A Review of Artificial Intelligence Adoptions in the Media Industry

Chan‐Olmsted, Sylvia M.

doi:10.1080/14241277.2019.1695619

Cited by 87 publications

(41 citation statements)

References 16 publications

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“…In deep learning, algorithms use statistical techniques to solve problems through models based on large and complex datasets with little human intervention. In other words, deep learning replicates the human brain's learning capabilities and is inspired by the structure and function of neural networks (Chan-Olmsted, 2019;Hassaballah & Awad, 2020). These networks simulate "large, multilayered webs of virtual neurons, which enable a computer to learn to recognize abstract patterns" (Castro & New, 2016, p. 3).…”

Section: Computer Vision a Branch Of Artificial Intelligencementioning

confidence: 99%

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From Data Journalism to Artificial Intelligence: Challenges Faced by La Nación in Implementing Computer Vision in News Reporting

de-Lima-Santos

Salaverría

2021

Pacla

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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.

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Section: Computer Vision a Branch Of Artificial Intelligencementioning

confidence: 99%

“…In journalism, CV can accelerate the editing process and enable journalists to source evidence for investigative pieces. So far, scholars have paid little attention to CV and its implications for journalism (Chan-Olmsted, 2019).…”

Section: Computer Vision a Branch Of Artificial Intelligencementioning

confidence: 99%

From Data Journalism to Artificial Intelligence: Challenges Faced by La Nación in Implementing Computer Vision in News Reporting

de-Lima-Santos

Salaverría

2021

Pacla

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“…Presently, there are also relevant literature reviews in the AIEL field, but some of these literature reviews only focus on a certain discipline (e.g., mathematics, Hwang and Tu, 2021 ) or a specific field ( Chan-Olmsted, 2019 ; George and Lal, 2019 ). Tang et al (2021) conducted a systematic review and co-cited network analysis on the application trend of artificial intelligence in online learning.…”

Section: Introductionmentioning

confidence: 99%

Research Landscape of Artificial Intelligence and e-Learning: A Bibliometric Research

Jia

Wang

et al. 2022

Front. Psychol.

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While an increasing number of organizations have introduced artificial intelligence as an important facilitating tool for learning online, the application of artificial intelligence in e-learning has become a hot topic for research in recent years. Over the past few decades, the importance of online learning has also been a concern in many fields, such as technological education, STEAM, AR/VR apps, online learning, amongst others. To effectively explore research trends in this area, the current state of online learning should be understood. Systematic bibliometric analysis can address this problem by providing information on publishing trends and their relevance in various topics. In this study, the literary application of artificial intelligence combined with online learning from 2010 to 2021 was analyzed. In total, 64 articles were collected to analyze the most productive countries, universities, authors, journals and publications in the field of artificial intelligence combined with online learning using VOSviewer through WOS data collection. In addition, the mapping of co-citation and co-occurrence was explored by analyzing a knowledge map. The main objective of this study is to provide an overview of the trends and pathways in artificial intelligence and online learning to help researchers understand global trends and future research directions.

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“…The academic scholarship of AI has been part of computer science for decades, but the automation of cognitive tasks became possible only after the developments relating to data, sensors, and advances in technology (Chan-Olmsted 2019). The ubiquity of computing has become apparent and has shown the different approaches that can be achieved using AI.…”

Section: Artificial Intelligence In Its Current Manifestationmentioning

confidence: 99%

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

de-Lima-Santos¹,

Ceron²

2021

Preprint

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In recent years, news media have been hugely disrupted by the potential of technological-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 shown the different approaches that can be achieved using AI. We analyzed the news industry AI adoption based on the seven subfields emanated from 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 more developed in the news media: machine learning, planning, scheduling &amp; optimization, and computer vision. Other areas are still not fully deployed in the journalistic field. Most of the AI news projects rely on funds from tech companies, such as Google. This limits the potential of AI in the news industry to a small number of players. We conclude by providing examples of how these subfields are being developed in journalism and present an agenda for future research.

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A Review of Artificial Intelligence Adoptions in the Media Industry

Cited by 87 publications

References 16 publications

From Data Journalism to Artificial Intelligence: Challenges Faced by La Nación in Implementing Computer Vision in News Reporting

From Data Journalism to Artificial Intelligence: Challenges Faced by La Nación in Implementing Computer Vision in News Reporting

Research Landscape of Artificial Intelligence and e-Learning: A Bibliometric Research

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

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