New machine learningtechnologies, user interfaces and automated content creation techniques are going to expand the personalization of storytelling beyond algorithmically generated news feeds and content recommendation.
The next wave will be software-generated narratives that are tailored to the tastes and sentiments of a consumer.
Concretely, it means that your digital footprint, personal preferences and context unlock alternative features in the content itself, be it a news article, live video or a hit series on your streaming service.
The title contains different experiences for different people.
When you use Youtube, Facebook, Google, Amazon, Twitter, Netflix or Spotify, algorithms select what gets recommended to you. The current mainstream services and their user interfaces and recommendation engines have been optimized to serve you content you might be interested in.
Your data, other people’s data, content-related data and machine learning methods are used to match people and content, thus improving the relevance of content recommendations and efficiency of content distribution.
However, so far the content experience itself has mostly been similar to everyone. If the same news article, live video or TV series episode gets recommended to you and me, we both read and watch the same thing, experiencing the same content.