Artificial Intelligence: Newsroom Savior or Editorial Overlord?
Bloomberg’s bright and sunny New York newsroom provides an excellent analogy. In the fast-changing and often overwhelming world of news and information, transparency and openness are far better than dark closed newsrooms of lore.
This is the third year of Bloomberg partnering with the NYC Media Lab to host the “Machines and Media” conference, and in just twelve months the questions and possible answers about how Artificial Intelligence will impact journalism have evolved dramatically.
Last year, there was a cloud of danger that hovered over the conference. But this year, there was a clearer understanding of where automation had brought us, and how digital tools were an essential part of the solution. I say ‘part’ because a theme of the conference was the partnership of man and machines and how the robots and the humans need to work together to build the future of news.
There are two sides of the AI and news equation. The first is content creation, and the second is content ingestion, and the discovery of themes, trends, and news that is buried in the sheer volume of information.
On the content creation side, news organizations are using AI to write stories on topics that are repetitive and have existing formats. Sports stories or reporting of company earnings reports are good examples.
Bloomberg’s John Micklethwait kicked off the conference with level setting. AI is helping Bloomberg cover much more, not pushing journalists out of jobs but changing the way those jobs are done. Making more media, and sorting more media. Micklethwait said machines and people working together is happening more often than one or the other working alone.
Today Bloomberg serves 2 MILLION pieces of content a day. And Gary Kazantsev, Head of Quant Technology Strategy at Bloomberg wowed the crowd with a live demo of the Bloomberg Terminal and a powerful tool to ingest and parse out nearly all news articles in real time.
Reviewing the firehose of unstructured text, and looking for complex search strings in real time. But then there’s more. Sentiment analysis, topic classification, language detection, novelty detection. Bloomberg customers derive immediate economic value from being able to discern emerging themes, trends, and outliers. Finding signal in the noise is critically valuable.
Chris Collins, senior executive editor of breaking news and markets at Bloomberg, agreed. “Technology is good at repetitive tasks and newsrooms tend to be overloaded with those. If you leverage technology to help with them, journalists can spend more time doing journalism — interviewing sources, breaking news, writing analysis and so on,” Collins told DigitalContentNext.
“It’s essential to understand what technology can and can’t handle. Clearly, as with all journalism, you need judgment, best practices and processes in place to ensure what you are writing is accurate, fast and worthwhile,” said Collins. “You need to be transparent about how a story was produced if it was assisted or published using AI. In our experience, the combination of years of human journalistic experience with technology such as AI is powerful. Obviously, the technology isn’t left to run the newsroom. It is trained and overseen by journalists, who are learning new skills in the process.”
And then — perhaps the most important and complicated question in the room. How can AI help to find, filter, and block fake news? The challenges are immense. Algorithms are written by people, and therefore are rife with unconscious bias. And in order to hunt ‘fake’ content, you need to agree on a definition of what fake is. That, it turns out, is very very difficult. Objectionable content is often a judgment call, and without human judgment and context, using AI to automatically block images or stories is extraordinarily difficult.
So, the Machines and Media conference ends with some remarkable clarity. Artificial Intelligence is here to stay in the world of journalism. Robots will make more and more content, publishing in a multiple of languages and form factors. And at the same time robot’s will are necessary, critically so, to separate signal from noise and find critical clues in the flood of information that now fills our digital daily lives.
The theme this year was about an emerging partnership. Humans AND Machines, not Humans OR Machines. How that collaboration will evolve will emerge in the years to come. And certainly, AI will replace humans in some jobs, even as it creates a new need for human editorial and insights in others.
Exciting, complicated, and important. If we get it right, the speed and accuracy can combat bad actors and so-called ‘fake’ news. If we get it wrong, the machines become editorial overloads. And, that would be bad.