AI in Journalism

I tested how well some AI tools actually work for journalism. Here's what I found, published today in the Columbia Journalism Review. 🤖🗞️ 👉 https://lnkd.in/eU4DVJsa As a reporter, I’ve often asked myself: Can I actually trust AI tools to support real journalism work? For me, and for folks like Hugging Face’s Florent Daudens, The Washington Post's Jeremy B. Merrill, and Sahan Journal's Cynthia Tu—“vibe checks” aren’t enough. I teamed up with a group of amazing researchers to run structured tests on some of the most popular AI tools. We used real-world editorial tasks, summarizing government meetings and reviewing scientific research, to see how these tools actually perform. The results? Surprising, frustrating, and occasionally impressive. 📝 Summarizing Local Government Meetings This is bread-and-butter work for many local journalists. Here's what we found: For short summaries (~200 words), tools like ChatGPT-4o, Claude Opus 4, and Perplexity Pro did surprisingly well, often capturing more facts (and hallucinating less) than the human-written summary we used for benchmarking. For longer summaries (~500 words), the quality dropped fast. On average, the tools retained only about 50% of the facts, hallucinated more, and missed key details. ChatGPT-4o had the most consistent and accurate output, with the lowest hallucination rate and best user experience. So: AI can help with quick recaps—if humans are verifying the work. But for more in-depth reporting, it still needs a human doing the work. 🔬 AI & Scientific Research: Not There Yet We also tested newer AI tools designed to help journalists and researchers make sense of academic work, especially tools that promise to surface related studies or verify the importance of a finding. Most tools surfaced less than 6% of the citations included in expert human literature reviews. Across the board, results were incomplete, or just plain wrong. 100% do not recommend (yet). Huge thanks to the brilliant team behind this work: Sophia Juco, Sandy Berrocal, Nneka Chile, Julia Kieserman, Jiayue Fan, Emilia Ruzicka, Mona Sloane, and Michael Morisy 🙌 (and anyone I may have missed!). I’m especially grateful for funding and support from the The Patrick J. McGovern Foundation, Vilas Dhar, and Nick Cain, who are deeply committed to journalism’s future. Next steps: If you’re experimenting with AI in your reporting—or you’ve read the piece and have thoughts—I’d love to hear from you. Drop a comment 👇 or shoot me a message. I'm also looking to connect with others interested in developing AI benchmarking standards for journalism, to help folks test tools more easily and responsibly. Burt Herman, Paul Cheung, Aimee, Nikita Roy, Silvia DalBen Furtado, Nicholas Diakopoulos, Jeremy Gilbert, and many others, I see you! #AIinJournalism #MediaTech #Journalism #AI SABEW Investigative Reporters and Editors Global Investigative Journalism Network Online News Association MuckRock Foundation, Tech Policy Press

Everyone says journalism is dying.   I don’t think that diagnosis is correct. What we're actually noticing is a restructure.    We just published a study analyzing 179.5 million citation records across 6 LLM platforms (OpenAI, Gemini, Perplexity, Grok, Copilot, Google AI Mode).   The headline finding: 88.4% of press release distribution domains were cited by at least one LLM. Nearly 9 in 10 domains entered the citation basket - which FYI, AI uses to form its answers.   This reveals a paradox: LLMs are simultaneously starving newsrooms of traffic while making high-authority journalism more valuable than ever.   In the Google Search era, PR was about links. In the LLM era, it's about attribution (i.e. being cited as fact inside an AI response). And AI doesn't pull from anywhere. It pulls from sources it trusts.   Gemini was the most selective platform we studied. It cited fewer sources than the others. However, the sources it did choose ranked near the top of its responses and captured 32% of competitive attention. Quality over quantity. It rewards journalism that's actually credible.   So why does the "dying profession" narrative persist?   Because the business model is under real pressure. If users get a ChatGPT summary instead of clicking to the WSJ, the journalist doesn't get paid. The value is being consumed without being compensated.   But the need for journalism has never been higher.    AI can't generate trustworthy answers from thin air; it relies on real reporting. As low-quality AI content saturates the web, original journalism is becoming rarer, which makes it more valuable, not less.   Some of the strongest performers in our study weren't household names. thestreet.com and washingtoncitypaper.com outperformed larger outlets not because they published more, but because they publish with authority and consistency. That's what AI rewards.   Two groups need to pay attention here.   Journalists → your value isn't shrinking, it's shifting. Lean into verification and consistency and AI will cite you, not replace you.   PR & SEO teams → unique data and original insights are your most powerful asset now. LLMs cite proof.   Do you think journalism is dying or being redefined? Drop your thoughts below.   Full study here: https://lnkd.in/eJCJH4et

Very proud to share this important new report from #JournalismAI! "AI and the Newsroom Next Door: Experiments and Best Practices for Small Publishers" showcases how 35 news organizations worldwide are using AI to enhance their journalism, strengthen their operations, and expand their public mission. As advisor for the 2024 #JournalismAI Innovation Challenge, I had the privilege of following the journey of this truly impressive cohort of small and medium-sized publishers exploring AI's potential in journalism. Huge thanks to Charlie Beckett for inviting me to serve as advisor, to Tshepo Tshabalala (Project Manager and Team Leader), Lakshmi Sivadas (Senior Programme Manager), and the entire JournalismAI team who made this program possible. The report features: 🌐 35 AI innovation stories from across the globe 📝 Practical lessons for newsrooms starting their AI journey 🗺️ Insights on experimental collaboration driving change 💡 Guidance on AI implementation in journalism These publishers have shown remarkable creativity in experimenting with AI while staying true to their journalistic mission. Their experiences offer invaluable insights for our industry. 🔗 Read the full report: https://lnkd.in/epEiF44S #AI #MediaInnovation #Journalism #DigitalTransformation #FutureOfNews

Agentic AI journalism has arrived. According to the UK Press Gazette this morning, Mediahuis, one of Europe's largest news publishers with 25 titles across five countries, just revealed it's experimenting with a chain of AI journalism agents to produce routine "first-line" news. Not just one AI tool. A full agentic AI pipeline: commissioning, writing, legal checks, fact-checking, multimedia sourcing, and discourse monitoring - all handled by specialised AI agents before a human journalist reviews and publishes. The goal? Free their (currently) 2,000 human journalists to focus on "signature journalism" — investigations, interviews, community-connected depth reporting. What does this mean for PR and communications professionals? How long before: 1. Your press release may be triaged by AI first. Mediahuis is building curated source databases — wire agencies, parliaments, think tanks, political leaders on social. If your organisation isn't in those source pools in a structured, machine-readable way, you may not even make the first cut. Being findable by validated AI system sources may become as important as knowing the right journalist. 2. The two-tier newsroom needs a two-tier pitch strategy. Routine announcements will increasingly flow through AI-mediated workflows. But "signature journalism" — the pieces that build reputations and break stories — still requires human relationships. Know which tier your story belongs to, and invest your time accordingly. 3. AI monitoring is now part of the editorial cycle. Mediahuis's monitoring agent tracks public discourse around published stories. When polarisation spikes, it flags the topic for deeper editorial investigation. That means how audiences react to initial coverage can now algorithmically trigger follow-up journalism. The crisis response window just got shorter and more complicated (if that's possible). The multi-agent workflow Mediahuis describes - commissioning, producing, checking, monitoring - maps directly to how many PR teams operate. Is there an opportunity to apply similar thinking to comms content production: use AI for the routine, preserve human expertise for the strategic? Though fewer routine journalism roles will mean an even thinner pipeline of experienced reporters long-term. And if multiple publishers adopt similar AI systems drawing from the same source databases, do we risk even more homogenised news coverage? What happens when dealing with agentic AI journalism systems becomes the norm? What changes are you already seeing in how newsrooms handle incoming stories? As ever, welcome your comments below. Read the original Press Gazette article here: https://lnkd.in/eZ5_SgpS

A story I wrote for a client showed up in a Google summary 30 minutes after it hit the wire. First, the article was picked up by a local newsroom in a midsize American city. Then, within half an hour, it was indexed and quoted as an AI answer. AI is reading your local news, and it's easy to understand why. Before GPT or Claude can answer a question, these AI models make a thousand small decisions about who to trust. There are too many sources to cover, so they fall back on the same heuristic newspapers have used for two hundred years: trust the institutions that have to put their name on something, that have editors, that are accountable if they get it wrong. Local newspapers fit that description even when they're operating with a fraction of the staff they had a decade ago. Which means the humblest little daily paper in Wisconsin is a more authoritative source in the eyes of a frontier AI lab than a Fortune 500 brand's polished blog. This is an aspect of syndication that nobody factored in two years ago. It wasn't even a real consideration when I started doing this work. Now it's the thing I lead calls with. Brands whose content is sitting in a hundred local newsrooms today are going to be in a very different position than brands whose content is sitting on their own website, hoping to get crawled. Local news has gotten a value boost as far as real estate on the internet right now.

It started as a data project on school closures. It ended with uncovering a political proposal built on fake studies generated by ChatGPT. itromso.no, a 25-person newsroom in Norway, published 90 stories in six weeks, exposed how politicians used AI without oversight, and even gained new subscribers along the way. When I spoke with Lars Adrian Giske this week, he walked me through how his team combined good journalism with AI-native tools (like their RAG system, Djinn, and an AI-checker for “low information density” texts) to uncover the truth. But this story is also the story of a small media climbing the AI competence ladder, a journey Giske describes as: 1. Getting to learn what AI is 2. Integrating AI into daily workflows 3. Expanding into data-journalism, with AI tools extending the work  4. Developing in-house tools through an innovation pipeline 5. Commercialising the tools "Having the AI framework and prompting classes is great, but it won't get people to understand and implement AI, he said. You do that through hands-on projects, and it's been our strategy since 2019." The media now has more subscribers than it did 25 years ago, pre-Internet, pre-social media, pre-AI. To me, this case shows both the risks of untrained AI use in public policy and the opportunity for small newsrooms to lead with smart, practical AI adoption. (Also! Lars Adrian Giske will share more at the upcoming WAN-IFRA, the World Association of News Publishers AI Forum in Paris 🇲🇫 )