Much of artificial intelligence (AI) in common use is dedicated to predicting people’s behavior. It tries to anticipate your next purchase, your next mouse-click, your next job move. But such ...

Marketing has always had the potential to be a powerful business multiplier, but its true impact is often misunderstood — or ...

Our foray into causal analysis is not yet complete. Until we define the methods of causal inference, we can't get to the deeper insights that causal analysis can provide. This article details many of ...

There is a missing ingredient in today’s artificial intelligence, which, when added, will make AI a truly indispensable partner in business and increase return on investment over the long haul. The ...

Finding individual-level data for adequatelypowered Mendelian randomization analyses may be problematic. As publicly-available summarized data on genetic associations with disease outcomes from large ...

In this talk, Hal Varian, chief economist at Google, discusses methods of big data analysis that can indicate not just correlation but also causality. He also considers whether access to massive ...

We’re constantly seeking ways to optimize our PPC campaigns and maximize impact. Testing is critical to this process, but traditional methods like A/B tests, incrementality evaluations and geo ...

A shared problem across the sciences is to make sense of correlational data coming from observations and/or from experiments. Arguably, this means establishing when correlations are causal and when ...