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Artificial Intelligence And Modern Journalism: Will Media Houses Have To Fire More Humans?

Khurram Shahzad writes on why Artificial Intelligence (AI) is taking over newsrooms and how the big media houses are already using it to produce timely content at a cheaper cost without compromising on accuracy. But can AI replace human intelligence?

These days almost every journalism conference has at least one session on the role of Artificial Intelligence (AI) in modern journalism and, interestingly, it is always asked: “will AI replace journalists and writers?” Last week I had the opportunity to visit the technology center of America’s top news agency in Washington. They were using many tools and techniques to generate quick, accurate and foolproof content using Artificial Intelligence (AI). These tools had multiple layers of data-centric AI wrappers to ensure the filtration of Fake News. During my visit, I was able to produce a 550-word article, based on a press release, with a single click and amazingly this article had many relevant references from the past. It was hard to say that it was a machine written article.

As print media around the world is struggling with its presence, war on digital media to produce new, verified and quality content is getting into a new era – the era of AI. The BBC Juicer, News Tracer of Reuters, Lab-Editor of New York Times, Knowledge-Map of Washington Post and Quill platform of Narrative Science, they all are using top-notch AI-enabled tools to generate the best content without any human involvement.

While AI algorithms are complex, setting up patterns of data for future use is key for this process. In 2015, The New York Times implemented its experimental AI project known as Editor and objective was to help journalists in writing news and articles. The journalists were required to use tags to highlight the phrase, headline, or main points of the text. Over time, the computer learns to recognize these semantic tags and learn the most salient parts of an article. By searching through data in real-time and extracting information based on requested categories, such as events, people, location and dates, “Editor” can make information more accessible, simplifying the research process and providing fast and accurate fact-checking.

Breaking a news, leading on a top trending story and dominating social media is all about maintaining the top ranking. The British Broadcasting Corporation (BBC) is using “The Juicer”, an AI-enabled tool to extract more than 1000 global news outlets’ RSS feeds and aggregates and extracts news articles from the BBC and outside sources. It then assigns semantic tags to the stories and organizes them in four categories: organizations, locations, people, and things. So, if a journalist is looking for the latest stories on President Trump’s chances to win in 2020 elections or articles associated with Democratic Presidential Debate, Juicer quickly searches the web and provides a list of webpages with related content.

Enabling data visualization in real-time is another milestone achieved by Reuters using AI. In 2016, Reuters implemented an interactive data visualization platform across a wide variety of topics including entertainment, sports, and news. Now publishers can access the data via Reuters Open Media Express. Once embedded on the publisher’s website, the data visualizations are updated in real-time. By using this tool, the breadth of information can be as varied as “Apple Stock Prices” to “President Trump’s Popularity” to “Predictive Analytics for Marketing “, all at the click of a button.

Robot Journalism or automated journalism was always a dream of media owners. The Washington Post implemented its AI-enabled platform called Robot Journalism using Heliograf smart software. During the Rio Olympic Games, 2016, the Post used Heliograf as a pilot project for coverage. Heliograf put together the news story by analyzing data about the games as it emerged. This information is then matched with relevant phrases in a story template and the machine adds the information to create a narrative that could be published across different platforms. The software can also alert journalists of any anomalies found in the data. This means that during the Olympics, Heliograf was able to keep up with the information relating to scores and medal counts in real-time, freeing up journalists’ time so they could work on creating other content.

Sports news and updates are always prime subjects for American and European media houses. I have seen people taking a newspaper from a news-stand, keeping only the sports section and throw away the rest of the newspaper without even looking at the front page. For that reason, much of the initial media coverage about “robot journalism” was involved in sports and finance stories at Yahoo. Despite the company’s poor performance for the last several years, Yahoo! still boasts a massive following on its news, finance, and sports media properties. Using Automated Insight, a natural language generation AI tool, Yahoo! claims that by generating content (articles, reports, emails) with data from specific sports teams (or fantasy sports teams), it can kill two birds with one stone: First, the company draws in readers for longer sessions with customized, rich content (based on sports data). Second, advertisers eagerly look for engaging material and are willing to spend more on ads that will gain more exposure for more time with more users.

Competing with competitors on Facebook, Twitter, Pinterest, and LinkedIn is always challenging because leading media houses want to make sure they don’t promote Fake News. The Associated Press (AP) started using AI-enabled platform NewsWhip to keep itself ahead of trending news stories on social media. NewsWhip uses analytics to perform competitor benchmarking on social media, keywords and related verticals, and current influencers across all social media network platforms. AP is also using an Automated Insight’s product “Wordsmith” to turn raw earnings data into articles – which is similar to the case with Yahoo.

Many organizations are also promoting and financing AI lead initiatives in media houses. For example, in 2016, Quartz received a $250,000 grant from the Knight Foundation to set up a Bot Studio to create a set of automated tools for journalists. The move is inspired by the fact that today’s news media has moved not just from print to desktop to mobile phones, but also other internet-connected devices for the home and car.

Every media house is unique when it comes to attracting targeted audiences. In 2016, The Guardian implemented an AI solution using Facebook’s product which allows users to pick from US, UK and Australian versions of Guardian News, choose from a 6 am, 7 am or 8 am delivery time and it will deliver selected news stories every day via Facebook Messenger.

In my opinion, there is a lot of room of AI in journalism, especially in the newsrooms, as it saves time, money and increases the speed without compromising on accuracy, but I don’t think journalists and writers are replaceable with present AI developments. As we are already seeing job cuts in this industry, big publications will gain from the additional capabilities of the AI data gathering and managing. In the next 10 years, I see reporters and machines working together in newsrooms to help human journalists keep up with the ever-expanding scale of global news media.

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