I’m going out on a limb here to say I think we’re entering a new golden age for local journalism.
Crazy, right? You’ve read repeated stories about the death of local journalism. The digital age crushed the advertising model, shrank newsrooms significantly and left wide swaths of the nation without any local coverage.
All true. Yet, as has happened regularly in the history of our species, momentous change can come just when things look the worst, and I believe that is happening now.
Over the last eight months, our newsroom has significantly improved the quality of our content, increased the number of substantive stories we publish and expanded into new topic areas.
We did it by embracing artificial intelligence as a tool to make us better.
I’ve written about AI in the newsroom repeatedly this year, and each time I do, I feel like we’ve taken a quantum leap forward since the last time. We’re using it to write better, report more thoroughly and create new forms of content that readers clearly love.
I note that I offer my optimistic view after more than a decade of having to accept that local journalism – our journalism – had sacrificed some cherished elements in the name of survival.
Before the internet turned journalism upside down, we had entire desks of editors whose job was to look for and fix mistakes in our content. Typos. Grammar errors. Gaping holes.
As budgets fell, we had to give up the backstops. As we worked to find a path to sustainable journalism in a digital age, we dedicated as ourselves to producing as much content as we could. The result was a lot of stories that people wanted to read, but errors spread rapidly.
Accepting the increase in errors went down hard. Every time I saw a typo or grammar error, or the misuse of words like comprise, I had to bite my tongue. More stories, not nitpicking, was the path forward.
In the last 8 months, everything changed. With colleagues at Advance Local, we built Editors Eyes, giving every reporter a personal copy desk to catch typos and grammar errors before publication. Every story you read here goes through it.
But AI is doing so much more for our writing. Everything I write – including this column – goes into AI, which I ask to identify any issues with structure. I ask it to find holes or anything that might be confusing. I don’t always agree with what it says, but I often do. It makes my writing clearer. Many of our reporters are doing the same.
Because of AI, the writing on cleveland.com and in The Plain Dealer is the best it has been in years.
That’s just the mechanical side. The real AI boon for our readers is the expanded content.
For the first time in years, we have reporters dedicated to covering Lorain, Lake and Geauga counties. We are using AI tools to be our eyes and ears, to help us identify potential stories, which the reporters then explore and write. Consider Hannah Drown’s story on a Lorain County commissioner wanting to shame child support scofflaws on billboards. She learned of it using our AI tools, then reported it out and wrote it.
This is not about robots doing our work. Hannah does the work. Many of her stories have no connection to AI. They’re the result of a dogged reporter keeping her eyes and ears open to find good subjects. We’ve set up AI tools, however, to make sure she sees what is going on.
AI also turns our podcasts into stories. We feed the audio into our custom tool, add prompts, and produce drafts 45–50 extra pieces a week, which we then edit – often heavily – before publishing. We started in March, and as you read this, we’ll be hitting the 5 millionth time one of them gets read. Readers love these stories.
The latest AI expansion of our content harkens to a standard newsroom practice when I became a reporter: almost daily reporter-editor conversations on how to follow up just-published stories, to advance them with new angles.
Those conversations were a good exercise, forcing us to step back and consider unanswered questions and think beyond the news. We had a lot more reporters then, so if I spent a day following up one of my stories, another reporter was there to pick up whatever news was breaking. Tightening budgets over the years left us with fewer reporters, and those enterprising follow-up stories dwindled.
Suddenly, we’re having those conversations again in our newsroom because of AI, and our readers are getting a boatload of new perspectives.
With any staff-written news or entertainment story we publish, reporters and editors talk about angles that might advance them. Maybe it’s using some stories in our archives to add historical context or discuss a trend. Maybe we use government statistics to put the original stories into a broader perspective. Maybe it’s simply a different angle that was underplayed in the original story.
Reporters feed their original stories into an AI chatbot along with the new material and write a prompt that gets them drafts of follow-ups, written through the prism of the new angles. Reporters clean up the drafts of any confusion and off-topic information, verify the accuracy and publish. And just to be clear, nothing AI produces goes straight to readers — reporters check every fact, remove errors or tangents, and ensure the final story meets our standards.
It’s just like we did in the old days, but much faster – minutes instead of hours or days.
We started publishing the follow-up stories about a month ago, and many of them have been rich. Some have been read by more people more than the stories they follow up on.
Consider a few examples.
Adam Ferrise reported on a woman jailed for filming in federal court, then used AI to draft a follow-up about efforts to end the courtroom photography ban, building on his reporting and new statements from advocates.
Lucas Daprile’s story on Trump sending the Guard to Washington became a broader comparison of crime in Ohio’s big cities after he fed his piece and statewide statistics into AI for new angles.
Ryan Cohick wrote about an 11-day August dry spell, then used AI with CDC, EPA and state data to turn it into a story on how the rain’s return would unleash a mosquito surge.
Sabrina Eaton broke the news of a proposed highway from Michigan’s U.P. to Myrtle Beach, then used AI prompts to spin a follow-up focused on the steep financial challenges behind the plan.
We have plenty of others. You might argue that the information in the follow-up pieces could have been included in the original news pieces, but we work fast on breaking news. We include needed context, but we can almost always find ways to go deeper later.
While we did do deeper dives on some stories over the last decade, we’re now doing them every day.
AI is not replacing journalists — it’s empowering them. With clearer writing, fewer mistakes, and more stories than ever, we are proving every day that local journalism’s best days aren’t behind us. They’re just beginning.
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