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Putting the Great Stagnation Behind Us

Putting the Great Stagnation Behind Us
We had begun our shift from the Great Stagnation which started with the crash. But COVID19 has convinced many that mediocrity is here to stay.
Technology Briefing


The Golden Age of the Fifth Techno-Economic Revolution is upon us. In fact, as early as 2017, we had begun our escape from the so-called Great Stagnation which started with the crash. But the COVID19 shock has convinced many that mediocrity is here to stay.

Fortunately, Wall Street anticipated the macro-economic trend earlier than Main Street, and this triggered a secular bull market beginning in 2013, which is still going strong. Furthermore, from the vantage point of early 2021, it appears that rather than derailing the Golden Age, 2020’s COVID19 shock simply accelerated the institutional changes needed to facilitate full and effective adoption of Golden Age innovations as they emerge. And, as subscribers to Trends and Business Briefings already know, those innovations in technology and business models are appearing routinely at an ever-accelerating rate.

Consider just one example reported recently by The New York Times. “Artificial intelligence researchers at Google’s DeepMind unit announced that an AI program had solved the mystery of predicting how proteins in the human body fold into 3D shapes. This long-sought breakthrough could accelerate our quest to understand diseases, develop new medicines and unlock mysteries of the human body.”

Obviously, finding the solution to this 50-year-old riddle could turn out to be a game-changer for human health and longevity. But more importantly, this advance illustrates why we have legitimate reasons to believe that the long-term slowdown in technological progress is in the process of reversing. And that’s exactly what the Trends editors have been anticipating since the transition began in 2000.

Once that reversal happens, every manager, investor, and consumer needs to be ready for much faster economic growth and all the good things that go with it, such as higher wages and a better quality of life.

To be sure, this forecast boom is not currently expected by most economists. In fact, all but the most bullish forecasters expect only a growth blip over the next couple of years as the economy rebounds from the pandemic-induced shutdown. That probably means a booming 2021 and 2022 before a deceleration back to an uninspiring pace of around 2 percent, which we’ve been experiencing since the Global Financial Crisis of 2007-to-2009. In fact, the Congressional Budget Office recently predicted that the economy’s average growth potential will be almost a third slower than it has averaged over the past 50 years.

But fortunately, history shows that both the consensus and government studies tend to be wrong more than they are right.

So that begs the question: What would constitute an end to the Great Stagnation and the beginning of a productivity boom? Any precise cutoff will be arbitrary, but a reasonable definition for discussion purposes would be sustained growth in utilization-adjusted total factor productivity of 2 percent per year. For reference, the mean average utilization-adjusted TFP growth from 1947 through 1972 was 2.1 percent per year. Since 2005, utilization-adjusted total factor productivity has averaged just 0.17 percent per year.

TFP growth is defined as the change in real output that cannot be attributed to changes in factor inputs like more labor or more capital. And the utilization-adjusted series corrects for the business cycle. So, it’s one of the best metrics we have for measuring the impact of innovation on the economy.

Why did TFP “hit a wall” for most of the past 15 to 20 years? Unfortunately, when it comes to growing TFP, scientific breakthroughs alone are not enough to drive an end to the Great Stagnation. TFP only budges when new technologies are adopted at scale, and generally, this means products, not just science. Science lays critical groundwork for new technology, but after all the science is done, much work remains. Someone must shepherd the breakthrough to the product stage, where it can actually affect TFP. This means building businesses, surmounting regulatory obstacles, and scaling-up production.

Traditionally, economic growth is enabled by three factors of production: more capital plus more labor hours worked plus more total function productivity. However, in a landmark study from 2016, Accenture and Frontier Economics concluded that artificial intelligence could be thought of as a distinct factor of production because it combines aspects of the other factors and performs a catalytic function distinct from the others.

As the Trends Editors see it, artificial intelligence is a special form of capital investment, which can substitute for many types of knowledge workers, while enhancing total factor productivity. And while we agree about the distinctive mechanics of AI-based productivity enhancement, we believe that its simply an advanced way to achieve increased TFP.

As highlighted in trend #1, we expect Artificial Intelligence to provide the general-purpose technological boost which will transform gloomy forecasts. Typically, the use case for AI is presented as automating operations such as customer service or improving decision-making through data analysis. Obviously, those solutions are important; that’s why companies spent nearly $50 billion on AI systems last year.

The pandemic has been accelerating that trend. Moody’s Analytics economist Mark Zandi says that many businesses “have taken advantage of the pandemic to more fully deploy technologies and process changes that they were investing in but reluctant to take full advantage of during the good times.”

More important, however, is the role of AI as a “super-researcher.” In a research paper titled Are Ideas Getting Harder to Find?,” economists Nicholas Bloom, Charles Jones, and John Van Reenen show how it’s been getting harder to discover the big advances and breakthroughs that drive technological progress and economic growth. The low-hanging fruit has been picked. Their conclusion: “Just to sustain constant growth in GDP per person, the United States must double the amount of research effort every 13 years to offset the increased difficulty of finding new ideas.”

But as we’ve documented previously in Trends, artificial intelligence can go a long way toward solving this problem. Instead of thinking of AI as a general-purpose invention, some economists think of it AI as a general-purpose invention, some economists think of it as a general-purpose method of the invention that can supercharge the research process. As a result, we believe that consistent with Accenture’s estimates, artificial intelligence will add two percent per year to average U.S. economic growth through 2035. That, in and of itself, will make all the difference between having a “Roaring Twenties” and a “Boring Twenties.”

Given this trend, we offer the following forecasts for your consideration.

First, by 2035 artificial intelligence will dramatically impact the profitability of almost every industry, but the implications will be far greater for some industries than others.

For example, AI has the potential to increase profits in education by 84%, while in utilities, Accenture estimates the potential profit impact at only 9%.

Second, enabled by AI and super-cheap gene sequencing, widespread commercialization of five nascent medical technologies will dramatically improve the productivity of health care.

The first gamechanger is reprogramming the body to fight back against infectious diseases & cancer using of mRNA. The second is CRISPR gene-editing technology which is finally becoming reliable enough to therapeutically rewrite segments of a patient’s genome, eliminating genetic defects. “In silico drug discovery” will directly harness the power of artificial intelligence to the problem of identifying promising therapeutic molecules. Combining these three technologies offers the possibility of slowing and even reversing human aging at some point in the 2020s. And combining AI with the Internet of Things and 5G networking opens the door to low-cost, truly effective telemedicine, anywhere at any time. All of this will combine to “bend the health care cost curve” in ways few expect. The key is ensuring that regulatory constraints don’t undermine the benefits.

Third, telecommuting combined with AI-based self-driving taxis and autonomous delivery vehicles will reduce the share of income households devote to local transportation.

Most families will own just one car or none. Highways will be far less congested despite larger populations and parking garages will be repurposed. Many car-related businesses will become obsolete. And many large metro areas will be served by flying taxis, which will also become autonomous by 2035. The net result will be increased safety, lower costs, and a better experience.

Fourth, space will become a major business destination as launch costs drop by a factor of 200.

Payload launch costs to low-Earth orbit (or LEO) which were $65,400/kg with the space shuttle are now at $2,600/kg for the SpaceX Falcon 9. But now SpaceX is talking about $10/kg with its new Starship. And because Starship is designed to be refuellable in orbit, space planners will be able to launch 150 tons to LEO, refuel while orbiting Earth, and then fly the same payload the rest of the way to the moons of Jupiter. That’s exciting. But the real impact may be more pedestrian. Meta-analyses have found that trade volume (on Earth) has a roughly inverse-linear relationship to transport costs. If that relationship holds true for space, a 200-times cost reduction in travel between Earth and LEO should increase “trade” between Earth and LEO by 200-times. Commerce between the Earth and the moon, or between the Earth and Mars, starting from a base close to zero, would be stimulated even more. We will have to wait to see exactly what this portends.

Fifth, for the next 20 years, fossil fuels will dominate the global energy market, despite the best efforts of environmentalists. Emerging economies can’t afford the costs and unreliability of today’s renewables. Natural gas will dominate North American electrical production because it’s clean, cheap, and abundant. China and India will rely heavily on coal. However, by the end of the decade, small-scale nuclear energy and advanced geothermal power will both become cost-competitive and will dominate the second half of the 21st Century. Without heavy subsidies, solar and wind will only become competitive for intermittent applications, and only if storage technologies can be substantially improved. Meanwhile, dramatically improved heating and air conditioning technologies, coupled with the transportation changes discussed earlier will reduce demand in the advanced economies while making upgrades in emerging markets more affordable. So, barring extreme political pressure, we do not believe energy costs will hinder economic growth in the coming years. And,

Sixth, the biggest impact of artificial intelligence will be in terms of scientific discovery and product development where whole industries will be built around discoveries that could not have even been made without the use of AI.

The protein-folding breakthrough mentioned earlier is only the latest of many blockbuster examples. Back in February, MIT researchers reported that “A computer model, which can screen more than a hundred million chemical compounds in a matter of days, is designed to pick out potential antibiotics that kill bacteria using different mechanisms than those of existing drugs,” Similarly, Wired magazine reported on InoBat, a Slovakia-based company which is using a U.S.-developed AI platform to analyze different lithium battery chemistries 10 times faster than what was previously possible. And this is just “the tip of the iceberg” when it comes to harnessing the unique abilities of AI to do game-changing scientific research. Since this technology is still in its infancy, the Trends Editors expect to see a whole wave of previously unimagined solutions, which will form the basis for new companies and even new industries.


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