News organizations have lost the power to define what is and isn’t news. Instead, social media channels and aggregators have called the shots, capitalizing on algorithms that directly impact the content that users see, as well as the type of content that gets created.
Marketing and advertising have been capitalizing on AI innovations for years, to the detriment of reliable news.
By contrast, few media outlets have harnessed the burgeoning technology successfully. Yet, AI offers a ton of promise for the media industry.
What stands in the way of AI adoption on a mass scale? Here’s a look at some of the challenges and emerging trends within the space.
Where are we at with AI and the news?
China rolled out their artificial intelligence news anchor a few months back. The Washington Post has been using their robot reporter for a couple years at this point. Other news organizations are using AI to help journalists analyze datasets that inform their reporting.
Then there’s the question of whether AI can write articles. The answer is, they can. However, writing is best done by a human, as it requires art, creativity, and empathy. Otherwise, you get something like this.
I forced a bot to watch over 1,000 hours of Hallmark Christmas movies and then asked it to write a Hallmark Christmas movie of its own. Here is the first page. pic.twitter.com/HMEtkzHVCi
— Keaton Patti (@KeatonPatti) December 12, 2018
The best application is using robots as a resource for finding plagiarized content and errors and analyzing statistics. Or, perhaps, running a media bias fact check.
These elements come together for more accurate reporting — and let writers cover more ground in less time.
We’ve found that there actually are a lot of places where the media is taking advantage of the new technology. The problem is, like the artificial intelligence news anchor and the reporter bot, the news media has been using AI in these novelty applications.
Unfortunately, they haven’t been able to use it in the same ways that advertisers have — and are struggling to monetize.
Why is that?
One thing slowing down mass AI adoption — at least on the distribution side is the business model. TV news is funded by advertising shown during commercial breaks.
Companies that use AI for advertising or content distribution make money by selling products or through ad revenue. So, content that’s interesting gets top billing over balanced, unbiased reporting on unsexy topics like local news coverage or regulatory issues.
Some online news organizations now make money through digital subscriptions. Which, of course, is an alternative to the aggregator model which depends on behavioral targeting, clickbait, and promoting video content over the written word (customers see more ads, so more money).
News by virtual assistant
Smart speakers like Alexa, Google Home, and Cortana are giving people an easy way to get their daily updates from news organizations.
As such, several media outlets are beginning to experiment with how these digital assistants can help them deliver the news more effectively. According to Trushar Barot, of Harvard’s Nieman Lab, newsrooms predict that AI-driven interfaces could have a greater impact on how we consume information than the iPhone.
That same article then mentions that these organizations say, “they’re not technology companies.” Yet, automatically generated voice content is the next great threat to journalism.
That said, not every news organization is sitting around ignoring innovation. NPR has been working on voice AI. NPR product manager Ha-Hoa Hamano says the broadcaster’s hourly newscast is a gateway to the rest of NPR’s content, allowing them to reach the 32% of 18-34 year-olds who don’t have a radio.
Lack of industry standards for AI practices
The media have been reporting on AI since day one. Yet, using the black box algorithms responsible for promoting fake news hasn’t been part of the strategy. Responsible journalists can comment on these changes and continue to publish articles — and they should. But, it’s going to be hard to enact change if things keep going as is.
While newsrooms understand content and the process of creating quality content in a short amount of time, the next step is joining forces with sophisticated tech teams to reach a larger audience.