Is Silicon Valley Being Disrupted?
By Santiago Roel Santos on ALTCOIN MAGAZINE
I’ve been thinking more about what makes Silicon Valley unique, and why this innovation hub hasn’t been replicated (to the same degree) elsewhere. Earlier this week, Michael Kremer (with Duflo and Banerjee) won the Nobel Prize in Economics. It clicked then: his O-ring theory of economic development offers a possible explanation.
The theory takes its name from the Challenger accident, where the failure of a seemingly low-level component — the O-ring — caused the catastrophe. Similarly, Kremer posits that small differences in quality produce non-linear differences in output. This is especially true in complex fields, like rocket ship production, that depends on a large number of tasks and where small changes in the quality of one can have a pronounced (even binary) effect on the overall output.
The O-ring theory offers an explanation for the unequal distribution of economic development and the brain drain phenomenon — talent begets more talent and higher levels of productivity. The theory suggests that human capital is the moat and driving force behind Silicon Valley’s high output environment.
The O-ring theory also demonstrates that small bottlenecks in an industry/economy can result in systemic (even catastrophic) effects. As we’ll see below, complex/advanced economies tend to have more interdependencies and rely on high-quality talent to produce comparable levels of output.
Contrary to popular belief, just because Silicon Valley hasn’t been disrupted doesn’t mean that it can’t (or won’t be). Taleb would say that the longer something hasn’t happened or changed, the higher the likelihood that it will. Kremer published his theory in 1993 but it is as relevant today as before, especially as the world has become more interconnected and distributed. Complex and high-talent industries like crypto, where talent is more easily distributed and moving overseas, may disrupt Silicon Valley’s center of gravity. So, the question is: can/will Silicon Valley be disrupted in the decades to come? Let’s explore.
O-ring Theory 101
The O-ring theory is named after the Challenger shuttle catastrophe which was caused by the failure of a single O-ring (a rubber seal that failed in the unusually cold conditions of the launch). Like rocket ships, complex industries depend on a series of dependent tasks working in concert. The complexity of tasks requires the highest-quality talent. As observed in the curve below, small differences in talent have a non-linear effect on output/wages. Moreover, there is a steep tradeoff between the two — a steep decline in output occurs at quality levels marginally below excellence (q<0.98/99).
Complex industries (space exploration, biotech, crypto) have a higher number of tasks that must work in concert and require higher levels of quality in order to achieve similar levels of output. This relationship can be observed in the chart below:
- Red Curve — low complexity industries are defined by a low number of interrelated tasks (t=5). A change in worker quality (x-axis) has a low impact on output (y-axis); there is a linear relationship between the two. Examples: agriculture and textiles (mostly produced in developing and low-wage countries). 0.9 quality = 0.6 output.
- Blue Curve — medium complex industries are those with a higher number of connected tasks (t=10). A change in worker quality has an increasing marginal change in output. Examples: car manufacturing and call centers. 0.9 quality = 0.38 output.
- Green Curve — highly complex industries are those with a very high number of connected tasks (t=40). A change in worker quality has a non-linear change in output. Moreover, in order to achieve a comparable level of output, it requires the highest quality workers (q=0.98/0.99). Examples: space exploration, biotech, and crypto. 0.9 quality = 0.01 output!
The Silicon Valley Flywheel (Talent > Output > +Talent > +Output)
Intuitively, existing talent attracts more talent, leads to higher output/wages, which subsequently attracts more talent. Highly complex industries can only exist in the presence of the highest quality workers. As observed in the green curve above, relatively talented workers (q = 0.9) don’t cut it to produce breakthrough innovations. This is why we don’t have hundreds of SpaceX’s or Google’s. The highest talent (q>0.98) is scarce and concentrated in hubs like Silicon Valley.
Highly complex industries also tend to be capital intensive. And capital follows the highest-quality talent. This circularity explains why some industries/economies develop much faster than others. Again, Silicon Valley is a prime example of this phenomenon.
Bottlenecks
Bottlenecks, like O-rings, can be catastrophic. Developing economies aren’t as exposed to this risk as their output is largely derived from low-complexity industries (red line), which can withstand bigger shocks to quality. But as countries develop, they graduate to more complex industries (blue and green lines). The more complex they are, the more sensitive they are to changes in quality.
We can think of Silicon Valley as a rocket ship — a highly complex machine with many interdependent tasks produced by the highest-quality workers. The moment any one of these tasks/skills deteriorate in quality, it has a material impact on output. At quality levels below 0.98, the marginal decline in output is material. And ripple effects will follow.
We can think of Silicon Valley as a rocket ship — a highly complex machine with many interdependent tasks produced by the highest-quality workers.
Lower levels of output translate into lower wages, which incentivizes high-quality workers to go elsewhere (brain drain), and reduces the incentives to invest in the industry/economy. Perhaps a good example of this phenomenon is India, which over indexes in talent (quality) relative to economic development (output). Corruption and bad government policies have stifled development.
Like O-rings, bottlenecks govern economic development and have a systemic (even catastrophic) impact on economic development. Moreover, bottlenecks have a higher impact in complex industries where subtle declines in quality have a dramatic effect on output.
O-Ring Industries Disrupting Silicon Valley
Not every industry is an O-ring industry. An O-ring industry has a lot of task dependencies, which determines the degree of complexity and the extent to which bottlenecks impact quality and output.
I believe crypto is an O-ring industry. It is highly multidisciplinary and complex — it combines elements of cryptography, economics, game theory, monetary policy, capital markets, government, sociology, and anthropology (likely missing a few disciplines here). Advances in crypto are made possible by innovations in other fields including computing, chip manufacturing, and research in cryptography and game theory.
As a proxy for quality, the crypto developer ecosystem is larger than well-known projects such as Apache and Linux. The team at Electric Capital puts the crypto developer ecosystem in perspective:
The ecosystem is growing at a fast rate and shows no signs of slowing down:
Silicon Valley != Crypto Valley
The recent stance of US regulators towards crypto is arguably already causing high-quality teams to migrate overseas. Singapore, Switzerland, China, and Estonia among other countries are incentivizing crypto teams by offering them regulatory clarity, tax breaks, and other benefits.
So, what does this mean for the overall competitiveness of Silicon Valley and the US economy?
Will crypto disrupt Silicon Valley’s center of gravity?
Will Zug, Singapore or Xiongan come to rival or displace Silicon Valley?
As work becomes more distributed (but remains highly interconnected), will Silicon Valley graduate from being a place to a state of mind?
Kremer’s O-ring theory offers insights into the power-law distribution of economic development and innovation. Silicon Valley has been the greatest beneficiary of this phenomenon — it attracts the highest-quality talent which creates a flywheel of innovation. But the US is at the peril of losing its competitive advantage because, so far, it has failed to remove regulatory bottlenecks that have stifled domestic innovation in one of the most promising industries — crypto.
While regulators have taken measures to protect consumers, there remains a great deal of regulatory uncertainty that has caused crypto projects to spend significant resources in legal and consulting fees. Those dollars would be better spent in furthering innovation and employment, not trying to get regulatory clarity. This bottleneck has arguably prompted many projects to migrate away from Silicon Valley to more friendly jurisdictions overseas.
Tilting The Center Of Gravity
Last, history reminds us that innovation often happens on the fringes and in unexpected places. Britain was an unlikely candidate to emerge as the center of the Industrial Revolution (IR) back in the 1550s — Spain, France, and even Belgium/Holland would have been far likelier candidates on measures of scale of urbanization, health, and wealth/capital (this essay is a fascinating read on the topic). Yet it did, and it can be attributed, in large part, to the creation of the Royal Society which predated the IR — “one of the most important institutions in Europe for the promotion of useful technical and scientific knowledge.”
Again, Kremer and the O-ring theory is right. Talent goes where institutions (private and public) favor innovation, and that is the biggest moat for development and innovation. The moment that begins to breaks down, talent flocks elsewhere. This is perhaps truer and easier to do today with the rise of globalization and the distributed nature of work/collaboration.
After all, Silicon Valley is a recent phenomenon — until the 1960s it was a valley home to prunes, apricots, and cherry orchards. Its rise had much to do with Stanford and William Shockley returning to his home town in Palo Alto to found the first semiconductor company. This paved the road for a community of high-tech entrepreneurs to emerge.
The question is not if Silicon Valey can be disrupted. History tells us that it can, and perhaps will. One thing is certain: if the next Thomas Savery or William Shockley decides to build the next breakthrough in Silicon Valley, then there must be pro-innovation institutions and policies in place.
As the O-ring theory would predict, even small bottlenecks can tilt the balance and produce systemic changes in economic output and innovation. Silicon Valley is composed of much more than crypto, but policymakers ought to be careful what kind of message they are sending to the brightest minds looking to solve the toughest problems. Crypto is one of those fields. And so far, the message has not been characteristically Silicon Valley.
