This article needs additional citations for verification. (June 2017) (Learn how and when to remove this template message)
In automated journalism, also known as algorithmic journalism or robot journalism, news articles are generated by computer programs. Through artificial intelligence (AI) software, stories are produced automatically by computers rather than human reporters. These programs interpret, organize, and present data in human-readable ways. Typically, the process involves an algorithm that scans large amounts of provided data, selects from an assortment of pre-programmed article structures, orders key points, and inserts details such as names, places, amounts, rankings, statistics, and other figures. The output can also be customized to fit a certain voice, tone, or style.
Data science and AI companies such as Automated Insights, Narrative Science, United Robots and Yseop develop and provide these algorithms to news outlets. As of 2016, only a few media organizations have used automated journalism. Early adopters include news providers such as the Associated Press, Forbes, ProPublica, and the Los Angeles Times.
Due to the formulaic nature of automation, it is mainly used for stories based on statistics and numerical figures. Common topics include sports recaps, weather, financial reports, real estate analysis, and earnings reviews. StatSheet, an online platform covering college basketball, runs entirely on an automated program. The Associated Press began using automation to cover 10,000 minor baseball leagues games annually, using a program from Automated Insights and statistics from MLB Advanced Media. Outside of sports, the Associated Press also uses automation to produce stories on corporate earnings. In 2006, Thomson Reuters announced their switch to automation to generate financial news stories on its online news platform. More famously, an algorithm called Quakebot published a story about a 2014 California earthquake on The Los Angeles Times website within three minutes after the shaking had stopped.
Automated journalism is sometimes seen as an opportunity to free journalists from routine reporting, providing them with more time for complex tasks. It also allows efficiency and cost-cutting, alleviating some financial burden that many news organizations face. However, automated journalism is also perceived as a threat to the authorship and quality of news and the precarity of employment within the industry.
Robot reporters are built to produce large quantities of information at quicker speeds. The Associated Press announced that their use of automation has increased the volume of earnings reports from customers by more than ten times. With software from Automated Insights and data from other companies, they can produce 150 to 300-word articles in the same time it takes journalists to crunch numbers and prepare information. By automating routine stories and tasks, journalists are promised more time for complex jobs such as investigative reporting and in-depth analysis of events.
Automated journalism is cheaper because more content can be produced within less time. It also lowers labour costs for news organizations. Reduced human input means less expenses on wages or salaries, paid leaves, vacations, and employment insurance. Automation serves as a cost-cutting tool for news outlets struggling with tight budgets but still wish to maintain the scope and quality of their coverage.
In an automated story, there is often confusion about who should be credited as the author. Several participants of a study on algorithmic authorship attributed the credit to the programmer; others perceived the news organization as the author, emphasizing the collaborative nature of the work. There is also no way for the reader to verify whether an article was written by a robot or human, which raises issues of transparency although such issues also arise with respect to authorship attribution between human authors too.
Credibility and quality
Concerns about the perceived credibility of automated news is not any different from concerns about the perceived credibility of news in general. Critics doubt if algorithms are "fair and accurate, free from subjectivity, error, or attempted influence." Again, these issues about fairness, accuracy, subjectivity, error, and attempts at influence or propaganda has also been present in articles written by humans over thousands of years. It is also remarked (by sources who do not want to name themselves?) that machines do not replace human capabilities such as creativity, humour, and critical-thinking. Substantial research in automated authoring has been pursued with some success at mimicking human humor and thinking abilities although a lot of improvement still needs to be done to existing techniques. At this point, computers alone lack the ability to write stories with perspective, emotion, thorough analysis, and surprising observations. Beyond human evaluation, there are now numerous algorithmic methods to identify machine written articles although some articles may still contain errors that are obvious for a human to identify they can at times score better with these automatic identifiers than human-written articles.
Among the concerns about automation is the loss of employment for journalists not dissimilar to the loss of jobs of hand-scribes before the invention of the printing press or those of telephone operators who connected "trunks" to enable long-distance calling. In the interest of saving costs, as mentioned previously, news organizations are inclined to cut staff when switching to cheaper, faster machines. In 2014, an annual census from The American Society of News Editors announced that the newspaper industry lost 3,800 full-time, professional editors. Falling by more than 10% within a year, this is the biggest drop since the industry cut over 10,000 jobs in 2007 and 2008.
Benefits and issues
The future of automated journalism can be seen as beneficial by some, however, others would argue that it could be detrimental to the industry as it removes the sense of objectivity. However, this argument is ludicrous because journalists themselves, being human beings, are subjective. For example, the media regularly spreads news that their government wants them to spread, e.g., with respect to WMDs and the Iraq War. As stated above, in the benefits section, the costs and efficiency of robot journalism are present and proven, however, some people have opined that utilizing a system of automation may separate the audience from the article. There exists no evidence for such claims however. This can happen because a human journalist writing on world issues may have their own personal writing style attached to the story, whereas, an article written using automation would result in the story being bland, and not having a personality although people who have made such comments have failed to provide evidence for such claims and largely lacked an understanding of the inner workings of the algorithmic processes. They said, again without giving evidence, that all automated articles were written within this firm would have a style that is similar to each other and the sense of a journalist would be lost in this process. In reality, it is very easy to make an algorithm have variations in style. Largely, algorithms mimic styles of existing writers or genres and have models for the differences between different authors. Just as an algorithm can paint in the style of Van Gogh or the early Chinese style, it can generate different articles using different styles. For example, an article about legislative news can be made cut and dry and matter-of-fact whereas an article about a fashion show can be infused with some colorful descriptions and comments.
The question regarding this issue is: what if these problems are claimed to only exist with current technologies without providing evidence? In the 2020s, the industry may change and new technological advancements may have been made, which can implement and fix some of the issues currently associated with the thought of using robot journalism. However, we need a lot of education in the area to get to a point where human beings do not make random claims about automated journalism without understanding what it really is and what it does without evidence as is usual in any of the scientific endeavors.
A Nieman Reports article, identifies whether or not machines will replace journalists and addresses many concerns around the concept of automated journalism practices. They discuss some of the benefits surrounding the concepts of automated journalism and how it can be beneficial to the industry, however, ultimately they support the idea that human journalists will stay around no matter how much technology changes. Their rationale is supported with the thought that the benefits of automation will never outweigh the perks of having a skilled journalist who is up to date with current technological advancements. Human attempts at foreseeing the future and foretelling it has been fraught with spectacular failures. It will be interesting to see how this prediction ages in the near future. Nevertheless, due to the journalism industry's reliance on technology, the industry itself must stay dynamic and shift with current trends. The professionals who work within this field must do the same as this field and can be competitive and over saturated due to the internet. As the internet has caused many shifts in the way this industry operates, it also opened the avenue for a citizen journalist to participate in the media much more frequently than before. Due to many people owning smartphones, with access to online databases and media sites, many people have taken on roles of amateur journalists. Overall this has benefited the industry from an efficiency perspective, however, it can be seen as hurting the professionals who work in the journalism field by some who want to see it as such especially if we do not carefully study the real effects and just go with perceptions and opinions. It is the hope that instead of conjectures and wild guesses there will be research in the field that will carefully examine these issues and make measured and accurate claims.
List of implementations
- In May 2020, Microsoft announced that a number of its MSN contract journalists would be replaced by robot journalism.
- Narrative Science - focuses on natural language generation for enterprise
- Monok - Autogenerated news articles using Neural Networks for NLG
- BBC - Streamlining media workflows (news aggregation and content extraction)
- Graefe, Andreas (January 7, 2016). Guide to Automated Journalism. New York City: Columbia Journalism Review. Retrieved February 14, 2018.
- Dörr, Konstantin Nicholas (2016-08-17). "Mapping the field of Algorithmic Journalism" (PDF). Digital Journalism. 4 (6): 700–722. doi:10.1080/21670811.2015.1096748. ISSN 2167-0811.
- Montal, Tal; Reich, Zvi (2016-08-05). "I, Robot. You, Journalist. Who is the Author?". Digital Journalism. 0 (7): 829–849. doi:10.1080/21670811.2016.1209083. ISSN 2167-0811.
- Cohen, Nicole S. (2015-04-03). "From Pink Slips to Pink Slime: Transforming Media Labor in a Digital Age". The Communication Review. 18 (2): 98–122. doi:10.1080/10714421.2015.1031996. ISSN 1071-4421.
- Carlson, Matt (2015-05-04). "The Robotic Reporter". Digital Journalism. 3 (3): 416–431. doi:10.1080/21670811.2014.976412. ISSN 2167-0811.
- Southern, Lucinda (2019-02-12). "Robot writers drove 1,000 paying subscribers for Swedish publisher MittMedia". Digiday. Retrieved 2019-02-19.
- Mullin, Benjamin (June 30, 2016). "The Associated Press will use automated writing to cover the minor leagues". The Poynter Institute. Retrieved April 19, 2017.
- Dalen, Arjen van (2012-10-01). "The Algorithms Behind the Headlines". Journalism Practice. 6 (5–6): 648–658. doi:10.1080/17512786.2012.667268. ISSN 1751-2786.
- "The Associated Press Uses AI To Boost Content And Video Volume | AdExchanger". AdExchanger. 2018-02-20. Retrieved 2018-04-05.
- "The Washington Post's robot reporter has published 850 articles in the past year". Digiday. 2017-09-14. Retrieved 2018-04-05.
- Dörr, Konstantin Nicholas; Hollnbuchner, Katharina (2017-04-21). "Ethical Challenges of Algorithmic Journalism". Digital Journalism. 5 (4): 404–419. doi:10.1080/21670811.2016.1167612. ISSN 2167-0811.
- Gillespie, Tarleton (2014-02-28), "The Relevance of Algorithms", Media Technologies, The MIT Press, pp. 167–194, doi:10.7551/mitpress/9780262525374.003.0009, ISBN 978-0-262-52537-4
- Gehrmann, Sebastian (2019), GLTR: Statistical Detection and Visualization of Generated Text, arXiv:1906.04043, Bibcode:2019arXiv190604043G
- Belz, Anya (2019), Fully Automatic Journalism: We Need to Talk About Nonfake News Generation (PDF), University of Brighton, retrieved 2020-02-01
- Caswell, David; Dörr, Konstantin (2017-05-09). "Automated Journalism 2.0: Event-driven narratives" (PDF). Journalism Practice. 0 (4): 477–496. doi:10.1080/17512786.2017.1320773. ISSN 1751-2786.
- Edmonds, Rick (July 28, 2015). "Newspaper industry lost 3,800 full-time editorial professionals in 2014". The Poynter Institute. Retrieved April 20, 2017.
- Thurman, Neil; Dörr, Konstantin; Kunert, Jessica (2017-03-01). "When Reporters Get Hands-on with Robo-Writing" (PDF). Digital Journalism. 0 (10): 1240–1259. doi:10.1080/21670811.2017.1289819. ISSN 2167-0811.
- "Will Machines Replace Journalists?". niemanreports.org. Retrieved 2017-04-21.
- "Microsoft sacks journalists to replace them with robots". the Guardian. 30 May 2020.
- "Microsoft 'to replace journalists with robots'". BBC News. 30 May 2020. Retrieved 31 May 2020.
- "Microsoft is cutting dozens of MSN news production workers and replacing them with artificial intelligence". The Seattle Times. 29 May 2020.