Editors and chief executive officers are prepared to enlist () and the power of computing to help them deal with the challenges of the digital age. Indeed almost three quarters (71 per cent) of those we surveyed in our annual digital leaders survey said they were already looking at as a way of creating or distributing content more efficiently.
Given the traditional agenda setting role of editors and journalists, it is surprising that 59 per cent of publisher respondents are considering letting algorithms select stories for users. Even more, that these algorithms might act independently, learning for themselves what might interest a particular user. But most of these early implementations are still trials and journalists remain clear that ultimate decisions will remain under human control.
How the news industry is already using ()
The core focus for many news organisations, as they move from a model based on reach (and ads) to one based on engagement (and subscription or premium ads), is the need to increase the time spent with a particular news brand. That means providing more personally relevant and timely content which is hard to scale without technology like .
An example of how this works comes from China where the most successful news app, Toutiao, has built an audience of 120 million with individual engagement times of 74 minutes per day. Newsfeeds are constantly updated based on what its machines have learnt about reading preferences, time spent on an article, and location. Toutiao claims to have a user figured out within 24 hours.
In the UK, even some of the most traditional journalistic cultures are embracing these ideas. A new recommendation service called James, being developed by The Times and Sunday Times for News UK, will aim to learn about individual preferences and automatically personalise each edition in terms of format, time, and frequency. The algorithms will be programmed by humans but will improve over time by the computer itself working to a set of agreed outcomes. […]