Newsroom AI Poses Opportunities, Challenges New survey identifies journalists' hopes and worries for Generative AI

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2 min read
Charts with results from a survey by the London School of Economics and Political Science

Journalists are approaching text generators with cautious optimism, a new study shows.

What’s new: Researchers at the London School of Economics and Political Science surveyed workers at over 100 news organizations worldwide. 85 percent of respondents said they had experimented with generative AI.

How it works: The authors asked journalists, technologists, and managers how their newsrooms were using generative AI and how they felt about the technology.

  • 75 percent of newsrooms surveyed used AI to gather news. 90 percent used AI to produce reports, and 80 percent used it to distribute them.
  • Respondents at 73 percent of newsrooms surveyed said generative AI presented new opportunities. Some argued that generative models were more democratic than other digital technologies, because using them did not require coding skills. 
  • 40 percent of respondents said generative AI presented new challenges, such as its potential to produce falsehoods. 82 percent were concerned that it would damage editorial quality, while 40 percent were concerned that it would degrade readers’ perceptions of the media.
  • Respondents outside Europe and North America noted that existing AI tools trained on data from those places failed to capture the cultural contexts of other regions. Others worried that independent newsrooms in poor regions did not have enough resources to deploy AI tools.

Behind the news: Publishers have been eager to take advantage of large language models, but the results so far have been mixed. 

  • CNET and Gizmodo published articles that were generated by AI but edited by humans. Readers pointed out factual errors and plagiarism.
  • In August, The Associated Press issued guidelines for news outlets that advised them to treat generated text with caution but avoid generated images, video, or audio.
  • Some efforts are widely regarded as successful. The Washington Post’s Heliograf has produced articles from structured data since 2016. The Times of London’s JAMES content management system uses machine learning to personalize the contents of its newsletters.

Why it matters: In a few short decades, journalism has suffered techno-shocks wrought by the web and social media. Generative AI is poised to bring a third wave of change and challenge, but journalists are generally confident that they can benefit from the technology.

We’re thinking: We recently distinguished between jobs and the tasks they comprise. While AI can perform some tasks at a human level, currently it rarely performs so well on all the tasks in a given job. We encourage publishers to adopt this framework and devise fruitful ways to allocate journalists’ tasks among human-only, machine-only, and human-plus-machine modes. 


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