Machine Learning Fails When We Need It Most

We are in the midst of a crisis. In these unprecedented times and extraordinary circumstances, the rapidly evolving conditions make it even harder for organisations of all kinds to adapt quickly. And now, when machine learning is needed most, it fails to deliver.

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This paper sets out how understanding causality is the key solving this problem. Causal AI truly understands the relationship between cause and effect and only requires a few data points to make an accurate assessment about a new regime. It adapted 3 times quicker to new conditions than models built with current state of the art machine learning technology