This week, the 2023 World Robot Conference is taking place in Beijing, China. Many companies are demonstrating their latest autonomous machine products, from agricultural robots for cherry picking to humanoid robots impersonating ancient Chinese poets, such as Li Bai.
Compared to a few years ago, when the autonomous machine sector was dominated by commodity robot vacuums and industrial robots, today autonomous machines have permeated into many aspects of our daily lives, especially in China. This makes me wonder whether our society is transitioning from the digital economy to the autonomy economy. If so, what will provide the catalyst for the explosive growth of the autonomy economy in the next decade?
For the past three decades, the world’s economic development has been driven by the digital economy – the use of information technology to create, market, distribute, and consume goods and services. The internet industry accounted for 21 percent of the GDP growth in mature economies from 2005 to 2010.
In 2019, the internet industry contributed $2.1 trillion to the U.S. economy, about 10 percent of the U.S. GDP. It represents the fourth largest industry of the U.S. economy, only behind real estate, government, and manufacturing; it has created nearly 6 million direct jobs, which accounts for 4 percent of U.S. jobs. In part, the U.S. has remained a world-leading economy in the past three decades due to its pioneering position in digital technologies, represented by tech conglomerates such as Microsoft, Google, Amazon, Facebook, Intel, NVIDIA, and others.
With the explosive growth of autonomous machines in both form factors and functions, we may have entered a new technological era: the autonomy economy, or the use of autonomous machines, such as autonomous vehicles, delivery robots, industrial robots, drones, home service robots, etc. to provide goods and services. The autonomy economy’s impact will be even greater than the digital economy.
For instance, the U.S. transportation sector is worth $1.9 trillion, or 8.4 percent of the U.S. GDP. The ubiquitous deployment of one form of autonomous machines, autonomous vehicles, will completely transform the transportation sector. Similarly, various forms of autonomous machines will transform almost every existing industry by replacing human workers or service providers. Hence, a natural deduction is that the countries that dominate autonomous machine technologies will dominate the world’s economy in the coming decades.
The transition to the autonomy economy seems to be happening in China first, as various forms of autonomous machines have gradually become an integral part of people’s daily lives. When you check into a hotel, it’s very likely that a delivery robot is going to bring what you need to your room. When you order food and grocery delivery, robots often deliver the food from the restaurant or the supermarket to your doorstep. At night, it’s likely that you’ll run into a fabulous air show performed by a swarm of robotic drones. At home, robotic vacuum cleaners have become standard home appliances for many Chinese families, just like refrigerators and air conditioners.
However, a hidden caveat behind this superficial prosperity of the autonomous machine sector is the scalability of autonomous machine technologies. The scalability of digital technologies enabled the digital economy to reach economies of scale and transformed the digital economy into the world’s economic growth engine. For instance, Google employs less than 30,000 engineers while serving over 4.3 billion users. The scalability of digital economy companies is mainly constrained by available computer resources and data instead of by the number of engineers; as a result, these companies are able to provide their service at mass scale at a very low price.
In contrast, although many autonomous machine products have emerged in the past decades, such technologies are not yet able to achieve economies of scale. An enormous amount of engineering effort is required to tailor make autonomous machines for a specific function in a specific environment. When the operating environment or the function of the autonomous machines changes, more engineering efforts are demanded. As a result, the costs of deploying autonomous machines to fulfill a specific task are often higher compared to human labor.
This explains why we have seen the emergence of various form factors of autonomous machines in the past decade, but not ubiquitous deployments of these autonomous machines in our daily lives yet. Hence, a further deduction is that the countries that develop scalable autonomous machine technologies will dominate the world’s economy in the coming decades.
As examined in my previous article, China currently leads in the hardware supply chain of autonomous machines, and possesses significant advantages in batteries, servo motors, sensors, and manufacturing capabilities. These are key areas for achieving economies of scale for autonomous machine manufacturing.
On the other hand, the United States leads in autonomous software technologies and computing semiconductors. Particularly, the software technology gap has been amplified by the recent emergence of large language models (LLMs) in the U.S. The application of LLMs demonstrate that artificial intelligence can be general-purpose instead of tailored for a specific application. The variations of LLM technologies can be infused into autonomous machines to perform various tasks, thus achieving scalability.
The technologies in China and the United States perfectly complement each other; however, the current China-U.S. tech tension puts the future of the autonomy economy at a crossroad. If these two countries can still cooperate, then we may see much faster progress toward achieving economies of scale in the autonomy economy. In contrast, if both countries decide to go their own ways, China will have to invest heavily in software and semiconductors in order to catch up with the United States, whereas the U.S. must to reshape their global hardware supply chain in order to supply affordable autonomous machine products.
The competition between these two countries in tech will not only incur very high costs to duplicate autonomy economy systems, but also delay the integration of scalable autonomy economy into society, as it takes years to make up for the missing part in each system.