Boom: Bubbles and the End of Stagnation

by Byrne Hobart

The technological sublime that the Apollo mission represented was replaced by meditation, yoga, and individualistic forms of spirituality. The infinite frontier of space collapsed into the solipsistic horizon of the self.

As Guy Debord, who distilled the dynamics that governed cyberspace decades before it existed, wrote, “That which appears is good, that which is good appears.”

In theory, everyone wants moderation, but in practice, people actually want a moderate-sounding voice that aligns with their views; it’s worth noting that both Vox and Fox News have used branding that is explicitly centrist but implicitly partisan.

The irrepressible desire for optionality results in the perpetual deferral of decision-making. Making a decision—collapsing a range of possibilities into one actualized instance—requires taking risks.

Drug discovery in biotech, for example, is becoming slower and more expensive over time. The cost of developing novel drugs doubles every nine years, an observation referred to as Eroom’s law. 99 In essence, the forces that govern scientific progress invert the dynamics that gave rise to Moore’s law in the semiconductor industry.

Scientific hyper-specialization is, to some extent, an inevitable consequence of the success of scientific progress. Due to the exponential accumulation of scientific knowledge over the past three centuries, specialization has become a practical necessity because it reduces the cognitive load that researchers in any given scientific field face.

Kuhn posits that scientific innovation progresses through revolutions, or “paradigm shifts.” In this framework, the steady and continuous process of scientific development—that is, normal science—is sporadically disrupted by scientific revolutions. These are catalyzed by the emergence of “anomalies,” which are incompatible with the existing paradigm that dominates normal science. A scientific revolution follows a crisis when a novel paradigm, which is “incommensurable” with the practice of normal science, supersedes the previous paradigm.

For Kuhn, it is entirely possible that science could enter a state of eternal normalcy in which the scientific decoding of the “book of nature” has exhausted itself. In this scenario, there will be no further revolutions and revelations. Instead, all that remains is permanent “puzzle solving,” or the fine-tuning of existing scientific theories and models.

High-risk, exploratory science gets less attention and less funding because it is less certain to lead to publishable results. Reducing science to a popularity contest is a good way to ensure that breakthroughs never happen. When they do happen, it is often in defiance of risk-averse, citation-counting bureaucrats.

In sum, systematic evidence showing the decline of scientific progress doesn’t imply that we have unlocked all of nature’s mysteries. Rather, it shows that the causes of scientific stagnation are institutional. Science’s bureaucratic and administrative systems, which are optimized for incremental research, don’t incentivize high-risk research. These systems don’t allow scientists to try, fail, and try again.

An analysis of more than 65 million papers, patents, and pieces of software demonstrates that between 1954 and 2014, smaller teams were more likely to generate novel ideas while larger teams engaged in incremental science.

For him, “the success of ‘science’ cannot be used as an argument for treating as yet unsolved problems in a standardized way.”

Feyerabend argues that the history of science is so complex that it cannot be reduced to a general methodology; asserting a general method will inevitably inhibit scientific progress, as any unifying and static method would enforce restrictive conditions on new theories. Epistemic anarchy would therefore represent a radical alternative that might liberate us from the tyranny of the scientific method.

Holding his head, Musk said, “I’m trying to figure out how we get humanity to Mars with all this bullshit.” Later, he added, “This is how civilizations decline. They quit taking risks. And when they quit taking risks, their arteries harden. Every year there are more referees and fewer doers. That’s why America could no longer build things like high-speed rail or rockets that go to the Moon. When you’ve had success for too long, you lose the desire to take risks.”

To that end, we now turn to an unexpected but highly effective vehicle for enabling just such a Promethean 132 spirit of risk-taking: speculative bubbles.

Cowen notes that even if we move away from energy-dense fossil fuels, the building of solar panels, wind turbines, and hydroelectric plants and the production of electric vehicles and storage batteries, which use massive amounts of rare-earth elements and critical metals, can offset any carbon emissions savings. Short of developing radically novel energy sources (such as nuclear fusion) or other novel technological breakthroughs, large-scale decarbonization and the physical trade-offs it involves will require massive investment and innovation just to maintain the status quo or achieve incremental growth.

For Spengler, only high-agency individuals are capable of temporarily halting the decline.

In the absence of Bretton Woods-era currency controls, investors could bet on the developing world’s convergence with the developed world’s status quo rather than investing in expanding the technological frontiers. Furthermore, countries that wanted to maintain competitively priced currencies could still do so, but only by accumulating US and European financial assets, which pushed global interest rates down. Over time, this dynamic led to a zero-interest and low-yield environment.

Aging, particularly that of large generations, also has cultural gravity. The cartoonist Randall Munroe has pointed out that 16 of the 20 most-played Christmas songs debuted in the 1940s and 1950s; what feels like a permanent tradition is really one generation’s childhood nostalgia.

Yet studies comparing the chaparral fire regimes in Southern California and Baja California, Mexico, found that the practice of letting numerous small fires burn helped prevent large fires. The large fires of Southern California are, in fact, artifacts of a zero-risk strategy, as suppression ensures an abundance of fuel is available when a fire does start.

Almost a century ago, the architect, philosopher, and futurist R. Buckminster Fuller referred to our ability to “do more and more with less and less until eventually you can do everything with nothing” as “ephemeralization.”

One of the biggest categories of long-lived assets is housing. Another is long-term government bonds. An investor who believes that rates will drop and stay low would view a SaaS startup as more attractive than, say, a coal mine, but a 30-year treasury would be more attractive still.

Lower interest rates and benchmarks against fully invested indices increase the relative opportunity cost for this behavior. This means that the marginal price setters are increasingly highly levered hedge funds, whose risk management approach often requires selling losing positions. This exacerbates price swings around big catalysts.

Referring to the dichotomy between a real and a virtual economy, Baudrillard writes that “the sphere of virtual capital has become so autonomous, so orbitalized, that it can in some cases proliferate—or even devour itself—without leaving any trace… Between the two spheres [of the virtual and the real], there is no longer any communication… It is this break between the two, this loss of a referent on the part of the virtual economy, which enables it to produce prodigious effects, but it is also this which protects the real economy from the catastrophes which may occur in the other sphere.”

While not a sound investing strategy, FOMO does play an important role in innovation-accelerating bubbles, as we’ll see in Chapter 2.

Similar to the transformative economic growth that occurred in the period between 1870 and 1970—the “special century,” as Robert Gordon calls it—the modernist cultural event at the turn of the last century could constitute a singular and anomalous event in cultural history.

“It is in this sense that America has become,” Baudrillard writes, the last remaining “primitive society of the future.” It has “no ancestral territory… except in the future and is, therefore, nothing but… perpetual simulation.” In other words, if we constantly entertain ourselves with simulations of the future, then we’re destined to remain in a perpetually primitive state, as a more advanced future still awaits us. Our current level of technology is so primitive that almost all of our techno-scientific advancements lie still ahead of us. But if the future is not a given—if stagnation, stasis, or decline are real possibilities—then the primitive state of Western society takes on a more terrifying meaning. Relative to the past, in which the techno-economic singularity has already happened in the form of previous industrial revolutions, we might regress and become gradually more primitive.

The trend toward interiority and dopamine-inducing simulation—in 2021, a Chinese state media outlet referred to social media, porn, and video games as “spiritual opium”—is reflected in a survey that found that the majority of Western children aged 8 to 12 aspired to become social media influencers while their Chinese peers wished to become astronauts.

Anticipating the current monopolistic and highly centralized version of the internet, author Neil Postman argues that, given that consumers’ self-medication into “bliss” enables the voluntary sacrifice of their rights, amusement and entertainment are more effective means of social control than totalitarian oppression. Comparing George Orwell’s 1984 with Aldous Huxley’s Brave New World, he notes that “in 1984… people are controlled by inflicting pain. In Brave New World, they are controlled by inflicting pleasure.”

This path is not actually a safe one—the failure rate is high, with both bad luck and burnout claiming a large share of aspirants. But it looks safe in hindsight for those who successfully follow it, and so has the appearance of a standard approach.

The exponential increase in computing power captured by Moore’s law is sustained by an explosion of ever-increasing costs. Since the 1970s, research efforts focused on improving semiconductors have increased by a factor of 18, while productivity has decreased by the same factor. This finding implies that it’s now 18 times harder to accelerate Moore’s law than it was half a century ago.

Indeed, a recent survey found that 81 percent of researchers would shift their research focus if they could deploy their grant money however they liked, while more than 62 percent said they would pursue work outside their field of specialization and against the norms of NIH. These findings speak to the ways in which the funding process often determines the trajectory of scientific research, even when it is at odds with the preferences and interests of researchers.

Here, falling testosterone levels, which decrease with age, marriage, and parenthood, could provide a biochemical mechanism that partially explains the risk aversion dominating contemporary science.

In fact, many of history’s most notable scientific breakthroughs were not peer reviewed, including Isaac Newton’s 1687 Principia Mathematica, Albert Einstein’s 1905 paper on relativity, and James Watson and Francis Crick’s 1953 Nature paper on the structure of DNA.

Rather than pushing the epistemic edges, these AI-guided systems tend to excel at interpolating between existing data, not extrapolating to the radically novel and unknown. But at the very least, this silicon-based science could help reduce the epistemic load for carbon-based scientists and let them catch up to the frontier faster. And while cyborgs have yet to take over the world’s research labs, by fully automating replications to verify published findings, AI could help solve the reproducibility crisis.

This might seem counterintuitive at first, since bubbles have funded all kinds of gadgets, fads, and technologies that faded into irrelevance after they burst. But bubbles are among the most powerful mechanisms we have to boost risk tolerance.

By generating positive feedback cycles of enthusiasm and investment, bubbles can be net beneficial. Optimism can be a self-fulfilling prophecy.

At the core of an innovation-accelerating bubble is a definite vision of the future that drives extreme commitment from investors and other participants. A bubble can be a collective delusion, but it can also be an expression of collective vision. That vision becomes a site of coordination for people and capital and for the parallelization of innovation.

In his 2007 book Pop, Daniel Gross runs through a list of historical bubbles, including telegraphs, railroads, dot-coms, and housing, that had undeniable upsides.

Even if the earliest investors in transatlantic cable lost their shirts, cables did get laid, and the world grew more connected. Thanks to overbuilding, a quarter of the entire US railroad system was in bankruptcy by 1894, but the tracks were still there, and cheap transportation remained available.

Railway bubbles made time more granular, since a railroad’s timetable only works if people can show up at the station at a precise time. The Manhattan Project gave us nuclear power and a good reason to develop better rockets. And the Apollo program subsidized the early stages of the transistor, arguably leading to the modern computer revolution.

Therefore, we need to think more carefully about bubbles so that we can discern useful bubbles from destructive ones.

One kind, the classic speculative financial bubble, involves speculators egging one another on, pushing prices higher and higher, until the only justification for asset prices is the expectation that someone else will be willing to pay even more.

The other kind of bubble is a filter bubble. Participants in filter bubbles wall themselves off from opinions they disagree with and become increasingly convinced that their viewpoints reflect the one true way to understand the world.

The likelihood that a futuristic vision will be realized is partly a function of how many people believe in it and how strongly. The believers may get certain details wrong, but if they put enough resources to work on behalf of their vision, they just might attain it—or create something unexpected but still extraordinarily valuable.

Both kinds of bubbles—the classic speculative financial bubble and the filter bubble—can lead to good and bad outcomes. Which outcome arises often depends on whether the bubble in question is a mean-reversion bubble or an inflection bubble.

In the case of a mean-reversion bubble, which is usually but not always a credit bubble, the basic bet is that the future will continue along present trends. It’s based on the assumption that we can extrapolate growth trends based on a future world that’s much like the present, only at a larger scale and with a smaller range of outcomes because we’ve gotten better at managing risks. In a sense, it’s a bet on the Great Stagnation itself.

By contrast, inflection-driven bubbles have fewer harmful side effects and more beneficial long-term effects. In an inflection-driven bubble, investors decide that the future will be meaningfully different from the past and trade accordingly.

If a mean-reversion bubble is about the numbers after the decimal point, an inflection bubble is about orders of magnitude.

A car is not just slightly faster and more reliable than a horse (although in the early days of the automobile industry, it was apparently common for pedestrians to yell “Get a horse!” at passing motorists); cars transformed American cities.