The World Association of Newspapers and News Publishers (WAN-IFRA) partnered with the University of Helsinki and the VTT Technical Research Centre of Finland to produce this latest report called News automation: The rewards, risks and realities of ‘machine journalism.

News media companies face ever-growing commercial pressure to extract higher margins from dwindling resources and that is a key driver for news automation, powered by machine learning and AI. The report focuses on a specific part of news automation: the automated generation of news texts based on structured data.

The report features five examples of how news automation has been implemented in newsrooms around the world: MittMedia and United Robots (Sweden), RADAR (UK), The Washington Post (US), Valtteri (Finland), and Xinhua and Caixin (China).

While these cases and others around the world demonstrate some of the possibilities for publishers to exploit news automation, researchers have found that there is still much development to be done – also from the publishers side, i.e. to continue to experiment.

“Five years ago, there were many bold predictions about how automated journalism will develop,” says Andreas Graefe, Endowed Sky Research Professor at Macromedia University, in the report. “From claims that 90% of news will be automated to Pulitzer prizes for automated content. In reality, not much has changed. Progress is steady but slow.” 

Here are a few takeaways from the report, which can be downloaded by WAN-IFRA members.

• Right now, one of the main goals of automated content is to save journalistic effort, especially on repetitive tasks, while increasing output.
• The good news is that so far, news automation has not replaced humans, and looks set to work alongside humans in the newsroom.
• News automation provides media companies with an opportunity to expand their businesses outside traditional news.
• The future of automation lies in decomposition, or deconstruction, of the fundamental principles of journalism. That means breaking down journalistic work into the actual information artefacts and micro processes to analyse what can be automated and what are inherently human tasks.
• Publishers considering implementing news automation systems have a lot of judgement calls to make. The biggest decision is whether the system should be bought from a service provider or created and modified in-house.
• Automated journalism transforms structured data into news articles, and the quality of the output is highly dependent on the quality of the data that is fed into it.
• Automatically generated texts beyond the most basic templating systems are often still prone to error. NLG systems are still quite unsophisticated and their extendability outside texts on sports, real estate or finance is limited by several factors.

For more information on WAN-IFRA research and reports, visit: www.wan-ifra.org/reports.