Tag Archives: random forest

Investigative journalism’s AI challenges: accuracy and bias, explainability and resources

1 Reply
screenshots of guidelines on AI

Having outlined the range of ways in which artificial intelligence has been applied to journalistic investigations in a previous post, some clear challenges emerge. In this second part of a forthcoming book chapter, I look at those challenges and other themes: from accuracy and bias to resources and explainability.

Continue reading →

Data journalism’s AI opportunity: the 3 different types of machine learning & how they have already been used

8 Replies

I understand that you want me to explain how Ava works (from Ex Machina)

This week I’m rounding off the first semester of classes on the new MA in Data Journalism with a session on artificial intelligence (AI) and machine learning. Machine learning is a subset of AI — and an area which holds enormous potential for journalism, both as a tool and as a subject for journalistic scrutiny.

So I thought I would share part of the class here, showing some examples of how the 3 types of machine learning — supervised, unsupervised, and reinforcement — have already been used for journalistic purposes, and using those to explain what those are along the way. Continue reading →