Where Artificial Intelligence May Take Journalism in 2019
2018 was a banner year for artificial intelligence (AI) in journalism. Many of the largest news publishers embraced machine-learning tools to augment newsrooms.
The Washington Post, Associated Press, and Reuters are just a few of the industry leaders who turned to AI in 2018.
Publishers who adopted AI and machine-learning tools have seen results. Last year, Digiday reported The Washington Post’s robot reporter published 850 stories in a year.
Next year, the global media industry will begin to use these new tools at a faster rate. Here are a few current stories on AI that will have real implications for journalism in 2019.
China Debuts AI News Anchor
This month, China’s state-run Xinhua News Agency debuted the world’s first AI news anchor.
Essentially, the AI anchor functions as a CGI entity that can read text and simulate a video of a news anchor speaking.
Xinhua released Mandarin- and English-speaking versions of the AI anchor, but there are some who have questioned whether Xinhua’s anchor can even be considered true AI, because it cannot actually think, nor does it have any apparent decision-making features.
This technology obviously presents potential ethical concerns, and those concerns will begin pop up in the mainstream conversation with more frequency, especially as a disruptive new concept known as “deepfakes” becomes more prevalent in the future.
Deepfakes is the set of technologies that allows for video mimicry. While the technology is only tangentially related to AI, it requires a mention here due to its potential to create serious issues for journalists in 2019.
U.S. politicians understandably are worried, and the Wall Street Journal even is taking steps to train its newsroom on how to spot fake video.
Data Journalism Heats Up
Data journalism is a growing field that empowers journalists with AI-driven tools.
These tools give journalists deep insight into breaking stories using data analytics.
The new field is incredibly important. It allows journalists insight from massive datasets that would be difficult to achieve without the benefit of machine learning.
Large-scale statistical analysis has been an important tool in journalism for a while. Historically, though, it’s been an expensive process to use.
The International Consortium of Investigative Journalists spent $2 million on the Panama Papers investigation, with a large portion of the bill going toward the analysis required to understand and draw insights from large sets of complex documents.
Machine-learning tools are being developed to make data journalism more accessible, and this year, Reuters found success with its News Tracer system.
“Since we started keeping analytical records about a year ago, Reuters News Tracer has beaten global news outlets in breaking over 50 major news stories,” said Reg Chua, executive editor for Editorial Operations and Data & Innovation with Reuters. “This has given our journalists anywhere from an 8- to 60-minute head start.”
This year, Reuters debuted its new Lynx Insight system, a tool that builds off of News Tracer. Lynx Insight represents the next-gen machine-learning systems that will become even more important to publishers in 2019.
What’s Next in AI
Data analytics powered by machine learning has advanced. Some are now working on developing tools to build predictive models that would allow journalists to peer into the future by predicting news events through statistical methods.
Predictive models have been a permanent fixture in economics and academia for many years. However, using these techniques in journalism still is a novel concept.
Although many AI-powered journalism tools still are in development, experts believe AI has the potential to solve a number of other problems that modern journalists are coming up against.
“[AI’s] other big benefits are increased scale, extreme customization and personalization, speed and accuracy and the ability to become systemic on reporting certain beats,” says David Caswell, a fellow at the Reynolds Journalism Institute at the University of Missouri. “There are also longer term benefits resulting from the accumulation of news as data over time that may be even more important.”
Next year is right around the corner.
As big as 2018 was for AI in journalism, it will be nothing compared with the fundamental changes that will take place in the world’s leading news publishers as they fight to remain competitive in 2019.
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Julian Dossett is a freelance writer and black coffee enthusiast. He’s based in New Mexico.
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Artificial Intelligence (AI) is poised to revolutionize journalism in numerous ways, offering unprecedented opportunities for efficiency, personalization, and innovation. AI-driven analytics provide valuable insights into audience behavior and preferences, empowering journalists and digital marketing company alike to optimize content strategies and distribution channels for maximum impact and reach.
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Your point about AI being able to sift through vast amounts of data to uncover trends and patterns is spot on. With so much information out there, it’s easy for journalists to get overwhelmed, but AI tools can really help streamline the research process and uncover stories that might otherwise go unnoticed. It’s like having a supercharged research assistant at your fingertips!
I also appreciated your discussion on the ethical considerations surrounding AI in journalism. As AI becomes more integrated into newsrooms, it’s important for journalists to remain vigilant about biases and ensure that these technologies are used responsibly. After all, the last thing we want is for AI to perpetuate harmful stereotypes or misinformation. Thanks for shedding light on this important topic!
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