Computer vision, natural language processing (NLP), semantics and speech-to-text abilities are converging to form a new class of powerful offerings for editors. Yet, many media professionals are uncertain of the disruption they will cause and are rightfully hesitant to place their faith in automation.
At the end of the day, really good storytelling is a form of art. How can a machine possibly replace that?
The Hollywood perception of AI that occupies many of us—one where human-like machines start to replace us—is the wrong way to view the future of the cybernetic newsroom. Instead, ask yourself: What do machines do really well, and what do humans do really well? AI brings speed, scale and efficiency. Humans bring ideation, original opinions and creative thinking.
The real question is, how can editors and machines work together?
At its core, content automation promises to give the editor more time to focus on storytelling and provides readers with benefits like more content and better personalization. So, how can publishers work hand in robotic hand with automation tools? Here are three ways to take advantage of content automation now.
1. Content extension
Today’s reader has an insatiable thirst for more content. Thanks to platforms like Instagram and Twitter, readers have grown accustomed to easy shortcuts and content references about a story of interest (think hashtags).
While they still appreciate the value of artfully crafted editorial masterpieces, once they’re hooked on a story, they want more. This moment is a great example of where editors can leverage content automation to enhance and extend the life of a story.
Through NLP, AI tools can now understand an article’s context and auto-generate relevant content enhancements. Think micro-stories around the same theme, or more information about the central figure of the piece. This type of structured authoring can extend beyond the written word as well. Audio stories can be derived to give readers easy on-the-go access to an article, or interesting video enhancements can be created to keep the reader engaged.
2. Personalized reader flows
Thanks in large part to Netflix, consumers have grown accustomed to an experience that’s completely curated and personalized to their viewing and consumption behaviors. Behind the scenes, Netflix leverages complex AI tools to personalize the viewer’s journey and create a much stickier content environment.
Similarly, publishers are looking for ways to develop micro-personalized journeys specific to each reader. Companies like Uberflip are accomplishing this with smart tags, filtering and first-party reader data. Ultimately, this investment from publishers will improve time spent on site and reader retention, which will directly translate into more page views, brand stickiness and increased revenue.
3. Trend analysis
Today, big publishing players are leveraging AI to scan what’s happening in the world and quickly identify trends. Reuters, for example, uses an AI Tool called Lynx Insight to data sift at scale and pull fresh topics and headlines.
Technologies like Lynx Insight are meant to mimic the typical process journalists go through to research and uncover new stories—but at the speed and scale only a machine can produce. Not only do these technologies help editors quickly jump on developing stories and fuel decisions, they give journalists more time to craft powerful and engaging stories for readers.
We are only just starting to understand the full scope of what AI can bring to journalism. There are immense opportunities for publishers to take advantage of AI and marry the power of speed and scale with ideation and context.
Even beyond editorial, there is a world of potential for publishers to create new revenue streams and unique offerings for advertisers. Content owners are sitting on a mountain of virtually untapped data related to context and reader engagement. Now is the time to think big, embrace the positive disruption AI is poised to bring to journalism and make room for robots in the newsroom.
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As VP of product, Gil Sommer leads Connatix’s product strategy. His innovative thinking is key in bringing cutting-edge functionality to the company’s full-stack video publishing platform. Before Connatix, he was a category manager for Fiverr, where he used customer insights and segmentation to guide product development.
