Adaptive surveys use AI to ask “one more thing” on purpose, balancing structure with responsiveness to context. This session explores how a small set of fixed questions, paired with AI-guided follow-ups in natural language, helps researchers probe real constraints while staying on script and avoiding generic or leading prompts. Drawing on early field tests, including a rapid-response study during the Iran–Israel conflict internet shutdown and a WhatsApp-based project with Latino migrants in Philadelphia using WhatsApp, speakers share lessons on making audience research more locally relevant, especially in hard-to-reach communities.
Patrick Boehler / Madison Karas
AI works best in journalism when treated as an adversarial co-pilot, not a summarization engine. This workshop introduces nine research and analysis workflows using NotebookLM to interrogate documents, surface blind spots, and stress-test assumptions. Participants learn how to use critique-driven techniques, reverse-argument analysis, and perspective shifts to probe policy papers and large document sets while staying grounded in sources and citations. Attendees leave with a practical playbook for turning dense material into deeper, more rigorous reporting.
Jeremy Caplan
AI is great at a lot of things, but math and number crunching are not its strong suits. The American City Business Journals wanted a tool to surface stories from public records, but kept running into the same problem: the LLMs would dream up what it thought was the right numbers, instead of actually doing the math. In this session, we'll explain how we paired a series of LLM inputs with behind-the-scenes JavaScript to transform hundreds of public records into a useful output for reporters and editors. This same logic flow has been applied to anything that requires a precise output: word counts, data analysis, and more.
Tyson Bird / Alex Mahadevan / Jessi Hollis McCarthy
Many newsrooms experiment with AI, but few turn those experiments into systems journalists trust and use. Teams struggle to align editors, engineers, and product leaders around priorities, guardrails, and clear ownership. This session shares practical lessons from what has worked and what has failed, focusing on how newsrooms earn buy-in and design AI systems built to last. The takeaway is simple: success comes from clear goals, shared standards, and strong product thinking, not from chasing better tools.
Ryan Struyk / Heather Ciras / Rubina Fillion / Ole Reissmann
Nikita Roy / Hilke Schellmann / Sonya Quick