From: jimruttshow8596
Brian Arthur, a leading economist and complexity thinker, explores the fundamental nature of technology and how it evolves, drawing on concepts from his book, The Nature of Technology: What It Is and How It Evolves [00:02:10].
Technology as an Academic Field
Despite its pervasive importance, technology, unlike the history and philosophy of science, is not a rich academic field with deeply developed theories [00:02:37]. This might be because engineers, who work directly with technology, are not typically focused on its foundational theories [00:03:10]. Furthermore, technology is often viewed as a “lesser sibling” to science, with science receiving more glory and blame, leading to a “bad rap” for technology [00:03:27].
Defining Technology: The Orchestration of Phenomena
Arthur’s central idea is that technologies are built upon “phenomena,” which are observable occurrences in the natural world, often rooted in physics [00:06:37]. Technologies are “orchestrations of phenomena” or “programmings of phenomena,” combining various physical or electrical principles to serve a specific purpose [00:09:42].
- Example: The Hand Axe: One of mankind’s earliest technologies, the hand axe, harnesses the phenomena of momentum transfer and the solid-state physics of materials [00:10:13].
- Example: X-rays: Wilhelm Conrad Röntgen’s discovery of X-rays in 1895, through experiments with Crookes tubes, revealed a phenomenon that allowed for looking at the internal structure of limbs, quickly leading to the birth of radiology [00:10:41].
Technology and the Economy
Traditionally, economics viewed the economy as a container that periodically created new technologies, which could then be “slid in” to improve the economy [00:14:15]. However, Arthur argues for a reversal of this perspective:
“It’s not that the economy creates technologies… A much rounder story is that technologies create the economy.” [00:14:54]
This view, shared by earlier economists like John Stuart Mill and Karl Marx, suggests that an economy is fundamentally built around its means of production [00:15:26]. Technologies form the “skeleton” of the economy [00:15:52].
- Epochal Shifts: Major clusters of technology define new eras and redefine society over decades [00:18:08].
- Settled Agriculture: The development of settled agriculture, based on a “folk genetics” of selective breeding, allowed for high enough yields to make permanent settlements worthwhile, initiating a new epoch [00:16:36].
- Automobile and Suburbia: The automobile led to the suburban era, transforming urban layouts and lifestyles [00:17:20].
- Railroads: The cluster of railroad technologies (locomotives, rails, better steel, signaling) transformed transportation, drastically reducing travel times and enabling a “new economy” [01:18:54].
Schumpeterian vs. Equilibrium Economics
Traditional equilibrium economics, which gained prominence around the 1870s with the use of algebra and calculus, tended to keep economic variables constant and static [00:23:02]. It focused on comparing static “snapshots” of the economy before and after a technological improvement [00:28:40].
Joseph Schumpeter, however, argued against this static view, asserting that the economy is constantly changing, discovering new structures and technologies, and is “nowhere near equilibrium” [00:25:51]. This dynamic, non-equilibrium perspective aligns with the continuous evolution of technology seen throughout history [00:26:18].
Technology as Combinations and Its Evolution
A key insight is that every new technology is a combination of components that already exist [00:30:50]. These components are themselves technologies, and this pattern of combination goes down multiple levels of sub-technologies [00:31:52].
- Expanding “Lego Set”: When a novel technology is created, it can then be used as a building block for even further technologies [00:34:47]. This means the overall collection of technologies constantly expands, like a “chemistry” where new compounds (technologies) are formed and then become new components for future reactions [00:36:36].
Technological Evolution vs. Darwinian Evolution
While there can be small, random variations in technologies, technological evolution differs significantly from biological (Darwinian) evolution because it is largely driven by human purpose or need [00:42:02].
- Jet Engine Example: The jet engine, for instance, did not evolve from piston engines through small variations [00:39:57]. It was invented to solve the problem of flying efficiently in thinner, high-altitude air, leading to a completely different operating principle [00:40:49].
The Nature of Invention
Invention, Arthur argues, is fundamentally a process of problem-solving rather than just mysterious genius [00:45:55]. It involves:
- Identifying a problem or need (e.g., detecting enemy aircraft) [00:46:42].
- Seeking an overall principle or idea to address it (e.g., bouncing high-frequency radio waves off metal objects) [00:48:50].
- Determining concrete ways to realize this principle using existing components [00:48:57].
- Solving numerous sub-problems that arise from these choices, often in an iterative process of trying, backtracking, and discovering new issues [00:49:15]. This requires expertise and familiarity rather than just raw genius [00:51:20].
- Wright Brothers Example: The Wright Brothers, though often seen as solitary inventors, systematically solved critical sub-problems of flight, such as control and lightweight power, by combining existing knowledge and relentless experimentation [00:53:57].
Evolution at Multiple Levels
Technology evolves simultaneously at multiple levels [00:25:51].
- The Automobile: While the car’s external form and basic function haven’t changed drastically in over a century, nearly every internal component has been continuously improved and swapped out [01:05:09].
- Structural Deepening: Technologies undergo “structural deepening,” where simple parts evolve into complex systems (e.g., a simple carburetor to a sophisticated electronic fuel injection system) [01:09:42].
- Modularity and Encapsulation: As subsystems become more common and refined, they become modularized and encapsulated, often making them less accessible to casual repair but more reliable and efficient (e.g., discrete electronic components to integrated circuits) [01:13:07].
- Enabling Future Technologies: This continuous, component-level evolution creates the necessary prerequisites for entirely new capabilities, such as the development of electronic steering and braking systems paving the way for the self-driving car [01:06:43].
Clusters and Domains of Technology
Technologies tend to arrive in clusters or groups, which Arthur calls “domains” [01:15:02]. These domains emerge as different phenomena are understood and harnessed over decades. Examples include:
- Optical Technologies (1600s, with telescopes and microscopes) [00:59:21]
- Chemical Technologies (150 years later, industrial chemicals) [01:15:45]
- Electrical Technologies (1840s onwards, motors, equipment) [01:16:11]
- Electronics (1905-1960s, radios, television, recording devices) [01:17:32]
- Digital Technologies (modern era, blockchain, AI, sensors, big data, telecommunications) [01:22:56]
These clusters don’t just improve existing production; they “sweep across the economy” and enable whole industries to reconfigure their operations [01:18:50]. For example, the advent of computational devices transformed banking, leading to modern computer-based banking [01:21:50]. Similarly, digital technologies are now reshaping healthcare, enabling automated diagnoses and interactive platforms [01:23:45].
Deep Craft
Advanced technology development is not solely driven by scientific knowledge or mathematics. It relies heavily on “deep craft” [01:25:54]. Deep craft refers to the practical knowledge, experience, and intuitive understanding of what works and what doesn’t, often residing within communities of practice [01:28:04].
This “recipe” knowledge includes knowing who to ask, what has been tried in the past, and how to troubleshoot [01:28:10]. It’s akin to cordon bleu cooking or the expertise of master violin makers like Stradivari, combining basic principles with vast experience and the ability to adapt [01:28:46]. This accumulated experience is why certain regions, like Silicon Valley, excel in advanced technology [01:29:31].
Conclusion
The discussion highlights Brian Arthur’s profound insights into the evolution of human intellect and technology, revealing it as a complex, dynamic process driven by purpose, combinations of existing elements, and accumulated practical knowledge. Understanding these dynamics is crucial for anyone navigating our increasingly technological world [01:30:32].