AI journalism: how augmented journalism will enhance the newsroom of the future

AI journalism- from science fiction to business reality

What will the newsroom of the future look like? According to a recent survey on journalism and technology trends in 2021 conducted by the Reuters Institute for the Study of Journalism, publishers see AI as the biggest enabler for journalism over the next few years, as shown in Figure 1.

Figure 1 : Data from a survey of 234 media leaders in 43 countries for Journalism, Media and Technology Trends and Predictions 2021.

At its core, augmenting journalism with AI is about automation. The main goal is to help journalists become more efficient and productive by using technology to reduce time and effort spent on laborious and repetitive tasks. It’s about human-machine symbiosis. To fully realize its adoption potential, AI needs to be applied in a way that is complimentary to both people and processes within news organizations.

AI journalism: examples of how AI is being used in journalism

• Improving efficiency - sourcing of information, story idea generation, identifying trends, investigations, event or issue monitoring, extracting information or content.
•  Increasing productivity and lowering production costs - content creation, editing, packaging for different formats and platforms, text, image and video creation, repurposing content for different audiences.
  
• Improving content quality - e.g. combatting fake news.
  
• Delivering more relevant content - personalisation, marketing, finding audiences, understanding user behaviour, monetisation/subscriptions.
  

Figure 2 : Reuters Institute for the Study of Journalism poll: Q11. To what extent will the following uses of Artificial Intelligence (AI) be important to your company in 2020? N=218

Does Eidosmedia have AI capabilities?

In the past we’ve mainly relied on integrations with 3rd-party providers to enrich our offering with AI services. We’re still using this approach to respond to specific customer needs.

Recently, however, we’ve also started to actively experiment in-house with new Machine Learning models, with the focus on the following use-cases:

• Suggestion / Completion
  
• Summarization
  
• Semantic Search

These capabilities are only experimental for now, but depending on performance results, we may decide to productize them as part of our overall offering.

Discover our news & media publishing CMS

Read our case studies with AI journalism examples:
Intelligent article auto-tagging system