & Ceron, 2021). The term AI broadly refers to
a field of computer science methods “dedicated to replicating human
intelligence" (Broussard et al., 2019, p. 673). These technologies offer
new possibilities for enhancing news gathering, content generation,
audience engagement, and data analysis. Furthermore, they possess immense
capabilities and offer incredible promises of transformation to media and
journalism. Moreover, the AI-driven journalism landscape has witnessed a
remarkable boom in the development and utilization of generative AI
technologies, such as ChatGPT and DALL-E (Gondwe, 2023). The surge of
generative AI has had a profound impact on news production, where AI
algorithms can generate articles, summaries, and even assist in
investigative reporting. These technologies have provided easy to use tools
for media organizations in creating content at scale, automating repetitive
tasks, and enhancing data analysis. While AI-driven journalism has garnered
substantial attention and analysis in different media landscapes, there is
a growing recognition of the unique implications, challenges, and
opportunities posed by AI in the news industry worldwide (Broussard et al.,
2019). This special issue aims to fill this knowledge gap by exploring the
appropriation of AI technologies in news production across different media
contexts.

The application of AI in different regions brings with it a set of
complexities that necessitate in-depth investigation. For example, previous
research has indicated that media professionals’ inclination toward AI
skepticism in Africa is influenced by concerns about potential job cuts,
the expenses associated with such deployment, inadequate training, ethical
dilemmas surrounding these emerging technologies, and doubts regarding its
effectiveness in the democratic process (Munoriyarwa et al., 2021).
Conversely, Latin American practitioners hold mixed feelings, with both
optimistic and pessimistic views about the application of AI in journalism.
However, they mostly perceive such tools as an opportunity rather than as a
threat (Soto-Sanfiel et al., 2022). Within this rich tapestry, media and
journalism play vital roles in shaping societies, enabling civic
engagement, and reflecting the voices of marginalized communities across
the world. The significant influence of AI deployment, as shaped by the
dynamics among platforms, governments, and media, is also noteworthy
worldwide. This power dynamics could lead to more influential actors
gaining control over media production and information dissemination,
consequently impacting the media ecosystem (de-Lima-Santos et al., 2023;
Kuai et al., 2022).

Understanding the nuanced landscape of AI-enabled journalism requires
considering a range of crucial factors. These include the vast linguistic
diversity, with hundreds of languages spoken, making language processing
and content personalization a unique challenge (Gondwe, 2023). Cultural
sensitivity is paramount, as news and information production must respect
the values and norms of diverse societies, often vastly different across
the world (Kothari & Cruikshank, 2022). Furthermore, each region faces
specific challenges related to media sustainability, including economic
constraints, political pressures, and issues of representation. While AI
has the potential to address some of these challenges, its application is
far from uniform (de-Lima-Santos et al., 2021). Local news ecosystems, for
instance, play a vital role in their communities, and understanding how AI
can strengthen local journalism while maintaining cultural relevance is of
utmost importance.

This special issue seeks to shed light on these intricacies, explore the
impact of AI on journalism and media moving beyond “North” and “South”
dichotomy, and delve into the challenges and opportunities that arise of AI
in news context. While countries in the Global North can actively
experiment with AI solutions in their newsrooms (Jones & Jones, 2021;
Pashevich, 2018; Stray 2021;), those in the Global South are often either
playing catch-up or simply acting as recipients of the experiments
conducted by these Western, Educated, Industrialized, Rich and Democratic
(WEIRD) nations. Thus, this special issue also aims to address the pressing
concern of the “AI divide” across these regions, discussing the unequal
access to AI technologies and knowledge, which can exacerbate existing
(news production) inequalities within countries and across geographies.
This can impose additional constraints on the global expansion of emerging
technologies within the news media  (Jamil, 2020). Understanding and
mitigating this divide is a central concern, and this special issue will be
a platform for scholarly inquiry and debates into these critical areas from
a global perspective.

With an eye on bridging gaps, promoting inclusivity, and narrowing the AI
divide, this special issue seeks to gather research and insights that can
inform the future of AI-enabled journalism within the “North” or the
“South” in socioeconomic and political terms. We invite contributions that
address but are not limited to the following themes in the context of the
AI and journalism:

   - *AI deployment:* Comparing the development of AI technologies in
   newsrooms worldwide.
   - *Generative AI*: Leveraging this technology across the entire news
   value chain, transforming traditional processes and enhancing various
   aspects of news production, distribution, and consumption, while also
   necessitating careful consideration of ethical, human, and editorial
   implications
   - *AI tools for news production*: Exploring the use of AI technologies
   in newsrooms, including automated content generation, sentiment analysis,
   and fact-checking.
   - *Ethical and societal implications*: Examining the ethical
   considerations and societal impacts of AI-driven journalism in culturally
   and politically diverse regions.
   - *AI for media sustainability:* Examining innovative AI applications
   that promote sustainability in media organizations, revenue models, and
   content creation.
   - *AI and indigenous knowledge:* Investigating how AI technologies can
   promote or affect indigenous knowledge and cultural heritage in media
   coverage.
   - *AI for disaster reporting:* Analyzing the use of AI tools in disaster
   reporting, early warning systems, and response efforts in disaster-prone
   regions.
   - *Audience engagement and personalization*: Investigating AI-driven
   strategies for audience engagement, content personalization, and the role
   of AI in addressing language diversity.
   - *Media capture and democratization*: Analyzing the influence of AI on
   media capture, control, and the democratization of information in the
   Global North and South.
   - *Platforms dependence*: Analyzing the influence of platforms on AI
   deployment in the news industry.
   - *AI, censorship, and freedom of expression:* Assessing the impact of
   AI on freedom of expression, censorship, and surveillance in politically
   sensitive environments.
   - *AI and local news ecosystems: *Understanding the potential of AI in
   strengthening local journalism and addressing issues of representation.
   - *AI in investigative reporting*: Exploring the application of AI in
   investigative journalism, data mining, and open-source intelligence.
   - *AI in fact-checking*: Exploring the application of AI in
   fact-checking practices.
   - *AI and data-driven storytelling*: Investigating how data journalism
   is advancing worldwide and the role of AI in helping these practices, such
   as extracting, analyzing, and visualizing data.
   - *AI and health communication:* Exploring the use of AI applications in
   health journalism, pandemic coverage, and the dissemination of public
   health information.
   - *AI and environmental and humanitarian communication:* Exploring the
   use of AI applications in environmental journalism, climate crises, and
   humanitarian action.
   - *AI literacy:* Investigating the role of AI literacy in the context of
   technological innovations and its impact on newsrooms.
   - *AI and inclusivity:* Exploring how AI technologies can enhance or
   suppress media inclusivity and accessibility for underserved communities,
   including issues of language, accessibility, and representation.
   - *AI divide*: Addressing disparities in AI access, knowledge, and
   impact in the Global South in comparison to Global North/Western, Educated,
   Industrialized, Rich and Democratic (WEIRD) countries.
   - *AI and power: *AI and power dynamics in newsrooms
   - *AI and journalistic role:* Global perceptions of journalistic roles
   in the age of AI
   - *AI and representations*: Exploring how AI represents North-South
   newsrooms, journalism, and media.

We look forward to receiving your contributions and exploring the dynamic
intersection of artificial intelligence and journalism.

Follow the link here for more details:
https://bit.ly/GenerativeAIAgeJournalism.

Thank you and regards,
Dr Allen Munoriyarwa
PhD, Journalism, University of Johannesburg, (South Africa)
Google Scholar link: https://bit.ly/3fxdWPp.
ORCID: https://orcid.org/0000-0001-5064-3192
Coordinator: British Academy Research:
https://www.gla.ac.uk/schools/socialpolitical/research/sociology/projects/watchingthewatchersstrengtheningpublicoversightofintelligencedrivensurveillance/
Board member: Intelwatch; https://intelwatch.org.za/
Email: allenmunoriyarwa at gmail.com.