We’re linear humans in a world of exponential change.


“Exponential emerging technological changes run counter-intuitive to the way our linear brains make projections about change, and so we don’t realize how fast the future is coming.” Jason Silva


The concept of exponential technologies has been popularized by organizations like Singularity University, which defines it as technologies where the power and/or speed doubles each year, and/or the cost drops by half.


One of the big challenges with exponential technology change in business is that - by definition - it starts off slow. In the early days, pilot projects can look like they’re failing compared to the incremental improvements of more established approaches.



The result is that it the projects look like a bad deal, resulting in organizations taking too long to invest - until it’s too late to catch up those who adopted early.


The trick, of course, is to know which technologies are going to be truly exponential, and the right point at which to invest.


Artificial intelligence is a great example: the opportunities have long been clear, but the results have been disappointing for decades - until now, when advances in computing power and the availability of data mean that there are almost daily breakthroughs.


Blockchain is following a very similar path. So far, there’s been a big contrast between an amazing vision of the future and the current very real practical limitations - I heard one Gartner analyst last year call it the most overhyped technology he’d ever seen. But technology changes fast, and organizations have realized that if they don’t start investing now, they’ll be left behind when it starts to scale.


The problem of human linearity also applies to the adoption of new technology. People don’t like change, so it takes time for organizational processes and cultures to adapt to new ways of doing things.


Simply being aware that fundamental changes are happening isn’t enough. New startups, with the ability to create new organizational cultures from scratch, are often the first to achieve scalable uses of the new exponential technologies, even as incumbents have massive theoretical advantages. The car industry is a great example, with Tesla clearly setting the standard with a modern vision of electrically-powered transportation while the rest of the industry tries to catch up.


So how do we fix the “problem” of exponential technology? We need to be able to implement organizational change at the same rate as technology change. And that means we need to invest more in people.


Paradoxically, this means that getting the most out of technology means spending less time on technology. At least, that’s one of the lessons behind the rise of new digital innovation systems that are designed to help organizations actually succeed with digital transformation, rather than just implementing digital technologies.


What do you think? Can we leverage today’s exponential technologies to help us linear human beings to adapt to technology at exponential speeds?


More quotes about exponential technology and human limitations:


“Our intuition about the future is linear. But the reality of information technology is exponential, and that makes a profound difference. If I take 30 steps linearly, I get to 30. If I take 30 steps exponentially, I get to a billion.”

Ray Kurzweil


“Technology has advanced more in the last thirty years than in the previous two thousand. The exponential increase in advancement will only continue.”

Niels Bohr


“Technology advances at exponential rates, and human institutions and societies do not. They adapt at much slower rates. Those gaps get wider and wider.”

Mitch Kapor


“People need to understand how exponential technologies are impacting the business landscape. They need to do some future-casting and look at how industries are evolving and being transformed.”

Peter Diamandis