The holidays have come early for human journalists around the world.
A recent study from Ludwig Maximilian University of Munich found that “traditionally-crafted news articles are more comprehensible than articles produced with automation,” with AI’s word choice being a particular point of dissatisfaction for the readers surveyed.
“Readers complained that the AI-produced articles contained too many inappropriate, difficult, or unusual words and phrases,” says the report, originally published in the Journalism: Theory, Practice, and Criticism journal. “Furthermore, readers were significantly less satisfied with the way the automated articles handled numbers and data.”
In all, more than 3,000 U.K. news consumers were asked to rate one of 24 texts, half of which were written by journalists and the other half with the help of genAI automation and edited by journalists.
For both sides, LMU Munich professor and project-leader Neil Thurman has a suggestion for those humans producing and refining content.
“When creating and/or sub-editing automated news articles, journalists and technologists should aim to reduce the quantity of numbers, better explain words that readers are unlikely to understand, and increase the amount of language that helps readers picture what the story is about.”
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