Content Automation: Can AI Write Like Humans?


When the Avengers series spreads the idea that artificial intelligence (AI) is going to take over the world, you laugh at it like a piece of science fiction. When technophobes warn you that bots are cutting jobs, you dismiss it as an unnecessary fear-inducement. You insist that AI automates routine physical tasks with great efficiency and speed. However, when you come across “this article was written by a robot” at the end of a story, it makes you sit down and take note.

Welcome to the world of content automation! It is one of the latest AI applications that will turn the world upside down.

Content Automation – Using AI and NLP

AI technologies are improving and accelerating with applications covering all use cases.

For interactive communication, writers and journalists use natural language processing (NLP) because of its ability to decode language and texts. They were first used in chatbot conversations and read aloud from text-to-speech systems. However, NLP platforms are now able to perform contextual searches and reviews on the web. Plus, they can turn both into summary stories. On top of that, it helps journalists and writers produce more relevant and error-free content in seconds.

There are improvements in NLP technology and advanced NLP software. They help in transforming structured data into simple and long content. These are automated natural language generation (NLG) systems that decode data and store textual information from multiple sources in real time. In addition, they also transfer the information in a readable format. Like data cleansing, the NLG system eliminates ambiguous or erroneous user input and translates it into text format.

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What is Automatic Natural Language Processing (NLP)?

NLP understands human language. Additionally, Machine Learning (ML) repeatedly learns during the process of finding and curating content from various sources. Additionally, the system determines what content to include, how to structure the document, aggregate text, and merge similar sentences to improve readability. On top of that, it uses rhetorical word choice for the natural and follows the rules of syntax to write a grammatically correct article!

The benefits of deploying the NLP technique for article generation have prompted publishers to create their own writing bots. Also, they influence computer writing software for automated generation of news and articles.

So, with the digital disruption of content creation, we now have robot-generated news stories and articles that go beyond rewriting news articles into opinion pieces. From creating summary news articles to opinion pieces, AI writing software has revolutionized journalism with content automation like never before.

With advancements in algorithmic techniques, is it possible to perfect AI and NLP in a way that people think a real human wrote an article designed by a robot?

Well, even as we speak it is happening all over the world!

AI writing software disrupts content creation
Photo by Swapnil Singh on Medium

Current content automation tools

Bloomberg was one of the early adopters of automated content. They used their dedicated program, Cyborg, to produce articles in their financial section. Much like business reporting, the “robotic journalist” reads and analyzes financial reports to produce news articles. This is one of the best use cases for content automation. This is because it leaves no chance for human errors of interpretation. Consider a traditional newsroom setup when the reporter is late. While she is browsing through a lot of data, her editor has to wait for her draft.

Enter the robotic journalists. From instant curation of financial news from around the world and different timelines, to analyzing tons of reports in seconds and translating into appropriate content, AI can do it all for the journalist. What else? You can do a lot more content, without any margin for error, with a fraction of the resources and in real time. Happy times for the editor, always under pressure to provide “breaking news” and justify staff costs to the board.

Forbes also uses the IA Bertie publishing platform. It is an essential content management system (CMS) tool that recommends article topics to contributors and titles based on sentiment analysis of previous posts. The Washington Post’s adoption of the Heliograf robot created a trend in content automation in 2016. It produced 850 reports on the 2016 presidential elections. Drawing inspiration from the use of robotic process automation ( RPA) in algorithmic trading, Heliograf relies on AI to detect trends in finance. For real-time automated news alerts, they collect a huge amount of information filtered by news services and global markets.

AI and NLP usher in a wave of robotic journalism
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Other uses of AI and NLP in journalism

Along with AI-driven automated writing software and custom bots, APIs are also used to optimize workflows that take the burden off the reporter from mundane tasks. The BBC uses news content and aggregation API, The Juicer. The Washington Post uses the Knowledge Map in addition to its robot Heliograf, to correlate media sources. The New York Times is deploying the publisher’s app in its research and development lab to process data faster. Reuter news agency uses News Tracer to stay on top of the latest news, automating routine content research tasks. Another news agency, the Associated Press, began using AI as early as 2013 to extract data and report on sports and income. Today, he uses the NewsWhip to stay ahead of new trends on social media.

These are just a few examples of how media giants and news agencies are deploying AI for bionic content. While some tools improve journalism, others improve the quality of stories and make them more relevant through timely publication.

Can AI ever write as naturally as a real person?

Digital transformation has pervaded all industries and streamlined work processes. However, most people would not have imagined that this has already had an impact on journalism. While it’s cool to have a chatbot to answer your product questions, asking the AI ​​to decide what content you read with your morning cup of tea can be a mind-boggling experience.

AI applications in content automation are a whole different ball game. AI can extract the most relevant news while algorithms bring content together; Produce summaries, generate search-optimized catchy headlines, and also map great news with an opinion.

Does the rise of content automation mean the resumption of journalism jobs and newsrooms?

Much depends on the ability of the AI ​​author and the robot author to write as naturally as humans. Just like in healthcare, robots cannot completely simulate human touch. In addition, the robot reporter cannot ask follow-up questions on the fly during a face-to-face interview. Creativity and humor also cannot be replicated by a robotic journalist.

The critical thinking and analysis of AI authors has its limits. They use ML and historical data for prediction and opinion. However, they cannot take advantage of critical thinking when there is no past data or relevant information to work with. Bots cannot replace opinion pieces and editorials because every top author or editor has their take on the news that builds their brand value.

How will content automation impact journalism?

Technology has always changed the way we live and work. In content automation, AI is poised to revolutionize the way news is generated and created. From images to data and scenarios, automated content is designed to be more sophisticated, relevant and precise.

While AI algorithms cannot (yet) independently create stories, they can work with given keywords and information to enhance storytelling; edit titles, images and supporting data tables. Moreover, it can analyze huge chunks of information in a very short time.

Robots can play the role of assistants and researchers. They can gather the necessary information and help with optimized headlines. Routine tasks can be automated, leaving the reporter free for live reporting, investigative reporting and face-to-face interviews. Content automation is most important in the realm of data-driven stories, financial and sports news, where real-time news generation makes the difference in profit for a publisher.

Will content automation have an impact on how news is generated?
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Content Automation: Will It Ultimately Benefit Journalism?

What is content automation for? It provides journalists with error-free, validated, verified and valuable work. It helps the writer with mundane data mining, research and aggregation of early drafts. The use of technology has freed up about 20 percent of journalists’ time to cover financial news.

Automation is a highly opinionated editorial area that can create a dangerous trend. On the flip side, the judicious use of bots and custom APIs for specific tasks can be more of an augmentation than a destructive force. Publishers have to get used to the haphazard deployment of technology to automate tasks.

Content Automation: Empowerment or a Dangerous Trend Maker?
Photo by Damon Ragusa on Marketing Land

Final thoughts on automating AI content

The overall narrative revolves around AI bots cutting journalist jobs, which is a myth at best. Automation can’t be a job killer, but raises the bar even higher with highly specialized, real-time factual stories. AI has unlimited potential to support the content automation industry. It tells better news that adds momentum to a 24/7 connected ecosystem hungry for instant information.

Content automation


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