SAN BERNARDINO — As the fall term begins, journalism programs are confronting a defining question: how do you train reporters for a profession being reshaped, in real time, by artificial intelligence? In a recent interview on Newsroom Robots, the weekly show hosted by Nikita Roy that spotlights AI leaders in media, Stanford’s Djordje Padejski, Associate Director of the JSK Journalism Fellowships and a veteran investigative reporter and educator—outlined one path forward. Before bringing an AI-focused reporting course to Stanford last year, he piloted one of the country’s earliest versions at Arizona State University. His aim isn’t to turn students into coders but to graduate AI-literate journalists who can use new tools, interrogate their limits, and protect core newsroom standards.
Padejski’s classroom functions like a lab. When some instructors reacted to generative AI by banning it, he went the other way, asking students to use it transparently and then critique it. Every assignment includes a disclosure of how AI was used and a reflection on what the system got right or wrong and why. The emphasis falls less on a polished product and more on the reporting process, including source vetting, prompt design, fact-checking, error analysis, and accountability. With his support, the course syllabus accompanies this story as a resource for faculty and student editors who want to adapt the framework.
That process-first design also reshapes assessment. Instead of take-home essays that a model could easily generate, students work through live experiments and in-class critiques. They push AI on concrete newsroom tasks (summarizing court filings, scanning campaign-finance data) and then document hallucinations, bias patterns, and gaps in coverage. Semester projects extend the work onto specific beats such as surveillance, healthcare, and transportation, so students learn to ask beat-smart questions rather than generic ones.
For Padejski, every beat is now an AI beat. Whether you cover city hall, business, sports, or health, algorithms are already changing the systems you report on. That makes AI literacy a core requirement alongside open-records skills, data hygiene, and media law. Students don’t need to build models, but they do need a working grasp of how models are trained, where they fail, and how to audit outputs against verified sources. The goal is not to fear AI or to embrace it blindly, but to examine it the way you would any powerful source.
The implications for CSUSB’s student journalists are immediate. AI can churn out headlines and tidy summaries; it cannot exercise judgment, understand a campus audience, or hold local power to account. That remains our work. But used carefully, these tools can surface leads faster, parse long agendas before a public meeting, outline follow-up questions, and organize complicated background. The safeguards are familiar: independent verification, transparent sourcing, and accountability to readers.
Practically, that means adopting an AI-use disclosure line on stories and assignments so reporters state which tools were used, what prompts they relied on, and how they verified claims. It means keeping a “hallucination log,” where any AI-generated assertion must be checked against a human source or a primary document. It means building beat-specific checklists, for example, on the city hall beat, which budget PDFs to parse, which names to cross-check, which datasets to download, and which phrases models routinely mangle. And it means running a pre-publication audit: if an AI summary of your draft drops nuance or invents facts, tighten the copy and strengthen the sourcing before you file.
This conversation originally appeared on Newsroom Robots, hosted by Nikita Roy, which features weekly interviews and insights from AI experts at the forefront of the industry. Tools will keep changing; standards should not. If we teach student journalists to interrogate AI—using it as a learning instrument, grading the process that produces trustworthy work, and integrating model-aware thinking across every beat—we can graduate reporters who are fluent in tomorrow’s tools and anchored in journalism’s purpose: to seek truth, minimize harm, act independently, and remain accountable.