Finding Signal In A Noisy World

A version of this article was originally published here.

In any new and developing space, there is bound to be a lot of noise. New solutions both compete for a new market against existing monopolies — which currently own the market, and against other technologies trying to displace them. Hard To Understand

This is especially true in those breakthrough innovations/discoveries that change our world and force us to use a new lens to understand it. Prior biases make us less likely to investigate the new innovations on a first principles basis. Data is a legacy of our existing models — not these new ones. New ones need to be intuited to predict what will happen instead of forecasted using historical data. We simplify the models in our brains to save time and as a result, most people fall into the trap of predicting their future behavior by looking back at their past.

It is the same reason that when using a Blackberry phone when the iPhone was released, we couldn’t predict how our minds would change — and our minds changing because of new value created, would change an industry. We move instantly when given something of greater value, and it’s impossible to predict that move before we’ve “seen” it.

It is the same reason why Kodak was destroyed by the very digital camera that Kodak created, and Blockbuster failed to see the threat of Netflix until it was too late.

And it is the same reason why all monopolies fail when misunderstanding the value creation delivered to society by a new technology. Technology adoption is most often bottom up versus top down. Why? Simply because the people furthest away from monopoly power have the most to gain, and the people closest to the monopoly have the most to lose.

Add to this that there are always far larger numbers of people farther away from the monopoly than close to it, and it becomes easy to see how fast something that creates more value for those people can take hold and get stronger — rendering a monopoly impotent in fighting it.

Note: This framework is important to consider regardless of whether the monopoly is within an industry, or whether it applies to money itself. Harder To Understand

It is even harder to understand general purpose technologies like artificial intelligence that affect all industries or predict their rate of progress. Because these general purpose technologies apply to most value creation over time, we can easily underestimate the corresponding impact on every business and, in turn, our lives. For example, pretending that a narrow or general artificial intelligence won’t negatively impact our job one day is something we want to believe, which ensures narratives that support that line of thinking are popular — even if untrue. <phoenix-ad