Recently, a friend of mine, analyst Syed Muhammad Osama Rizvi, wrote a fascinating article in the Pakistan-based Express Tribune (with Linked In commentary here) about the nature of innovation and its role in the shift of America from a barely subsistent agrarian country into one of the most powerful countries on earth. Overall, I'm in agreement with his assessment, but I also think that there's more to the story.
The twentieth century globally is remarkably anomalous when looked at from global demographics, and in the US in particular, the transition from a fairly sleepy regional power of 76 million in 1900 to the dynamo of nearly 331 million in 2020 could be attributable to innovation, but it also was dependent upon other factors.
Indeed, it's worth viewing the growth of innovation relative to the growth of population in the US. The first benchmark census in 1790 put the population of the US at just shy of 4 million people. The country grew by a factor of 19 in the first 110 years, but only by a factor of 4 in the second. That initial growth was due to an obvious factor - Americans went from a sparse fringe population distributed across the Eastern seaboard to a country the size of Europe by expanding into territory that was sparsely held by the native American tribes (bringing with them decimation and disease in the mix),
During this period there were major innovations - steam-driven railroads made it possible to create markets and extract resources across vast areas, revolutions in canal making turned the Great Lakes into an inland sea with trading ports all across the region, refinements in metallurgy made it possible to create better plowshares and more reliable guns. Telegraphs made long-distance communication possible. It's worth noting though that in all of these cases, the innovations were also driven by higher population densities, a growing number of educational institutions, and as a consequence, higher literacy rates. People were learning more from more people, and, in turn, were spreading this knowledge along increasingly robust networks.
Innovation, when it comes right down to it, is a mixing function. Take a glass of water, and very slowly drop in a stream of red dye towards one edge of the glass, and blue dye in the other. Over time, the blue and red dye will start to move around in eddies and vortices and will create clear fractal structures with interweaving read and blue strands. Left to its own devices, the glass of water will eventually turn purple, but it may take hours or even days for that to happen.
On the other hand, heat the water first to boiling, then repeat the same experiment. The same mixing will happen in minutes. Why? because the hotter the water is, the faster the molecules within it are moving, and the more contact that they make with one another as a consequence.
Similarly, stirring that water after the dyes are added creates eddies and turbulence that also brings the two color dyes together. In populations, population density increases encounters, but only if there is diversity. If the population has the same basic values, beliefs, and expectations, nothing significant will happen - current beliefs are reinforced, while innovation stagnates. It's only when the interactions occur where population density is mixed with different cultural beliefs and knowledge that you get novelty, the process of different ways of attempting to solve the same problems becoming refined by alternative approaches.
San Francisco (and Silicon Valley) is actually an interesting case in point here. San Francisco started as a port town, a place where trappers, loggers and farmers would bring their products to sell, where miners would sell their gold and where finished goods manufacturers out east would sell their wares. The population was diverse, both culturally and ethnically, and because of its strategic placement, the City By The Bay also become a significant military emplacement. It's not at all surprising that it became a hotbed of innovation long before the first computers appeared on the scene. Yes, the technology increased the standards of living, but that technology occurred because of the collision of worlds that made up San Francisco in the 1860s through the early 1900s.
Silicon Valley arose because of this mix, but arguably, as the city's cultures have become more stable (and more stratified) the diversity that marked the latter half of the twentieth century is increasingly becoming a monoculture. When you have thousands of startups in such a concentrated area, after a while, you see the reinforcement of established ideas rather than innovation brought about by interaction with other beliefs.
This is actually one reason why the watercooler argument doesn't really hold much sway. Many companies talk a lot about how innovative they are, and how having people located in a single workspace increases that innovation, but I'd argue that companies actually stifle innovation because they create microcosms in which there is comparatively little mixing of distinct cultural and technological ideas. Put a lot of likeminded people into the same room, and the solutions that they come up with will be those that mostly correspond to the zeitgeist of the company itself.
The fear of a competitor stealing a new technology weakens the innovation that makes that technology valuable, while at the same time increasing the likelihood of convergent evolution where several different organizations come to the same technological endpoint without realizing it. It's also one of the reasons that both conferences and open source technology are so important - they do provide this mixing factor, and do establish a mechanism for the communities in question to cross-pollinate.
The other factor that causes innovation to happen is the inefficient access to energy. The reason for the "inefficient" part has to do with the fact that early technologies usually require a lot of energy to create and/or run because they are so inefficient, and only over time are these technologies optimized to be more efficient. Purely electric vehicles were being constructed as early as the 1890s, but batteries couldn't be made powerful enough to move vehicles fast enough to make a difference. This is why the internal combustion (IC) engine gained hold: gasoline holds much more power per liter than a lead battery by itself, and even though the early IC engines were extraordinarily inefficient, they were efficient enough (and gas was cheap enough) to win out over battery power.
Steam-powered locomotives appeared before cars primarily because the earliest trains were built near coal deposits, which had much more energy per cubic meter than charcoal did, yet you still needed to devote an entire train car to burning that coal along with another several cars tasked with carrying additional coal as fuel for longer trips. The internal combustion engine made moving smaller vehicles around possible since most of the space wasn't taken up with fuel transport or combustion.
Seen in that light, the market is not responsible for creating innovation. Indeed, the market creates nothing of value, but only acts to establish consensus on value. Let me repeat that point because I think it's important to understand: the market itself creates nothing of value. Instead, it serves as a vehicle for more efficiently determining the value of specific transactions relative to one another, when it is truly representational.
I would contend that the stock markets as they exist today don't do a very good job of determining that price point, largely because the speculative function that is used to predict the future value of a good or service has been replaced by a speculative function that largely tracks where dividends are most likely to be had. If dividends actually reflected sales, then it becomes a good proxy. When dividends instead reflect accounting changes (moving money from overseas because tax rates are low, public companies buying back their own stock to goose their share prices before execs can cash out, or the Fed injecting trillions of dollars into the economy to keep it from collapsing, then the stock markets cease to have any reasonable connection to the value that companies provide.
When the stock markets have a reasonable connection with true innovation, markets disseminates innovation, making it possible for an innovation to be used in facilitating transactions, providing the resources for innovations to be realized more efficiently. This holds as true when that market is github as it does if the market is the NewYork Stock Exchange. Indeed, it can be argued that the monetary aspects of exchanges and the profit-taking in the buying and selling of shares can actually prove to be a disincentive for innovation because they tends to move money away from those innovations that most need that money to those investments that are safe and dividend producing, but that actually provide comparatively little value.
This also highlights the complex relationship between innovations and jobs. A job, at its core, is the payment of a person to complete a task - you are exchanging money (a proxy for previously accumulated value) to a person or team of people to utilize their skills, strengths, and expertise for a particular end goal, whether that be building a house, cooking a meal, or building a weapon. In this viewpoint, a job is episodic, and it usually described most labor transactions up until the 19th century. Some jobs are open-ended - a guard, for instance, is paid to watch and protect a person or place, and in that respect, it makes sense to pay them on a regular basis, because it is unknown how long such a guard will be required.
That surety of wages was perhaps one of the biggest innovations of the last two hundred years. Once you ensure a consistent wage (barring being fired), then you end up spending less time trying to find additional work and can invest more of what you make in yourself and your family. In essence, an employer is paying for your availability to work at any time (within a specific range), rather than for the completion of a specific task. It was what made up the burgeoning middle class throughout the late nineteenth and early twentieth centuries.
There were, unfortunately two major consequences of the rise of automation towards this surety. The first was that, as automation (another form of innovation) became more efficient, there was less need for human labor. This played out especially in the mid-twentieth century, when advances in machining (particularly after World War II) began to eat into the manufacturing workforce. Tools went from augmenting physical capabilities to replacing them and contributed to the decline of manufacturing and agriculture (both previously manpower-intensive) as a segment of the economy in the US.
This then impacted increasingly cognitive (service-oriented) work, where computer software eliminated whole swathes of departments such as accounting, payroll, and even sales. That there were new opportunities that opened up in utilizing these technologies to augment a given individual's skillset offset this to some extent, but in general augmentative technologies typically become fully automated technologies within twenty years, as expertise becomes increasingly captured in code. The discussion of the Singularity, the point where computer technology reaches a stage where it becomes difficult to see a way forward for society, has been pinpointed to around 2040, and while that number may be off by a decade or so, it's opacity as an asymptotic phenomenon is becoming more and more obvious. The society that exists beyond that point becomes very difficult to predict.
The second consequence of automation is that it has now irreversibly broken the concept of wage income. Companies, typically operating on quarterly budgets and dealing with benefits mandates that come in only when hours worked exceeds a set limit (usually 37.5 hrs/week), now have the flexibility to force lower-income workers into an hourly basis where they are essentially on call at all times but only paid for those hours that they are actually working.
The initial idea of a full-time wage was that the worker would be paid less per hour in exchange for wage surety, yet once forced into a part-time mode a person's hourly wage generally reflects that "paid less per hour" rate, in essence providing neither income nor surety. Because of the nature of scheduling, the hours they are not working cannot be filled with other work efficiently, and in many cases, such dual work may be grounds for dismissal. Workers become poorer, to the point where they can no longer afford to live in the cities where they work, with those higher up on the socio-economic scale continuing to be paid at full wages while working far fewer actual hours.
It's worth noting here that this inequality works at every level - in general, the higher your socioeconomic status, the more likely that your income is derived at least in part from dividend instruments - stock options, stock grants, rental income, stock dividend payments, trusts, and inheritance income.
It is also likely that your network will also tend to be more likeminded than not. If you make available your income per year from all sources and express it as a power of ten (i.e., someone making $10,000 a year would have a log value of 4 (10 to the fourth power, or 10,000), $100,000 a year would have a log value of 5 and so forth, then it is likely that the average person in your network will be within a quarter log value either way (a person with a 5 income ($100K) may view people who have a 4.75 or 5.25 ($60K to $180K, roughly) as their socio-economic network, but much beyond this range, there's simply little interaction.
When incomes are continuous, this isn't that much of a problem - if I have visibility to someone who's at $180K and they have visibility to someone who is at $316K (log value 5.5) then it becomes possible (albeit progressively harder) to push ideas up the chain. Where this breaks down is when bands form, and you end up with the upper end of one band being below the lower end of the next band. That can occur when you have regulatory or taxation based systems that tend to segregate people into certain financial ranges. I believe we have entered such a period now, and one of the biggest impacts of this is that for all that what we are doing technologically seems almost magical, in reality, innovation has been slowing dramatically, and no amount of social media memes and marketing wish-fulfillment is going to change that.
This social-economic stratification acts as an impediment to innovation because people within the same general economic bracket usually tend to also have similar ideas and priorities. This also tends to play out within companies. Seventy years ago, it was still possible for a person who started in the mail-room or on the factory floor to become CEO of a company, primarily because hires tended to occur inhouse. Today, most hires tend to occur from other companies, and the expectations in general on those hires is that they conform to the same social strata as others at the same level. This cross-hiring may bring in new perspectives, but ironically the "innovation-content" of those perspectives may actually be less than those coming from below who have encountered first-hand the problems that the organization faces at varying levels.
Finally, diversification of viewpoints is important beyond being a manifestation of identity politics. Think of each person as a multidimensional vector of interests, priorities, and concerns (each vector pointing in a certain dimension). When you vote on an action, what you are doing is adding up those vectors among all members of the electorate and then from that determining the vectors that least cancel out to determine what the priority is for that group. In a representative democracy, you are voting for a representative whom you feel most closely represents those values that you feel are important. When you do not take diverse viewpoints into account, a bias is introduced where the course of action (or the representative) does not in fact represent the group, but rather only one particular viewpoint, and that viewpoint may not be (and most likely is not) beneficial for the group overall. The opposite of innovation is stagnation and calcification.
It's no real surprise that racial and gender tensions are high in the United States at a time when inequality is also at its highest point since the 1890s. Nor is it surprising that innovation at all levels of society is at its lowest point. As a society, we are regressing, becoming stratified, reducing upward mobility, and building walls intended to reduce the mixing of ideas while promoting the veneration of ignorance and apathy. Innovation has become a corporate buzzword, hauled out for corporate business statements and TED talks, but increasingly a word devoid of substance or meaning. The result is a system that is, if not failing, at least stagnating.
At the end of an essay such as this, there should be a call to action, do this to avoid that or make the other thing possible. I'm struggling to find one here.
I think the biggest takeaway from all of this is to stop being concerned about innovation, or, more to the point, stop trying to monetize innovation. There are many, many problems that we currently face - the pandemic, the economic crisis, crumbling infrastructure, climate change, decaying educational systems, and so forth - which can already be solved by existing technology, but which do not necessarily have a profit motive attached to those solutions.
In more than a few situations, the problems we face today are due to the technology that we introduced to solve yesterday's problems. At some point, we are going to discover that we've pushed the can down the road so far that it's bounced up against a concrete barrier and hits us smack in the face.
Kurt is the founder and CEO of Semantical, LLC, a consulting company focusing on enterprise data hubs, metadata management, semantics, and NoSQL systems. He has developed large scale information and data governance strategies for Fortune 500 companies in the health care/insurance sector, media and entertainment, publishing, financial services and logistics arenas, as well as for government agencies in the defense and insurance sector (including the Affordable Care Act). Kurt holds a Bachelor of Science in Physics from the University of Illinois at Urbana–Champaign.