How far can automation go, as robots continue to take over journalism? The question is canvassed in a new WAN-Ifra report, News automation: The rewards, risks and realities of 'machine journalism'.
Macromedia University professor Andreas Graefe says not much has changed, despite bold predictions five years ago about how automated journalism would develop - from claims that 90 per cent of news would be automated to Pulitzer prizes for automated content.
"Progress is steady but slow," he says.
Despite newsrooms warming up to the possibilities, a number of challenges still surround actual implementation and deployment. WAN-Ifra partnered with Helsinki University and the Finland's VTT Technical Research Centre for the report which is free to members.
It features five examples of how news automation has been implemented in newsrooms around the world - at 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.
-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.
Non-members can purchase the report by using this link.
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