In the build up to the ‘Journalism + Silicon Valley’ event at the Tow Centre on 12th November, Paul Quigley, CEO of co-sponsor, NewsWhip, explains more of his vision of Artificial Intelligence in the modern newsroom. 
The routine of Jamie Siedel, Digital News Producer at News Corporation Australia, will sound familiar to many journalists today.
He starts at 4.30am, with a goal to figure out which stories and events should be the ones that will be “news” today – and push those stories and events to editorial teams at Australia’s biggest news sites – including the Daily Telegraph, the Herald Sun and the Courier Mail. He helps newsrooms answer the question: where should our precious resources be deployed today?
As the day breaks he monitors which stories are getting engagement across the web – and also which angles on those stories are the ones winning the day – what’s the true “lede” for a given story? Why is it doing better on one site than on another?
Jamie is a journalist in the age of “information abundance”. Back in the last media age – say, prehistory to 2000 AD – information was scarce, and the job of making news was easier. There was just less to report.
There was no “user generated content” – few people could create and broadcast or publish media. News moved more slowly – daily print runs, and nightly evening broadcasts. Put these together and you have an environment of less “noise”. An easy media environment to stay on top of.
Today, well, there’s a lot more to contend with.
Almost everyone carries a recording and broadcasting device, and uses it to create and broadcast media (pictures, video, sharing news, text updates). These travel at instantaneous speeds, so at an extremely high velocity. This results in an extremely “high noise” environment, where there are far more digital records of the world – and stories – being created every minute.
In this era, the task of staying on top of the news and social web would be impossible without digital tools to help. Jamie uses NewsWhip’s Spike platform, Google News, and various other tools for discovering stories and then sorting the wheat from the fields of chaff.
We believe the next step for Jamie will be help from artificial intelligence too. Machine learning algorithms will analyze the social web and open web for stories or events that fit the editorial agenda of each publication, and will pre-filter those stories for him and his team. The algorithms will get smarter based on which stories are used, and which are rejected, and will build a picture of what events need to be alerted to journalists, and which ones can be passed on.
The great outcome of all of this? The same thing that happens every time a good technology arrives: it frees up humans to focus on higher value work. In this case, it frees up journalists to report, without worrying about whether they know what stories they should focus on for their audience today.
The Associated Press reported a similar experience from a different kind of automation – using software to write basic sports and business stories. Rather than replace journalists, the automation freed them to focus on contextual storytelling.
Imagine a digital newsroom where journalists don’t need to worry about missing any salient facts – all the stories, digital user generated content and events that might matter to their audience being delivered to them, in a way they define. So they can focus on understanding, editing, storytelling and helping contextualize for their audience – or the people formerly known as the audience.
We’re proud to be co-sponsoring the ‘Journalism + Silicon Valley’ event with the Associated Press, at the Tow Centre on November 12th. If you’re a thought leader in journalism and news technology, join on the day, or follow the discussion on Twitter.

Read More: 

Article 1: Why Social Signals Are Critical To The Modern Newsroom
Article 2: Why NewsWhip Is Building An AI Layer
Article 3: Why We Should Welcome Our New Robot Overlords

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