Understanding the Second Machine Age Beyond Prediction

In The Digitisation of Just About Everything, the authors explain how the rise in digitisation is changing the nature techno-social systems. They recount the economic properties of information identified by Varian and Shapiro—zero marginal cost of reproduction and the fact that information is non-rival—and add that, in what they regard as a ‘second machine age,’ some information is no longer even costly to produce. All of this is augmented by increasingly better, cheaper and more sophisticated technologies.

At the core of the author’s appraisal of the benefits of digitisation lies the notion that digitisation will help us to better understand and predict different behaviours. There is a strong element of truth in this. Statistically speaking, our models do get better as we have more data—and this is primarily what digitisation has left us, more data. However, I do not think the process will be as straightforward as the authors depict it. More data does not necessarily mean better data. And digitisation is only partially equipped to provide us with that. Digitisation can allow us to record new kinds of information about more people, but that information is limited to the digital realm. As much as technologists want to believe it, there is no one-to-one correspondence between the digital and physical worlds.

Digitisation is an enhancement to old statistical techniques, not a panacea. Our challenge is to understand the consequences of the constant, increasingly more complex interactions between the digital and physical realms. This entails more creativity and audacity than mere statistical prediction, because the encounter between these two worlds in yielding a context that is different from its parts. Once we understand this, we can begin to comprehend new behaviours instead of just extrapolating old ones.