Report on journalism and GenAI features important use cases, biggest challenges

By Sonali Verma


Toronto, Ontario, Canada


The recent Trusted Journalism in the Age of Generative AI report by the European Broadcasting Union shows GenAI offers “an abundance of tools and opportunities to support news organisations.”

In a recent blog, I looked at what the report predicts GenAI will — and will not — change about journalism. Today, lets take a closer look at the use cases in the report.

“For example, targeting and serving different audiences with specific products and content will likely contribute to them feeling acknowledged in their needs and interests. This could build trust and increase news consumption.

“Additionally, the increasing availability of data generates opportunities to serve local audiences better with hyper-local content, including specific weather reports, real estate listings, traffic reports and the like… . For example, to serve people in different communities better and around the clock, the BBC and German Rundfunk Berlin-Brandenburg have used synthetic voices for automated traffic and weather updates.”

The BBC offers the weather forecast specific to a listener’s postal code, which “proves that text data provided by meteorologists can be converted into a rich audio weather forecast.” RBB offers app users weather and traffic updates every 15 minutes. 

AI can also make the news easier to access and understand, for example, through automated translation, text-to-speech, or speech-to-text tools, or visualising written content — making it particularly important for people with different native languages or audiences with impaired hearing or vision. 

The BBC offers a Tell Me More box that provides more contextual information within articles.

Screenshot of the Tell Me More tool from the BBC Labs Web site.
Screenshot of the Tell Me More tool from the BBC Labs Web site.

“Our prototype automatically identifies topics within an article that might require an explanation and then uses GPT-3 and pre-published BBC News content to automatically generate suggested explainable copy for those topics,” the BBC said.

The team at Brazilian news brand Agência Pública uses cloned voices reading long-form investigative stories to extend their reach, the EBU report said. 

They “had experimented with the technology when preparing an investigation into a corrupt politician who was abusing his power to push people off their land. They sent an audio version of the article, created with machine reading technology, to one of the affected farmers they had interviewed to help him respond to the investigation. This proved to be a hit — it was listened to by the farmer and others in his local community and shared with others affected by the story.” 

Screenshot from Agencia Publica’s Web site showing a podcast headline.
Screenshot from Agencia Publica’s Web site showing a podcast headline.

Finland’s national public media company Yle wanted to facilitate the integration of 62,500 Ukrainian refugees into Finnish society by providing a news service in their native language. It could launch this within two weeks, using machine-based translation, which is then checked by a journalist.

Screenshot of Yle’s Ukrainian news Web site.
Screenshot of Yle’s Ukrainian news Web site.

What was also interesting is what several news leaders flagged as the biggest challenge in managing AI: dealing with humans.

“(AI) is a massive topic with a lot going on all at once. People get information about developments from different sources. It’s very difficult trying to keep everyone on the same level of understanding with similar amounts of knowledge,” said Manuela Kasper Claridge, editor-in-chief at Deutsche Welle, which has more than 3,000 employees.

Jane Barrett, global editor/media news strategy at Thomson Reuters, also flagged communication as critical and said the biggest challenge she faced was prioritisation of projects: “What do we take from the experimental phase into production? Our newsroom has come up with so many great ideas. But it takes a lot of work to take something from a basic prompt, test it, integrate it into the workflow. Even more if you are fine-tuning a model or building more complex systems.”

That was echoed by Dutch broadcaster NPO’s Strategy and Innovation Director Ezra Eeman, who said his greatest challenge was “encouraging people to experiment but not put it out for production.”

For Kai Gniffke, chairman of Germany’s ARD consortium of nine public broadcasters, bureaucracy was a concern: “Getting the people who want to work with it to do so (is the biggest challenge). They shouldn’t have to wait for instructions by top management.”

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About Sonali Verma

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