Three examples of machine learning in the newsroom – Global Editors Network – Medium

In 1959, Arthur Samuel, a pioneer in machine learning, defined it as the'field of study that gives computers the ability to learn without being explicitly programmed'. Machine learning can translate to using algorithms to parse through data, recognise patterns, and then make predictions and assessments based on what the algorithms have learnt. Machine learning can be used for fact checking and it can make archiving less of a tedious task for journalists. It can let voice assistants like Alexa or Google Assistant know you're pissed off based on the tone of your voice on a Monday morning and then play a song to cheer you up. It can also be used to explore scenes in Wes Anderson films and help uncover hidden spy planes. In short, machine learning systems could very well become essential journalism tools in the coming years.