Reddit AI, LA Times’ $50M Misstep, AP’s Image Verification Playbook, and more...
A Slightly Unusual Intro This Week…
Every now and then, a rare talent emerges—think ‘Top 30 Under 30’—someone who’s not just good at their role, but genuinely passionate about the industry. Jessie Shi is one of those people. She’s held roles at MarketWatch and the San Antonio Express-News, understands audience strategy at a core level, and has written for us, Poynter, and CJR. She’s also looking for her next role. If you're hiring—or even thinking about it—drop her a line. P.S. Her latest byline for Editor & Publisher is included in this week’s takes.
With more than 200M AI images generated each week, this week’s Long Read looks at how the Associated Press verifies the 3,000 images it distributes daily. TL;DR: AI tools alone won’t cut it—but AP’s framework shows how it can be done, and it has made its AP Verify tool available to other media organisations.
Let’s dive in…
Reddit AI: Transforming Its Own Community Threads into a Search Tool
Reddit’s user content is so valuable, Google paid $60 million to license it for AI training. Now, Reddit’s harnessing that same data in-house with “Reddit Answers”—an AI tool that pulls together advice from real users, notably the left-field, niche stuff it’s famous for. 1M Redditors use the tool each week, upgrading Reddit into a dynamic answer tool. r/AskReddit is simply AI at its very best...
WAN-IFRA World News Media Congress: Publishers Set AI Ground Rules
Announced earlier this week in Kraków, 3,000 media organisations have backed a new initiative from WAN-IFRA and the EBU calling for clearer AI standards. The five-point plan demands consent before using news content, fair value for quality journalism, and clear attribution. A laudable move—although the call for “open dialogue and cooperation” with Big Tech reads as naïve, lightly tossed word salad. You’re going to be played like a fiddle……{Exhibit A}
How Publishers Are Using Apps to Deepen Engagement and Improve Retention
Esther Kezia Thorpe says that apps are now one of the most effective tools in a publisher’s portfolio, forging deep audience engagement. It’s echoed by media analyst Simon Owens who writes, “Now we're in the post-scale era, where business models are more dependent on high quality engagement, I'm more sympathetic to the argument that publishers should invest in apps.”
Wall Street Journal’s ‘Taxbot’ Turns Readers Into Testers
WSJ has quietly built a chat product, Lars, the AI taxbot, to answer readers’ questions on filing U.S. taxes. It’s used a ‘Retrieval-Augmented Generation (RAG)’ model, built on WSJ content and publicly available information. Uniquely, it invites readers to challenge the bot, further refining the tool's accuracy and effectively turning them into co-developers of the tool.
$10K Per Journalist: Google Pays USD $16.5M to 108 Canadian Outlets
The first installment under Canada’s Online News Act (2023), recipients include national, local, digital, and Indigenous media. With echoes of Australia’s successful News Media Bargaining Code, U.S. News/Media Alliance CEO Danielle Coffey calls it a “significant victory” and a proof of concept for similar U.S. legislation now underway. P.S. Toronto’s Globe and Mail alone received $2,062,409.41.
KEEP YOUR EYE ON: OpenAI Is Building a Social Network
ChatGPT gained the accolade of the world’s most downloaded app in March and is set on launching a social network. Details are sparse but the “X-like social network” will probably be integrated into ChatGPT itself. Key quote: “One idea behind the OpenAI social prototype is to have AI help people share better content.” Get ready…
L.A. Times Lost $50M in 2024—And 25,000 Subscribers Walked
Mark Stenberg’s inside scoop on the drama at the LA Times reveals a loss of $50 million and the haemorrhaging of nearly 500 subscribers per week. The reasons are numerous, but the introduction of an AI-powered "bias meter” in January doesn’t seem to have helped. In fact it backfired badly…consider it an AI warning.
Judge Sets September as Date for Google Ad Break-Up
Mark your diary: The 20-year wait for Google’s ad tech slap will finally end in a US court on Sept 22. The terms are pleasing: the forced sale of Google’s ad server GAM, its ad network AdX, and the sharing of the data behind targeting, analytics, etc—not to mention the secrets of its ad auctions. One guarantee: Their lawyers will be working overtime to delay it further.
News and the Public Interest: Time to Rethink the Paywall
Jessie Shi argues that publishers must unlock public interest stories for the sake of democracy—and offers four practical ways to do it without gutting revenue. Packed with case studies and examples, it’s a call for newsrooms to rethink what really needs to be gated—not least for the sake of societal cohesion.
Here's Why You Should Say 'Thank You' to ChatGPT
ChatGPT spends $millions processing users saying "please" and "thank you"—but Sam Altman says it's worth it. He could be right: Research by Tom’s Guide has found that responses do improve when users are polite. When challenged by WNIP, ChatGPT answered: “I’ve been trained on enough human nuance to recognise that tone shapes outcomes.”
AI TOOL OF THE WEEK: Rephonic 3D Audience Graph
Rephonic’s 3D Audience Graph maps podcast relationships using algorithmic analysis of global listener data—it lets you see which shows share audiences, identify guest or sponsor opportunities, and, in short, plan smarter programming and scheduling. It’s more data-driven than AI per se, but as a ‘podcast intelligence’ tool, it’s damn effective. Free seven day trial…
WEBINAR: Beyond Clicks: Measuring What Really Matters in Journalism
Presented at last month’s International Journalism Festival in Perugia, Italy, Smartocto’s webinar tackles a key challenge: how to measure what actually drives value. In short, real audience engagement, trust, and—interestingly—societal impact. P.S. Smartocto is a leading European newsroom analytics company.
DATE FOR YOUR DIARY: Newsrewired
Final call for next week’s Newsrewired taking place at NewsUK’s headquarters in London, 13-14 May. Join 200 media execs, journalists, academics and industry experts to share the latest insights, trends & innovations in digital publishing. Detailed overview here. Organised by Marcella, Jacob, and the team behind Journalism.co.uk—they deserve your support.
LONG READ…What Publishers Can Learn From Associated Press’ AI Image Verification Strategy
The Associated Press (AP) news agency distributes 3,000 photos daily, which is more in one day than most publishers handle annually.
In a recent webinar, hosted by AP and supported by the Patrick J. McGovern Foundation, the AP outlined how it is adapting its editorial processes to deal with Gen AI images—a huge concern for the entire media industry.
30 Million AI-Generated Photos Per Day
The session, featuring AP UGC Editor Nadia Ahmed and Felipe Dana, News Manager for Field Innovation (and Pulitzer Prize winning photographer), highlighted that 30M Gen AI images are created each day. While most are not directly tied to news reporting, the sheer scale presents a clear risk if even one synthetic image inadvertently made its way into AP’s reporting workflows.
Indeed, for AP—which processes huge volumes of content—errors in verification can have wide-ranging, devastating impacts—therefore ensuring its standards aren’t breached is absolutely critical to its approach.
Tools Have Limits
Both speakers acknowledged the usefulness of AI detection tools but stressed that these tools alone are not enough. Detection models can miss AI-generated content or flag real images incorrectly. As a result, AP treats these tools as part of a broader process, but not a final decision-maker.
However, in the same vein, visual cues that once suggested an image might be synthetic—such as unusual anatomy or lighting—are now less reliable, especially as Gen AI models improve. It’s complex and tricky.
A clear example—pre-dating AI tools—is the 2003 case of Brian Walski, an LA Times photographer who combined two images from Iraq to enhance a photo. It ran on the front page before readers noticed duplicated figures. Walski was fired. (This example was not discussed in the webinar but serves as a reminder.)
The Role of Provenance
To address the challenges more directly, AP is using tools that focus on content authenticity. One example is C2PA (Coalition for Content Provenance and Authenticity), an open-source standard that allows metadata to be embedded in digital files. This metadata can include who created the image, where and when it was made, and what tools were used.
While C2PA doesn’t verify content as authentic or unaltered, it can help users trace its origin and understand its production. This transparency supports much more informed editorial decisions.
Human-Led Processes Remain Central
AP has developed a tool called AP Verify, which combines several verification features—reverse image search, object detection, geolocation, and more—into one platform. Automation speeds up parts of the process, but final verification always involves human review. AP has made this tool available to other media organisations.
Ahmed shared how her team approaches third-party content: requesting original files, checking metadata, speaking with the creator, and sometimes asking for screenshots from a mobile device’s camera roll. Even minor edits made with AI-based tools in common software can be hard to detect without access to the original file.
Verification is a process. It’s about gathering as many data points as possible and making a judgment based on a full picture.
Nadia Ahmed, UGC Editor, Associated Press
Takeaways for Publishers
Many of the practices outlined in the webinar can be applied across media organisations, regardless of size:
Use detection tools carefully: A helpful first step but should not be relied on without supporting checks.
Explore provenance standards: Tools like C2PA are still evolving, but adopting or aligning with them will become more important over time.
Request originals and ask detailed questions: Understanding who created the content, how, and under what circumstances remains a core verification step.
Keep a record of verification decisions: Documentation can support transparency internally and defend editorial choices externally.
Encourage team-based decision-making: AP uses collaborative review to increase rigour. Smaller teams can benefit from peer input, especially when content is ambiguous.
Apply standards consistently: All content—whether from staff, freelancers, or social platforms—should meet the same threshold for accuracy.
Looking Forward
Dana noted that even real content can mislead if presented out of context. That’s why context and provenance are just as important as detection.
While AP continues to test provenance technologies with camera manufacturers and platforms, these systems are still evolving. The key message to publishers: no single tool is enough. But combining clear processes, sound editorial judgment, and traceable content standards can help strengthen trust.
We want to be fast on decisions. But we also want to be sure. That’s why we’re re-evaluating even the sources we used to trust more.
Felipe Dana, News Manager for Field Innovation, Associated Press
Credibility doesn’t just depend on spotting fakes—it hinges on being able to explain what’s trustworthy, and why.
The entire webinar can be viewed by clicking on the image below:
