When companies such as Facebook, Tesla and Citigroup release their quarterly earnings statements, reporters scramble to assess what’s important. It’s no longer enough to just focus on earnings per share and revenue. Bloomberg’s editor-in-chief John Micklethwait has equated the timely dissemination of breaking financial news to “an arms race…with the battleground moving to secondary data.”
It’s also a resource issue. Companies such as Bloomberg and The Associated Press are among those that have changed the way an initial story is published, using artificial intelligence and machine learning to immediately obtain the information with limited or no human interaction, notes Brad Skillman, a managing editor and global news automation leader at Bloomberg.
Automation is also being used to seek out other material details or market anomalies. Micklethwait also points to the use of artificial intelligence in non-financial news like the Washington Post’s reporting on high school sports.
For routine reporting, newsrooms build templates for their stories using algorithms that search for content from press releases, websites and social data using programmed key words and logic. Technology also allows information extracted through automation to be combined with comparable estimates to ensure accuracy, and publishes a tagline that identifies the use of automation in reporting for its readers.
In the case of financial coverage, given its power to move markets, Skillman unequivocally believes “accuracy and transparency are paramount. ... A substantial amount of work is done ahead of time, researching the right metrics and reviewing details before the actual earnings release to ensure we are getting it right.”
This technology-based approach to reporting allows the newsroom to shift its resources in how it pursues the news. As Skillman puts it, “news automation answers the ‘what’ so journalists have more time to find the ‘why’.”
Getting to the “why” is more important than ever given the large volume of content available online with varying degrees of transparency of the source, motive or integrity of the content.
According to USC’s 2018 research on ethics, 64% of communications professionals believe that in the next five years, the average consumer will not be able to distinguish whether or not the content they consume is paid, earned, shared or owned, and 59% believe that for consumers the source will no longer be important.
By newsrooms adopting automation to identify the facts, journalists will be able to turn more of their attention to topics and angles that require human deductive reasoning and judgment. As a result, Micklethwait believes that the increasing prevalence of automation in reporting “gives even greater value to people who can uncover news that computers cannot reach — the fact that two companies are in takeover talks or the corruption of a politician.”
It also places increased responsibility on communications professionals whose skills need to evolve, especially knowing automation could be used to obtain the information. For example, earnings press releases using structured data with a consistent format and key words allow for greater accuracy for automation-based reporting. Website and social data should reflect the key messages and key words used in critical communications like earnings releases and scripts.
To preserve the integrity of news and content, and facilitate the evolution of our collective professions, newsrooms, the communications industry and academia should come together to identify risks, create guidelines, establish ethical standards and encourage transparency. Together, we will be better positioned to win “the arms race” and deliver accurate information to our audiences.
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