Artificial Intelligence in News Media: the Case of Local Journalism. by NT

Artificial Intelligence in News Media: the Case of Local Journalism. by NT

https://vimeo.com/574374212

A MeCCSA Local and Community Media Network Virtual research seminar. Abstracts of presentations: PhD Carl-Gustav Linden, Associate Professor of Data Journalism, University of Bergen, Norway In this talk, I will analyse AI strategies in four Nordic news agencies, how they serve local newsrooms with content or applications and what plans for the future they have. The case study is based on interviews with representatives of four news agencies, STT (Finland), NTB (Norway), TT (Sweden) and Ritzau (Denmark). We will specifically explore access to digital data as a driving force for automation. The Nordic states and local government produce massive amount of open access data, also real time data, which can be used for many purposes. News agencies have good reasons to adopt new technology that makes their work more efficient and have been a leading force in news automation (Lindén, 2017; Fanta, 2017). The four Nordic news agencies have all been on the forefront when it comes to, for instance, the use of natural language technology for media purposes. Automation in local journalism: The views of news consumers, editors and executives in the UK and Germany Professor Neil Thurman, University of Munich, Bartosz Wilczek, University of Munich, Florian Stalph, Florian Stalph and Sina Thäsler-Kordonouri, University of Munich, Germany This talk will present early results from two studies. The first investigates how local newspapers in Germany are adopting AI for input, throughput and output activities along the news value chain and what factors drive or constrain that adoption. Twenty online/digital editors and executives at 14 of the largest local German newspapers were interviewed, and the data analysed using cross-case pattern matching. The results reveal whether and how news automation is being used; and the factors—including linguistic, financial, and data availability—constraining its adoption. The second study is a qualitative comparative analysis of data-driven local news texts written with various levels of automation and none. Workshops were held with 31 participants from various UK regions during which they read articles from a range of sources, including PA Media’s RADAR (Reporters And Data And Robots) service, BBC News online, and local online newspaper websites. The results reveal both some of the differences between human- and machine-written local news stories and how news consumers can respond to those differences. Artificial Intelligence and Journalism: A Systematic Literature Review Professor Agnes Gulyas, Canterbury Christ Church University and Gentian Gashi, Canterbury Christ Church University, UK News organisations have begun to adopt artificial intelligence (AI) into their newsrooms, to automate article production, distribution and fact-checking. Using search terms such as “Automated Journalism,” “Algorithm Journalism” and “Robot Journalism,” a systematic literature review was conducted, analysing a reduced sample of 142 journal articles. The review analysed the content of the publications in terms of definitional and theoretical approaches, methodological design, focus of news organisation and AI providers, ethical and legal considerations, as well as perceived impact of AI on journalism. Initial findings suggest that the number of journal articles published on the topic has increased significantly since 2019 and most papers present results of an empirical study, while theoretical contributions are limited. Most news organisations discussed in the papers are national or international outlets from developed countries. Research on AI providers and local news organisations appears to be scarce, which suggests less widespread use of AI in local media.

Uploaded 2021-07-13T10:00:44.000Z Aerials and Satellites Wakefield