Research

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14 pages, 1265 KiB

Open AccessArticle

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

by Mathias-Felipe de-Lima-Santos and Wilson Ceron

Journal. Media 2022, 3(1), 13-26; https://0-doi-org.brum.beds.ac.uk/10.3390/journalmedia3010002 - 30 Dec 2021

Cited by 37 | Viewed by 28878

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Algorithms and Artificial Intelligence in Journalism and Media)

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16 pages, 1744 KiB

Open AccessArticle

An Affirmative Approach to Teaching Critical Data Studies

by J. J. Sylvia IV

Journal. Media 2021, 2(4), 641-656; https://0-doi-org.brum.beds.ac.uk/10.3390/journalmedia2040038 - 21 Oct 2021

Viewed by 3187

Abstract

This article proposes an affirmative theoretical framework for teaching students about social media, algorithms, and critical data studies and offers a concrete example of an assignment that can be used to help students better understand how social media sites impact our processes of [...] Read more.

This article proposes an affirmative theoretical framework for teaching students about social media, algorithms, and critical data studies and offers a concrete example of an assignment that can be used to help students better understand how social media sites impact our processes of subjectivation, or how we are created as subjects. This pedagogical approach is situated within larger conversations about how to best approach media literacy, digital literacy, and other emerging 21st century literacies. Drawing upon a pedagogical action research methodology, this article analyzes student projects and reflections to determine how one can actively participate in one’s own processes of subjectivation as they relate to social media, as well as what factors facilitate or limit this ability. I argue that a deeper understanding of how platforms and algorithms function increases one’s ability to intervene in their own processes of subjectivation. Further, I analyze student projects to demonstrate how the assignment helped students better conceptualize the ways that their data were being captured and then used by Facebook. This analysis showed that the inherent for-profit nature of the Facebook platform limits the possibility of intervention ability by design. These results suggest that new approaches to social media platforms, such as those that are non-profit or for the public good, might open further opportunities for more creative interventions. These experimentations at both the level of the user and the platform align well with an affirmative critical theory approach of experimentation and counter-actualization. Full article

(This article belongs to the Special Issue Algorithms and Artificial Intelligence in Journalism and Media)

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Review

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14 pages, 920 KiB

Open AccessReview

Algorithmic Journalism—Current Applications and Future Perspectives

by Efthimis Kotenidis and Andreas Veglis

Journal. Media 2021, 2(2), 244-257; https://0-doi-org.brum.beds.ac.uk/10.3390/journalmedia2020014 - 21 May 2021

Cited by 18 | Viewed by 12522

Abstract

Journalism, more so than other professions, is entangled with technology in a unique and profoundly impactful way. In this context, the technological developments of the past decades have fundamentally impacted the journalistic profession in more ways than one, opening up new possibilities and [...] Read more.

Journalism, more so than other professions, is entangled with technology in a unique and profoundly impactful way. In this context, the technological developments of the past decades have fundamentally impacted the journalistic profession in more ways than one, opening up new possibilities and simultaneously creating a number of concerns for people working in the media industry. The changes that were brought about by the rise of automation and algorithmic technology can mainly be observed in four distinct fields of application within journalism: automated content production, data mining, news dissemination and content optimization. This article focuses on algorithmic journalism and aims to highlight the ways that algorithmic technology is being utilized within those fields, as well as pointing out the ways in which these developments have altered the way journalism is being exercised in the modern world. The study also discusses challenges related to these technologies that are yet to be addressed, as well as potential future implementations related to algorithmic journalism that have the capacity to improve on the foundation of automation in the news industry. Full article

(This article belongs to the Special Issue Algorithms and Artificial Intelligence in Journalism and Media)

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