Is causality the missing piece of the AI puzzle?

Qualcomm AI Research explores fundamental research to combine causality with AI

At its core, science is all about finding causal relations. For example, it is not enough to know that smoking and cancer are correlated; what is important is to know that if we start or stop smoking, then that will change our probability of getting cancer. Machine learning (ML) as it exists today usually does not take causality into account, and instead is merely concerned with prediction based on statistical associations. This can lead to problems when using such models for decision making. For example, we may find a strong and statistically robust correlation between the chocolate…

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• Leo Ware

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