Reporting on AI: a guide for journalists
Cover AI accurately: the right questions, sources, language and traps for reporters and editors
A taste of a lesson
A startup says its AI detects fraud with 95% accuracy. What do I ask?
Accuracy alone tells you little. If only 1% of transactions are fraud, a system that flags nothing is 99% accurate. Ask: accuracy on what data, collected how and when? What share of real fraud does it catch, and how many innocent customers does it flag for each true case? Who ran the evaluation, the company or an independent party? Is it deployed, and what happens when it is wrong? Exercise: rewrite their claim as a sentence you would actually publish, with attribution and caveats.
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Ask companies and researchers precise questions about AI capabilities and limits
- Test demos and read model announcements critically
- Write about AI with precise, non anthropomorphic language and honest uncertainty
- Build a diverse source list that includes affected people and independent experts
- Apply verification and disclosure standards to your newsroom's own AI use
Lesson plan
- 1 The technical floor for reporters Learn just enough about how models work to ask sharp questions. Start
- 2 Questions that cut through Prepare interview questions for companies and researchers. Start
- 3 Testing demos and reading announcements Verify capability claims hands on and through documentation. Start
- 4 Language and images Describe AI precisely and choose honest visuals. Start
- 5 Sources, balance and uncertainty Build balanced, well sourced AI stories. Start
- 6 AI in your own newsroom Apply editorial standards to AI assisted reporting. Start
Try asking
About this tutor
For reporters, editors, producers and student journalists covering AI on any beat. You build enough technical understanding to ask sharp questions, then focus on craft: interviewing companies and researchers, testing demos yourself, reading model announcements and safety reports, avoiding anthropomorphic language, choosing images, handling uncertainty, and finding independent experts and affected people. You practise on realistic press releases and pitches, and you develop a personal checklist for AI stories. You also consider ethics in your own newsroom's use of AI tools, such as disclosure and verification of AI assisted work.
Reviews
4.7
3 ratingsSample
- Olumide S.Sample
The 99% accurate by flagging nothing example is now my favourite question in interviews. Editing my draft lines on language was very helpful.
- Patrick D.Sample
Strong on questions and sourcing. The technical floor was a bit fast for me, but enough to follow interviews.
- Clémence R.Sample
Practical newsroom focus. The section on verifying AI transcripts led us to change our desk's workflow.
About the teacher
I teach people to judge AI claims, spot synthetic media and report on AI without the hype
9 tutors 435 lessons taught Sample
I teach media literacy for the age of AI. My learners include journalists, students, sceptics and anyone tired of breathless headlines in both directions. We practise reading claims about AI critically, checking images and video, understanding why AI text detectors fail, and asking the questions a careful reporter would ask. My background is in newsroom fact checking and training reporters,...
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