TL;DR
- News organizations are on their guard against deepfake AI-generated news stories but are also keen to adopt AI tools to save them time and money.
- AI could be used to generate more local stories, quickly analyze satellite imagery, or transcribe foreign-language content into English and back again.
- A panel of experts at NAB Show also point to the day — soon — when news will be personalized.
The time and resource-saving capabilities of AI for cash-poor news organizations should be welcomed as much as the technology’s potential to erode trust should be guarded against, say executives working in the field.
Scott Ehrlich, CIO at Sinclair, said AI was forcing his organization to reevaluate everything it was doing. “Whether it is traffic, or finance, or story publishing, or how we manage the archives, or how we extract value from our archives, we get the opportunity to reevaluate and ask if AI is this something that can help,” he said.
“I don’t think that we’ve yet found a corner of the organization that is not going to be impacted in some way, shape, or form. One of the big challenges is prioritizing all of the use cases that you can develop for generative AI across the entire enterprise.”
Christina Hartman, VP of News Standards and Editorial Operations for Scripps News, said AI tools could cut down on the daily non-newsgathering functions that their journalists have to do in order to free them up to actually gather news.
“Our mission is use tools and use cases that prioritized our journalists to be able to do as much news gathering as possible,” Hartman said.
“That’s led to a world in which AI helps our journalists format their broadcast scripts for digital, generate SEO friendly headline, format for social media and a number of other tasks that take away the drudgery of the post-news gathering process to allow our journalists to focus on what is most significant, which is the news gathering.”
One use case Scripps News is considering for AI is generating more local stories from city councils and school boards. AI could be used to transcribe an interview or a public meeting and then synthesize the most important parts.
One such product was previewed at NAB Show by Moments Lab (formerly Newsbridge). Its new MXT-1.5 indexing model automatically analyzes live streams and archives, generating descriptions of video content, “just like a human would.” This claims the company empowers your team to work 10x faster, focusing on creative tasks and generating more revenue from your ever-growing media library.
READ MORE: Newsbridge is Now Moments Lab – Here’s Why (Moments Lab)
“As newsrooms shrink, that is a problem very much worth solving,” Hartman said. “That is where I think generative AI poses really incredible opportunities to allow us to effectively be there, when we can’t be there.”
Mohamed Moawad, managing editor at Al Jazeera, had another pertinent use case for AI. He explained how the channel was using AI to enhance and analyze satellite imagery from Planet Earth of Gaza, in particular so it could inform its journalists on the ground where Israeli and other forces were.
“The imagery wasn’t high resolution so we relied on AI to [up-res] the imagery and secondly to, in a second, analyze it. How many tanks, how many Israeli soldiers, approximately, of course. It empowered the journalist and gave us the opportunity not only to take our reporting to another level, make it more in depth, more analytical, but also gave us the opportunity to have a safety measure in place.”
Scott Zabielski, chief content officer of AI startup Channel 1, highlighted the ability to translate news to a multitude of languages as a major advantage of the tech.
“We can pull stories directly from other countries translate them and bring them to the United States. Then we can bring translate them back out to the rest of the world. What we’re really focusing on with AI is the efficiencies of how to distribute that story, how to edit into a video package, how to publish to different countries.”
He pointed to a day when news will be personalized. “So when you’re watching a newscast, you can watch something that’s a 30 minute newscast, but instead of it being the same thing everybody in the country sees, it can be about your local area. It could have the sports scores from your favorite team, business news focused on your stocks. Exactly customized to you.”
Of course there are negatives with AI too. Channel 1, for example, pulls stories from sources that it trusts, and these are written and shot by journalists.
“We are very cognizant of the idea that there’s a trust issue with AI. How do you know if you can trust what you’re seeing in the news?” Zabielski said.
Moawad was concerned about accuracy: “Sometimes we rush to conclusions that AI offers us in terms of analyzing imagery from satellites, even drawing conclusions from data, but we have to be cautious about the accuracy, because it’s not 100 per cent accurate. And that’s a challenge because if there is a tape out there of a military leader and there are rumors online that it’s a deepfake, we have to talk about it publicly, we have to show people how we verify it. If we don’t talk about it some people will accuse us of accepting fake videos and airing them.”
To combat conspiracy theories and suspicion of news organizations, Hartman argued for “doubling down” on making human connections with the audience.
Other spoke of working with camera vendors to ingrain and track metadata from the moment video is captured to publication online to verify provenance.
Hartman was optimistic that the essential functions of news gathering won’t be radically altered by AI, even in a decade’s time.
“My perspective is that we will continue to use AI to reduce the amount of drudgery that is non-news gathering related, but I think the core fundamental work of building sources, getting those sources to share things with you, and then vetting what you’ve been told and reporting that out at its core isn’t going to change.”
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