Media Party New York @ Brown - 2026

I propose a lightning talk length case study of Bellingcat's work and our unique "audience engagement" strategy via an open-source investigative story about an oil spill in the Caribbean. This project started as a comment in our public Discord chatroom, and became a sprawling collaboration with multiple newsrooms across multiple continents. Along the way, it remained transparent and community-led. Our audience are more than passive consumers of our content. Through our public gathering spaces and volunteer programs, they can become co-creators of our research. By building this community, Bellingcat promotes ethical and responsible open source investigation skills, critical for media literacy and democratic participation in the misinformation age.

I will give quick take highlights on why this emerging field of creator priovders matters, who they are, their brackgrounds, business strategies, audience relationships, support structures and more. Data comes from long-form interviews with creators info providers in the U.S. and South Africa. The U.S. findings will be realeased April 13 with South Africa following soon after. 

Women on Wikipedia 

At Alley, we're working on an open-source audience toolkit for publishers. We observe that mid-sized and larger media organizations have fewer and worse options for payment acceptance, customer data and identity management, and authentication than do startup and indie publishers. We launched our tools on LAist.com, a major public radio digital platform in Southern California, and are soon to launch them with Chicago Public Media. I'll show our work, describe the project, and discuss the mandate to a new era of open source technology in the LLM era of news product development.

At NowThis, we don't have a big engineering team. So I built AI tools myself to solve the problems our newsroom actually has.
In 5 minutes, I'll walk through three internal tools I shipped:- A synthetic audience panel: AI-generated Gen Z personas that simulate focus group feedback on content before we publish, helping us catch tone and framing issues early.- An AI ad ops assistant: a Slack bot that manages paid campaigns across Meta and TikTok, pulls real-time analytics from API and data warehouse, and saves our team hours of manual reporting.- An AI pilot tool: lets our team generate AI-powered pre-pilots to visualize new show concepts before committing resources
I'll share what actually worked, what flopped, and the practical lessons for any lean media team thinking about building (not buying) AI tools. No massive budget required.

Small, mission-driven newsrooms face a persistent editorial bottleneck: too many pitches, too few editors, and a set of editorial values around representation, framing, and sourcing that resist easy automation. At Minority Africa, a Uganda based publication covering minorities on the continent, we wanted to know whether AI could help triage our now too many pitches without flattening the judgment behind it.
In 2025, we built Iraka, a custom GPT-based tool trained on a structured dataset of over 400 de-identified historical pitches paired with editorial decisions, reviewer comments, and outcome labels. The system prompt encodes Minority Africa's editorial criteria (including originality, representational depth, feasibility, and alignment with the publication's justice-oriented mission) and the tool returns a decision prediction (accept, develop, or reject), a score out of five, and written feedback designed to mirror the developmental tone of our editorial process.
In phase one, we benchmarked Iraka against real pitches it had not previously seen. It matched editorial decisions about 70% of the time, but feedback alignment was significantly lower at around 30%, showing that while decision replication is achievable, generating the kind of nuanced, contextual feedback editors actually give remains a major gap. We also tried to build it across different models with varied outcomes.
Phase two, now underway, targets the feedback layer directly. We are building synthetic and counterfactual pitch sets — controlled variations where elements like framing, sourcing, or representation are intentionally altered — to stress-test the tool on edge cases and ethical dilemmas absent from our historical data.
This talk shares what we built, what it got right, where it broke down, and the harder question underneath: what does it mean to encode editorial values into AI when those values center justice and representation?

The Global Index of Responsible AI measures how countries are honoring their international commitments on AI governance and responsible AI, especially those tied to UNESCO’s Recommendation on the Ethics of Artificial Intelligence. The project tracks 17 responsible AI topics, assessing whether countries have relevant laws, regulations, and real-world implementation, using a global network of 135 researchers—one in each country—who contribute data every two years. Beyond serving as a diagnostic tool for international organizations, the project also has strong value for journalists because it offers open, comparable data that helps contextualize public debates on AI, identify regulatory gaps, and bring a globally informed but locally grounded perspective led by a South African organization.

Stop chasing the latest viral distractions and consider the insights from three real-world case studies that demonstrate how building engaged audiences with journalistic impact can lead to long-term success. SembraMedia’s co-founder Janine Warner draws on research on more than 3,000 media organizations and news creators in the Project Oasis global media initiative to share a few innovative gems, and one cautionary tale.

What happens when you embed an AI engineer inside a newsroom and tell them to help wherever needed? At ProPublica, it led to “Spreadsheet Inference,” a method that combines the rigor of spreadsheet reporting with the scale of AI. This lightning talk will give a brief overview of how real investigations became product iterations, not the other way around. You'll see how the team turned iteration and empty into documentation, then code notebooks and eventually a fully featured Google Sheets plugin.