[Commlist] Call for Papers - Emerging Media (SAGE): AI from a Human and Responsible Perspective: Challenges and Prospects for the Media and News Industries External

***Special Issue: AI from a Human and Responsible Perspective: 
Challenges and Prospects for the Media and News Industries***

*Editors: Mathias-Felipe de-Lima-Santos (University of Amsterdam) and 
Sadia Jamil (University of Nottingham in Ningbo)

*Journal: Emerging Media by SAGE (https://journals.sagepub.com/home/EMM 
<https://journals.sagepub.com/home/EMM>)

**Open Access – No Article Processing Charges**

**Timeline**

Abstracts: November 15th, 2023

Full Papers Submission: April 30th 2024

Publication: After acceptance, the paper will be published online first, 
followed by inclusion in a forthcoming issue expected in either Q4/2024 
or Q1/2025

Artificial Intelligence (AI) promises enormous benefits, such as 
economic growth, social development, human well-being, and safety 
improvement. Conceptually, the notion of “artificial intelligence” can 
be more narrowly perceived as “a branch of computer science focused on 
simulating human intelligence” (Broussard et al. 2019, 673). In other 
words, AI is understood as any sort of computational system that relies 
on algorithmic models as well as large and complex datasets to replicate 
the human brain’s learning capabilities (de-Lima-Santos and Ceron 2022; 
Diakopoulos 2019). In the last decade, AI applications have increased to 
an unprecedented level in the media industry after the developments 
relating to data, sensors, and advances in emerging technologies. AI is 
transforming the media and entertainment industries by changing existing 
relationships, transforming how activities are performed, reinventing 
business models, expanding the power of data, and permeating the entire 
value chain of these industries, from content production and 
distribution to audience consumption (Chan-Olmsted 2019).Much of the AI 
disruption in the media and news industries is evident through the 
enhanced interactivity through content recommendation and discovery 
tools, increased audience interest using augmented audience experience, 
and the improved delivery of data-intensive, personalized content to the 
audience, just to mention a few. In journalism, AI solutions have the 
potential to revolutionize news production, such as automated news 
processes and enhanced investigative reporting through computer vision 
models or expert systems (Broussard 2015; de-Lima-Santos and Salaverría 
2021), distribution such as recommender systems (Mitova et al. 2022), 
the relationship between media and news consumers, e.g., adaptative 
paywalls mechanisms (Davoudi et al. 2018) and new business strategies 
(de-Lima-Santos et al. 2022), and more broadly, the journalistic 
environmental conditions that shape the news media ecosystem in any 
context (Jamil 2020; Dorr 2016).The challenges of integrating AI into 
media and news ecosystems might be significant considering these 
products’ unique social impacts on society. Technologies do not operate 
in isolation, and the human in the loop is essential to deliver the 
desired outcomes. The scholarly literature has pointed out a number of 
ethical dilemmas and questions that need to be addressed concerning AI 
systems. The low level of explainability, data biases, data security, 
data privacy, and ethical problems of AI-based technology pose 
significant risks for users, developers, humanity, and societies.To 
address this, researchers have proposed a number of concepts and 
theories. For example, the notions of “machine ethics,” “computer 
ethics,” and "fair-ML" (fairness-aware machine learning) in practice are 
used to describe the concern with surrogate agents of humans and their 
impact on ethical issues, such as privacy, property, and power (Moor 
2006). More recently, the concept of “Responsible AI” has attracted 
massive attention from governments, companies, and organizations to 
address the ability of AI solutions to behave and make decisions in a 
responsible way, that is, ethical development of these systems to 
benefit the individuals, society and its environment, while minimizing 
the risk of negative consequences (Benjamins et al. 2019; Burkhardt et 
al. 2019; Cheng et al. 2021; Clarke 2019; Ghallab 2019; Lu et al. 2022; 
Sambasivan and Holbrook 2019; Schiff et al. 2020; Stenbom and Størmer 
2020; Trattner et al. 2022). In this respect, certain principles should 
be addressed to establish a transparent, governance structure that 
builds confidence and trust in AI technologies, such as fairness, 
explainability, robustness, traceability and privacy.Similarly, the use 
of human-centric ethical considerations when applied to an AI context, 
known as Human–AI teaming (HAIT), presents additional challenges, as the 
ethical principles and moral theories that justify them are not yet 
computable by machines and may conflict with social, cultural, and moral 
values (Pflanzer et al. 2022). Furthermore, it is crucial to recognize 
that AI-driven tools have emerged in the well-developed economies of the 
Global North, making economic and social benefits remain geographically 
concentrated primarily in this area. Despite these discussions, 
Responsible and Human AI in the media and news industry is still in its 
infancy.This special issue delves into the transformative potential of 
AI in the media and news sectors. It discusses the rich context that the 
interplay between AI, big data, and the media and news industries are 
offering to examine the broader implications of technological 
advancements on society and human interactions. By investigating topics 
such as responsible AI, human-AI collaboration, privacy and 
surveillance, liability challenges, data biases, and cultural variations 
in AI adoption, this special issue on “AI from a Human and Responsible 
Perspective: Challenges and Prospects for the Media and News Industries” 
expands the boundaries of critical scholarly research in the realm of 
emerging media. The recognition of ethical dilemmas, privacy concerns, 
and biases inherent in AI systems aligns with existing research that has 
emphasized the importance of addressing these issues for the responsible 
and beneficial deployment of AI technologies.Additionally, this special 
issue aims to explore the current state of AI from a human and 
responsible in diverse contexts, devoting particular attention to 
evolving standards, conventions, best practices, and challenges that 
recognizes the imperative of addressing these challenges in media and 
news industries worldwide. As a result, this special issue aims to help 
the media industry to better evolve technologically in a responsible and 
human-centered AI. We welcome contributions from different disciplines. 
Possible themes to be examined empirically, theoretically, practically, 
and methodologically in relation to one or more following 
topics:Responsible AI in the media and news industry;Human AI from a 
media and news industries perspective;AI and the issues of privacy and 
surveillance faced by journalists and media practitioners.The challenge 
of liability for news media organizations and journalists;Data biases, 
accuracy and authenticity;The cultural approaches to AI in the Global 
South;The divide between the Global North and South in the realms of AI 
and media;The limitations for responsible and human practices for AI in 
media and news;The differences in responsible AI approaches by media and 
news industries worldwide.The human perspective in AI systems for media 
and news worldwide;The social aspects, such as the interaction of 
operators with technologies and cultural values, and the institutional 
elements of AI-enabled systems in media and news industries;The 
implications of Ethical AI in investigative journalism;Fairness and bias 
in media and news;Robustness of AI systems to build trust in 
media;Reliability and safety of AI systems for media and 
news;Interpretability and audience knowledge;Explainability in media and 
news content;Marginalized communities and the use of AI in media.

**Submission Instructions**

Extended abstracts (400-600 words), accompanied by a 100-150-word bio 
introducing relevant expertise of each author should be sent no later 
than **November 15** to (mathias.felipe /at/ unifesp.br) 
<mailto:(mathias.felipe /at/ unifesp.br)> and (sadia.jamil /at/ nottingham.edu.cn) 
<mailto:(sadia.jamil /at/ nottingham.edu.cn)>.

Manuscripts will be submitted through the journal’s website. Authors 
must indicate that they wish to have their manuscript considered for 
this Special Issue. Three types of articles will be considered for this 
special issue:

*Original research articles (both empirical and conceptual papers are 
welcomed) are up to 10,000 words (including abstract, acknowledgments, 
references, tables, figures, and conflict of interest).

*Research notes are extensions or replications to previously published 
research, short descriptions of research projects that did not provide 
publishable results but represent valuable information. These are 
between 3,000 and 5,000 words, including references.

*Colloquium are papers that are along the lines of opinion or op-ed 
pieces. They are between 3,000 and 5,000 words, including references.



---------------
The COMMLIST
---------------
This mailing list is a free service offered by Nico Carpentier. Please use it responsibly and wisely.
--
To subscribe or unsubscribe, please visit http://commlist.org/
--
Before sending a posting request, please always read the guidelines at http://commlist.org/
--
To contact the mailing list manager:
Email: (nico.carpentier /at/ commlist.org)
URL: http://nicocarpentier.net
---------------