After years of being seen as an emerging tactic, automated journalism has finally made it to the mainstream. We’re now witnessing a growing shift towards machines with high-level problem-solving capability. Each day, more robots and smart computers are in to give more and more impact on the news media industry.
From Facebook using artificial intelligence (Al) to detect the pattern of the words that indicate fake news to Trint using voice recognition to transcribe interviews in multiple languages in no time, journalists around the world embrace AI to speed-up the research and cross-referencing data and beyond.
Here are five points where you can see the impact of AI on journalism:
#1. Keeping an Eye on Fake News
Fake news has now become a part of our everyday life. Those fake articles or stories solely to mislead and misinform people into believing news that far from the truth. What’s more, that such news tends to go viral because people can spread lies faster than the actual fact itself.
Fact-checking sites such as FactCheck.org, MBFC, PolitiFact, and Snopes surely are doing an excellent job in verifying rumors, but after all, they have limited reach. That’s where AI comes in to fight against fake news by spotting misleading, fake online information.
The advanced technologies create a deep learning algorithm that determines whether a piece of news or document agrees, disagrees, or takes no stance on a specific claim. Therefore, it will distinguish seamlessly between previously unseen real or fake news in online articles.
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#2. Faster Information Gathering
In an era where people are bombarded with tons of information every day, it’s crucial to automate and centralize the information gathering process to share it faster than anyone else.
In that case, AI with the machine learning algorithm can seamlessly uncover data from various sources and summarize it before analyzing them into decent articles with useful information inside.
That’s why this AI’s impact comes handy, especially for journalistic organizations and newsrooms, as they can boost their fast-breaking news developments.
It allows journalists or reporters to define public domain resources and what kind of information is needed. That way, they can shorten their content creation process and time to distribute.
#3. Generate Reliable Outputs
Machine learning can put together reports and stories from raw data into intelligent stories. It helps news organizations to dig more in-depth on topics where the news is mostly numbers or statistics.
Since reporters or journalists don’t always have access to do an in-the-field report to specific events like stock markets, local sports, or local political elections, AI can be a handy tool to help cover things and generate outputs with its smart systems and data structure.
For instance, the Associated Press (AP) adopted article-generating software to cover at least 10,000 minor league baseball games across the nation for each season. It helps the organization to translate the data from box scores into stories and share the news right after the umpire’s final call.
Also, the automated writing systems can save reporters and journalists a lot of time by transcribing audio and video interviews into text in just no time.
#4. Automated Content Production
AI systems can also generate entire articles from both quantitative and qualitative data from scratch. Many news sites are using this system for speeding up their content production.
For example, The Washington Post has rolled Heliograf to generate high-quality articles with qualitative data as its resources. On the other hand, Bloomberg uses Cyborg to manage their content creation and management.
Not to mention that Forbes uses AI-enhanced content management called Bertie to help them with rough drafts and story templates to write.
Therefore, AI can automate content creation workflows that sometimes can be high-touch, time-consuming, and consequently expensive if done manually.
#5. Streamline Media Workflows
It’s now such a common knowledge that AI can take a massive, mundane workload of journalists and help them get their work done much faster, cheaper, and more efficiently.
That’s why from all those four points above, the impact of AI in journalism technically leads to one thing: it helps reporters, researchers, or journalists to focus on what they do best.
In this same vein, AI allows organizations or newsrooms to streamline their distributed processes from gathering information to news distribution. It can also relieve some of the common problems like inaccurate facts, information overload or underload, uncooperative sources, and more.
Wrapping Up: Is This The End of Human Journalism?
The use of AI has now become an essential part of the news media industry’s toolbox. The question is: is it going to kill human journal journalism at this point?
Well, radio didn’t spell the end for newspapers and TV hasn’t been killed off by Netflix. That’s to say, traditional human journalism is still alive and kicking despite AI’s power in journalism.
However, the newsroom should adopt artificial intelligence technologies sooner as the way news is produced and consumed is rapidly changing.
Andre Oentoro is the founder of Breadnbeyond, an award-winning explainer video company. He helps businesses increase conversion rates, close more sales, and get positive ROI from explainer videos (in that order).