Since the first of our ancestors chipped stone into weapon, technology has divided us. Seldom more than today, however: a connected, always-on society promises health, wisdom, and efficiency even as it threatens an end to privacy and the rise of prejudice masked as science.
On its surface, a data-driven society is more transparent, and makes better uses of its resources. By connecting human knowledge, and mining it for insights, we can pinpoint problems before they become disasters, warding off disease and shining the harsh light of data on injustice and corruption. Data is making cities smarter, watering the grass roots, and improving the way we teach.
But for every accolade, there’s a cautionary tale. It’s easy to forget that data is merely a tool, and in the wrong hands, that tool can do powerful wrong. Data erodes our privacy. It predicts us, often with unerring accuracy — and treating those predictions as fact is a new, insidious form of prejudice. And it can collect the chaff of our digital lives, harvesting a picture of us we may not want others to know.
The big data movement isn’t just about knowing more things. It’s about a fundamental shift from scarcity to abundance. Most markets are defined by scarcity — the price of diamonds, or oil, or music. But when things become so cheap they’re nearly free, a funny thing happens.
Consider the advent of steam power. Economist Stanley Jevons, in what’s known as Jevons’ Paradox, observed that as the efficiency of steam engines increased, coal consumption went up. That’s not what was supposed to happen. Jevons realized that abundance creates new ways of using something. As steam became cheap, we found new ways of using it, which created demand.
The same thing is happening with data. A report that took a month to run is now just a few taps on a tablet. An unthinkably complex analysis of competitors is now a Google search. And the global distribution of multimedia content that once required a broadcast license is now an upload.
Big data is about reducing the cost of analyzing our world. The resulting abundance is triggering entirely new ways of using that data. Visualizations, interfaces, and ubiquitous data collection are increasingly important, because they feed the machine — and the machine is hungry.
The results are controversial. Journalists rely on global access to data, but also bring a new skepticism to their work, because facts are easy to manufacture. There’s good evidence that we’ve never been as polarized, politically, as we are today — and data may be to blame. You can find evidence to support any conspiracy, expose any gaffe, or refute any position you dislike, but separating truth from mere data is a growing problem.
Perhaps the biggest threat that a data-driven world presents is an ethical one. Our social safety net is woven on uncertainty. We have welfare, insurance, and other institutions precisely because we can’t tell what’s going to happen — so we amortize that risk across shared resources. The better we are at predicting the future, the less we’ll be willing to share our fates with others. And the more those predictions look like facts, the more justice looks like thoughtcrime.
The human race underwent a huge shift when we banded together into tribes, forming culture and morals to tie us to one another. As groups, we achieved great heights, building nations, conquering challenges, and exploring the unknown. If you were one of those tribesmen, it’s unlikely you knew what was happening — it’s only in hindsight that the shift from individual to group was radical.
We’re in the middle of another, perhaps bigger, shift, one that’s taking us from physical beings to digital/physical hybrids. We’re colonizing an online world, and just as our ancestors had to create new social covenants and moral guidelines to work as groups, so we have to craft new ethics, rights and laws.
Those fighting for social change have their work cut out for them, because they’re not just trying to find justice — they’re helping to rewrite the ethical and moral guidelines for a nascent, always-on, data-driven species.
This post was originally published on O’Reilly Radar.