The Smug Baldy Speaks

Chris Anderson, Editor in Chief of Wired Magazine, believes that we’re entering a new age of scientific understanding that renders the “old” scientific method obsolete. The reason? We now live in an age where petabytes of data are available, and we can now use powerful computer and mathematical models to find heretofore unanticipated correlations.

This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out with every theory of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.

The point that Anderson is trying to make is that now that we have such an overabundance of data, we don’t really need science anymore. We don’t need to worry why things happen, only that they do happen, and that’s good enough.

The problem with this sort of thinking isn’t just that it mistakes correlation with causation, but that it elevates the role of data in our thinking about natural phenomena to an undeserved level. As I mentioned before, scientific reasoning begins with data - it doesn’t end with it. In Anderson’s world, there’s some level of data at which we can stop asking why. He claims that the more we learn (that is - the more data we have) the farther we are from having good theoretical models that account for the facts.

That’s an interesting position, but it’s wrong. Even in the cases he uses, such as theoretical physics, the volume of data isn’t what threatens our mental models - nor does it need to fundamentally alter how we go about creating those models. As he correctly points out - data without a model is just noise. To go from that truth to a conclusion that boundless vistas of disconnected data are somehow more than noise is quite a conceptual leap.

More data doesn’t change - and certainly doesn’t obsolete - good scientific reasoning from facts toward organizing principles that account for those facts. Instead, new mountain ranges of data provide the possibility of new discoveries and challenges to existing theoretical structures that simply cannot explain them. We’re not facing some data-driven obsolescence of the scientific method.

Instead, we’re probably looking at an acceleration of it.