Journalism in The Gen AI Era: The Help Newsrooms Get — And Want To Get — From AI

This year’s Pulitzer Prize winners will be announced next week. And while we hope to find out some details and use-specifics about the handful of finalists in the journalism category who utilized AI in their entries — either for the researching, reporting, or telling of their submissions, as they were required to disclose — the fact that newsrooms are already using the tool is a solid sign that the technology’s capabilities are a help worthy of the hype.

In its April report, “Generative AI in Journalism: The Evolution of Newswork and Ethics in a Generative Information Ecosystem,” AP’s Local News AI program surveyed 292 news professionals about their gen AI use, with nearly three-quarters (73.8%) saying they or their organization are using the technology in some capacity.

“The dominant category of use is unsurprisingly related to content production,” the report says. “This category included responses about using generative AI tools in processes of producing public-facing or newsroom internal content, including creating, editing, and transforming media formats.”

Textual content production by far led the current tasks for 69.6% of respondents, with subcategories of content production ranking 3rd (multimedia, for 21.5%), 5th (translation, for 8.8%), and 7th (transcription, for 7.2%). Other high-ranking usages included information gathering and sensemaking (21.5%), business (16.6%), data work (7.7%), and coding (5%).

(Source: AP’s Local News AI)

“In the text category, respondents state they have used generative AI for generating content such as news headlines, social media posts, newsletters, quizzes, text from data, taglines, and story drafts,” the report says. “They have also used generative AI for copy editing and summarizing articles, rewriting for a different medium (e.g. script production) or to reduce jargon or produce a press release, and fact checking. Respondents also mentioned using generative AI for generating multimedia content, such as illustrations (e.g. for social media posts), videos, audio (e.g. text to speech), or for editing images.”

Text production even led the list of aspirational uses, as 78.6% listed it as a task they’d like gen AI to do “if it were capable of producing quality results.” Other top tasks respondents would ideally like to do were information gathering and sensemaking (34.9%), business (27.5%), and multimedia content production (23.1%).

(Source: AP’s Local News AI)

“Respondents talk about saving time and enhancing efficiency, but also augmenting and supporting creativity with story discovery, idea generation or brainstorming, and mentioning specific activities where AI might offer some gains such as content production with headlines and illustrations, for research in gathering background content, data work for scraping and extraction from documents, and expanding audiences,” the report says.

In its findings breakdown, the report noted the usual ethical concerns that come along with the idea of journalists using generative AI, but also an “unmet opportunity to design new interfaces to support journalistic work with generative AI,” particularly wherein journalists act as editors and quality-control checkers for any gen AI output. 

“This might, for instance, include details to support replicability of an analysis, provenance for a number, fact, or source, or a general explanation that could be used to help assess an output,” the report says. “Perhaps what journalists need in order to effectively use generative AI are well-designed editing interfaces to support human oversight.”