Editor’s Note: This post originally appeared in the Answering AI editorial section of our newsletter. Subscribe to the newsletter to get exclusive insights and resources twice weekly (usually Tuesday/Thursday), as well as select promotions.
This is one I think about, a lot.
My dad worked for The Cleveland Plain Dealer when I was growing up. I remember as a kid waking up with him in the early morning hours to deliver papers. And, every once in awhile, getting to walk through the old printing press downtown when it was churning out the next day’s publication. The smell of the ink, and the sounds of press, are etched in my mind.
Back then The Plain Dealer had 300+ reporters. Through years of attrition due to the rapidly evolving financial and advertising landscapes, the paper is now down to a few dozen.
Years later, I went to college to become a doctor. After one quarter of my freshmen year it became very obvious that wasn’t the right path for me. So, I turned to the one thing I knew I loved to do, write. I found my way into the E.W. Scripps School of Journalism at Ohio University.
While I didn’t go into traditional journalism out of school, I immediately put the skills I’d learned to work creating content for brands, before my friend Joe Pulizzi gave our industry the term content marketing.
After five years at another marketing agency, I started my own, PR 20/20, in 2005. For nearly 15 years we’ve hired journalism school graduates and helped grow businesses through brand storytelling.
Along the way I’ve watched journalism, as an industry and profession, decline. Not because it isn’t needed—it’s needed more than ever—but because the business model that sustained it couldn’t adapt fast enough.
Now, the industry faces a new challenge, the intelligent automation of writing. And it’s not coming, it’s here.
Major media companies, including The Washington Post, The Associated Press, BBC, The New York Times and The Wall Street Journal are using Natural Language Generation (NLG) technology to write earnings reports, sports stories and election results, and leveraging machine learning to enhance human writers through the discovery and analysis of data.
But, it’s not only available to massive media properties. Earlier this week, my agency introduced NLG-powered solutions to automate the writing of press releases and marketing performance reports.
So, to go back to the question of how AI will change writing, the technology exists for media outlets and brands to publish formulaic and data-driven content at scale once a HUMAN creates the templates to do it. That’s how we’re doing press releases, and how the media are using machines to write stories.
Is it AI? Not really. But, it is intelligent automation at a scale with which humans can’t compete. And that’s really all that matters.
But, the story is just starting. As we learned with the introduction of GPT-2 in February, machines are getting smarter, and true AI is being used to generate content with minimal human involvement.
We’re going to be talking, and writing, a lot more about the future of journalism and writing here, but, in the meantime, I highly recommend you read Will AI Save Journalism—or Kill It? over at Knowledge@Wharton.
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