From Principles to Machine Learning
Not the other way around.

False news has to be fought

We at Lingmill are into AI and machine learning, that's for sure. But to secure the quality of our texts and to know that they are based in facts we start from a different angle.

We don’t pour data into a machine learning process hoping it will produce “nice texts.” Instead, we start by setting up journalistic principles and order of preferences. And when we obtain secure texts, we add manual improvements and machine learning to enrich them, adding variety, and adding alternatives.

This isn’t always the fastest way, though it is fast, and it isn’t always the conventional way within the AI field. But in a context where false news has to be fought, we think it’s the better way.

So we work like this:

  • Secure trustworthy and reliable data sources.
  • Stipulate journalistic principles and decide what to pick out.
  • Create the foundation for the text robot.
  • Enhance these principles with statistical analysis and machine learning.
  • Add variety and alternatives, both manually and with machine learning.
  • Write and publish news and content.

This is how we at Lingmill can deliver news that are safe and true.

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