Automation, Big Data Analytics and the End of Traditional Journalism

The digital age has ushered in an age of crisis for traditional news media organisations and journalists alike. Falling advertising revenue and the rise of citizen journalism has led a dramatic drop in the profitability of news media and traditional journalism (Pavlik, 2013). Pavlik believes that innovation has the potential to reinvigorate the field of journalism, yet fails to consider the implications of innovation on the viability of journalism as a profession. With ever-increasing innovation in the field of analytics in our data-rich world, it is likely that our concept of news and journalism will undergo a radical shift in the not-too-distant future.

In 2011, a young startup in Chicago began work on a news automation service. Known as Narrative Science, the company utilises big data analytics and social media analytics to create simple yet readable news stories. These stories are written and published with minimal human oversight, reporting on topics such as sport, finance and even politics (Levy 2012). Similarly, tech giants like Google and IBM are constantly improving upon their big data analytics capabilities, finding faster and more effective ways to track trends and sentiments through social media and other online sources.

News organisations are already making use of this technology, using social media analytics to find trending topics and to gauge public sentiment (Bartlett 2013). Already, technological innovation has led to a partial automation of the first step in a journalist’s job – finding what to write about.

At the risk of propagating conjecture, is it not altogether likely that the entire journalistic process could one day be automated? As Narrative Science has shown, computers are more than capable of writing simple articles with minimal human input. I propose that with the continual improvement of analytics platforms and the growing amount of data for these platforms to process, computers will one day (sooner than many journalists would care to admit) be able to write stories faster and with more accuracy than any journalist. And for a fraction of the cost.

What does this mean for news media organisations and journalists? As this technology becomes cheaper and more effective, news organisations are likely to begin adopting it, though will probably face harsh competition from established digital companies like Google and Facebook. With diligent editorial oversight and careful criteria selection, news organisations (particularly the big media conglomerates) will be able to tailor their stories to suit their readership and filter out any stories that conflict with their advertiser’s interests.

For journalists however, the outlook is far grimmer. While journalism as a profession is unlikely to outright disappear, computer-automated writing is poised to take over a significant portion of the work currently undertaken by journalists. Consider the following possibilities, some of which are already nearly a reality:

  • In a crisis, news-writing software will be able to aggregate official and social media channels to form a cohesive, informative and unbiased story. Quotes, videos and pictures could be sourced from these channels to provide a potentially unbiased report on any given crisis.
  • Sports results and players can be analysed to create a report on any given sporting event. Furthermore, player/team performance could be compared to past games, social media and current news stories to add a depth of analysis to the report.
  • Analysis of social media channels (combined with any other sources of data that news companies can acquire) could lead to the creation of stories reporting on trends within particular topics or fields (eg, polling results could be combined with social media sentiment analysis software to develop a report on a country’s political climate during an election).

As the distinction between human-written and computer-written stories becomes thinner and thinner, the number of journalists employed by these organisations will decrease. The journalist’s sole bastion may reside in the field of investigative journalism, which is far more difficult to automate.

Yet investigative journalism has all but disappeared from the commercial mainstream media, fuelled by the conflict of interests between media conglomerates’ revenue streams and the public idealisation of an unbiased media (McChensey, 2004). This has relegated the field of investigative journalism primarily to independent online news sources and blogs, such as Vice and Crickey. In a world in which the sporting, financial and current affairs mainstays of a newspaper publication are written by computers, the average journalist may find themselves working for one of these independent publications, likely in an investigative role.

It may well be that in the future, the news we consume will be split neatly into two categories – computer-written and human-written. At the rate with which this technology is improving, given enough time we won’t even be able to tell the difference.

 

Levy, S 2012. “Can an Algorithm Write a Better News Story Than a Human Reporter?”, Wired, Published 24/04/12, Available at: http://www.wired.com/2012/04/can-an-algorithm-write-a-better-news-story-than-a-human-reporter/

Bartlett, R 2013. “How newsrooms can use social analytics to guide editorial strategy”, Journalism.co.uk, Published 19/06/2013, Available at: http://www.journalism.co.uk/news/how-newsrooms-can-use-social-analytics-to-guide-editorial-strategy/s2/a553295/

McChesney, R 2004. “The Problem of the Media: U.S. Communication Politics in the 21st century”. Monthly Review Press. p. 81

John V. Pavlik, 2013, “Innovation And The Future Of Journalism,” Digital Journalism, 1:2, 181-193

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