We are bombarded with endless news about the possibilities of High-tech. Starting from venture capital fund managers, development practitioners to entrepreneurs, everybody seems to be after the high tech. Fund managers and Startups are after it for making a quick profit. On the other hand, the UN has been looking into it as a silver bullet for attaining sustainable development goals. Hence, international consultancies and Think Tanks recommend high-tech to less developed countries as a window of leapfrogging opportunities. What are high or frontier technologies? In the past centuries, did we have high-tech?
Technologies have a typical S-curve-like dynamic lifecycle. In the beginning, Innovation potential remains latent. However, after crossing the infancy, some technologies show amenability of rapid progression. And some of them also offer the possibility of reinventing existing products, fueling Creative waves of destruction. It appears that high-tech or frontier-tech refers to those technologies which are at the early stage of their lifecycle and are capable of fueling creative waves of Reinvention. However, upon reaching maturity, they become low-tech.
For example, lithium-ion battery is high-tech as it has been evolving in fueling the reinvention of automobiles. Similarly, machine learning tends to have the potential of reinventing many works processes by replacing the cognitive role of humans with machines. These reinventions will make products better and less material and energy-hungry. Hence, starting from fighting food scarcity to climate change, the human race will substantially uplift in meeting sustainable development goals. On the other hand, many of those reinventions will emerge as creative waves causing destruction to incumbent products, jobs, and firms, and they will empower tiny startups to grow as mega-success stories. Hence, venture capital fund managers are busy funding startups pursuing reinvention out of high or frontier technologies.
High-tech examples:
AI, machine learning, computer vision, blockchain, 5G, lithium-ion battery, quantum computing, robotics, and many more belong to high-tech. Computer vision has the potential to reinvent products and processes requiring human visual perception. Hence, starting from driving to quality inspection, an array of production processes are targets for reinvention, resulting in higher quality and less cost. For example, the replacement of human vision with the computer has the potential to improve accuracy and reduce wastage in production. Similarly, AI, machine learning, and computer vision have the potential to have an autonomous vehicle, resulting in fewer accidents and higher utilization factors of automobiles and road networks.
Challenges in leveraging high-tech opportunities:
Technological knowledge and skill alone do not create economic value. High tech or frontier tech is no exception. Value creation occurs through invention, reinvention, innovation, and usage of products and processes out of frontier technologies. Instead of incremental advancement, high technologies are considered the candidates for reinvention.
Yes, reinvention is our means of dealing with the maturity of growth of existing products and processes. For example, the reinvention of the light bulb through the change of energy-hungry filament by highly efficient LED chips has reduced energy consumption in serving our purpose of getting light. Similarly, the reinvention of television through the change of CRT with LCDs and vacuum tubes with transistors has made them less material and energy-hungry. But despite their ultimate delivery of a better alternative, invariably, all reinvention waves begin the journey as inferior alternatives.
The embryonic beginning of reinvention waves needs a flow of knowledge and ideas through systematic R&D. As the journey of nurturing faint potential into a creative wave of destruction is fraught with pervasive uncertainties, there is a need for a synchronized, well-managed response. Furthermore, their primitive beginnings also create a decision-making Dilemma. Furthermore, not all frontier technologies are amenable to growth in empowering target reinvention waves to reach the inflection points. For example, due to the prevailing weakness of AI and machine learning, the autonomous vehicle reinvention wave is virtually stuck in offering us a better alternative.
Growing role of ideas: high capital investment in R&D and the negligible marginal cost of replication
Family savings and household workshops were good enough for Carl Benz to invent the automobile,. But its reinvention has been demanding a staggering number of resources. Tesla has already spent billions in subsidies to keep pushing electric vehicles; and lithium-ion battery makers had to dig out a Nobel Prize-winning scientific discovery for powering this journey. Similarly, for reinventing Edison’s tinkering-based invention of the light bulb, Nichia had to figure out the technology through Nobel Prize-winning scientific discovery.
The leveraging of frontier technologies through reinvention demands a staggering amount of R&D investment. Interestingly, many ideas distilled from R&D are candidates for software-based implementation. Hence, due to the zero cost of copying software, the marginal cost of producing each product unit with those ideas is negligible. Such a reality reveals that the reinvention of high tech offers a high degree of Economies of Scale and scope advantages. As a result, such reinvention waves have a high Natural tendency of monopoly.
On the other hand, those reinventions also demand less role of the humans in both producing copies and using them. Hence, high-tech possibilities have an inherent tendency to increase Wealth accumulation inequality. Therefore, there are severe governance issues for leveraging high-tech for the common good.
Frontier tech possibilities are elusive:
The possibilities of many high-tech candidate technologies are pretty attractive. For example, the advancement of raw computing power and resolution of image sensors offer the options of making computer vision a far better substitute than human vision. Such possibilities provide the hope of having autonomous cars causing fewer accidents. Similarly, the accuracy of medical diagnostic or crop health assessment could be improved significantly. Moreover, with little effort, such a possibility could be demonstrated with a few training samples and neural networks. But such demonstrations are elusive in nature.
Upon showing even more than 90 percent accuracy, AI-based learning reaches saturation in many applications. Hence, many endeavors of leveraging AI, computer vision, and robotics have become stuck at the last leg. For example, upon investing more than $3billion with the powerful Watson for automating cancer detection and prescription preparation, IBM had to give up at the last moment. Similarly, upon spending more than $500 billion in ASIMO for automating nursing care jobs, Honda has terminated the projects due to the last mile difficulties.
Diminishing labor requirement in frontier tech manufacturing:
Although there has been a staggering need for R&D investment, the replication of reinvited products out of frontier technologies demands far less labor. For example, due to the need for fewer moving components, electric vehicles require as low as 50 percent less labor than needed for gasoline vehicle manufacturing. Besides, the role of frontier technologies in reinventions is in the form of software. Despite the high upfront R&D cost, the cost of replication of software is zero. Furthermore, the implementation of many frontier technology components demands a high level of automation. For example, unlike glassblowers in making CRT, LCDs require high precision automation. Hence, the scope of adding value through labor in manufacturing in frontier technologies has been diminishing.
High tech or frontier technologies are those that are at the emerging state, presenting reinvention potentials. It happens that contemporary frontier technologies are software-intensive, and they demand high-level R&D expenditure. Hence, the natural tendency of monopoly due to growing economies and scale and scope advantages. On the other hand, high-tech reinvention possibilities are elusive in nature. Besides, high-tech manufacturing has been demanding decreasing labor requirements. Hence, in addition to reducing material need and emission, high-tech possibilities have been posing the threat of increasing monopoly, decreasing demand for labor, and growing inequality. In a nutshell, high-tech candidate technologies are highly idea incensive, and they are in the emerging state of their lifecycles.
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