Despite all the excitement for today’s technology, we still see shadows of doubt here and there. We hear the voices that say innovation has fallen short of its promise. A decade ago, the Pentagon physicist Jonathan Huebner published a study called, “A Possible Declining Trend for Worldwide Innovation.” In it, he took 7,200 key historical innovations and plotted them onto a graph, expecting exponential growth. Instead, he found decline. The curve peaked in 1873 and has been going down ever since.

The future of innovation

Huebner wrote, “Perhaps there is a limit to what technology can achieve.” Some people wonder what happened to the flying cars we dreamed about when we were young.

Indeed, for every person who says Silicon Valley is about making the world a better place, there seems to be a naysayer who says we’re just making apps to let you track your dry cleaning. But if you ask me, these doubters of innovation are pointing to the wrong things. While they’re talking about flying cars, I’m talking about what’s under the hood, and that’s artificial intelligence (AI). Today, we are witnessing the dawn of attainable AI, something that’s magical — not as a thing of invention, but as a thing of infrastructure. AI is like running water. We don’t marvel at running water, but where would society be without it?

Finding the limit

Even Huebner himself acknowledges in his report that an alternative reading of the data reveals a limit to the human brain, rather than to technology. He wrote, “For the first time in history, people are bombarded with far more information than they can process, so sending them increasing amounts of random pieces of information will not increase their rate of innovation.” We’ve been living with big data for a decade or so, but right now we’re interpreting just a fraction of this data, because there’s a natural human limit to the amount of data that we can turn into meaning.

AI like running water greatly augments our natural ability to make sense of information. It might be the multiplying factor we need to begin digesting data at such high volumes that the resulting insights launch us into a new and unknown mode of society.

Laying the groundwork

Right now we’re talking about AI, but in five years we’ll be talking about something else — and we don’t even know what that is yet. Today is the first phase of this transition to an AI-based digital infrastructure. Just look at Google. Last year, they swapped out the algorithms behind Search, replacing its rules-based engine to a machine learning engine, and you probably didn’t even notice. Or, there are companies like mine that are pioneering the use of AI for risk management, leveraging the power of machine learning to detect patterns and make commerce safe. It’s a pattern that’s being repeated across every major industry. Business leaders are eager to run AI through their organizations, but first we must lay the pipes.