Contextual knowledge is integral to understanding why we behave the way we do. Why we might buy one product over another, invest in that crowdfunding campaign or choose to watch a particular movie, these decisions are governed by a complex set of functional, social and emotional reasons. Whilst this may be something humans take for granted, machines need to be taught how to do this. According to the economist Clayton Christensen, the causality behind why someone might purchase a particular solution is what matters most in innovation, not correlation.
In this video, Jermain Kaminski, an assistant professor at Maastricht University, talks about his recent research on experimentation and causal machine learning in entrepreneurship and innovation. He explains how applying causal models to big data can help businesses and entrepreneurs make better business decisions in positioning and improving their products.
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