Is Artificial Intelligence Really the Next Technological Revolution?
A comparison of AI with previous technological breakthroughs
There’s no shortage of hype around artificial intelligence. Fueled by recent scientific advances in the field, AI is now characterized as the “new electricity”—a technological breakthrough that will revolutionize the world.
But are we sure that’s the case?
Many booms and busts have punctuated AI’s nearly half century of history. Excessive expectations and promises, which drove the first AI bubble in the 1980s, have been followed by decreased funding and interest — the so-called “AI winters.” But this time feels different. Five billion in venture capital was funneled into AI last year. Coupled with recent acquisitions of AI startups by tech companies such as Facebook, Google, and Apple, and the exploding interest by other companies — reflected in the skyrocketing mentions of AI in company earnings calls — it seems rather obvious that AI is here to stay.
But is AI indeed the next major technological revolution? Is there a generic structure of technological revolutions that can be identified historically? If so, can the insights of previous technological revolutions be applied to AI? And if AI represents a major technological breakthrough that is comparable to electricity and steam, in which phase of its development do we currently find ourselves?
In her work on the economics of innovation and technological change, socio-economist Carlota Perez has traced the discontinuities and regularities in the process of innovation. Similarly to Thomas Kuhn’s work on the nature of scientific discoveries — in which scientific revolutions disrupt the process of science and trigger the formation of new scientific paradigms — Perez identifies a sequence of technological revolutions and “techno-economic paradigms” that have disrupted our industries and societies.
A technological revolution — which locally disrupts a specific market or industry in terms of new inputs, methods, and technologies — becomes a techno-economic paradigm when it starts to globally transform organizational structures, business models, and strategies in markets and sectors beyond which the technological breakthrough had initially erupted. Techno-economic paradigms, in other words, represent a collectively shared best practice model of the most successful and profitable uses of the new innovations. By enabling the wide-spread diffusion and adoption of the emerging technologies across economies and societies, techno-economic paradigms will fundamentally affect our socio-institutional frameworks.
As Perez has shown, two distinct phases can be identified in each technological revolution. There is an “installation” phase, in which innovators and entrepreneurs explore the potential of the new technology. In this phase, the diffusion of a breakthrough technology is often driven by a financial bubble. The installation phase is followed by a “turning point” or phase of readjustment — in which the bubble bursts — and the “deployment” period, which diffuses the new technological system across industries, economies, and societies.
Each technological revolution can be characterized further in terms of a specific life cycle, which, as Perez documents, tends to last around half a century (see image 1). Perez identifies four distinct phases within such a life cycle: an initial period, which is characterized by explosive growth and innovations and new products; a phase of constellation, in which new industries, infrastructures, and technology systems are built out; the full expansion of innovation; and the last phase, which is defined by technological maturity and market saturation.
Perez defines a technological revolution as a set of interrelated radical breakthroughs — that is, singular innovations — that form a constellation of interdependent technologies. A technological revolution, in other words, is a cluster of clusters, or a system of systems of technological innovations. The recent major breakthrough in information technology, for example, formed such a technology system around microprocessors and other integrated semiconductors, from which new technological trajectories opened up: personal computers, software, telecommunication, and the internet emerged from the initial technological system. These new technological systems subsequently created strong inter-dependence and feedbacks between technologies and markets. The defining features of technological revolutions — as opposed to a random collection of singular innovations — are thus the following: (1) they are interconnected and interdependent in their technologies and markets, and; (2) they have the disruptive potential to radically transform the rest of the economy and society.
Historically, Perez identifies five such major technological meta-systems, which were initially triggered by a technological (or scientific) breakthrough and, then, expanded across industries and economies. The first such disruption of the late 18th century was organized around the mechanization of factories, water power, and the canal networks. This was followed by the second revolution, which initiated the age of steam and railways. In the late 19th century, electricity, steel, and heavy engineering intensified international trade and globalization. In the last century, two technological revolutions transformed our economic and industrial system: the age of oil, mass production and the automobile was followed by the era of information and communication technology.
What made these technological disruptions revolutionary were not only the new interrelated technologies, industries, and infrastructures but their transformative potential defined in terms of extraordinary increases in productivity that they enabled. When a technological revolution propagates across industries and economies, it radically transforms the cost structure of production by providing new powerful inputs (such as steel, oil, or microelectronics). Thereby, it unleashes new innovations and interrelated technological systems, which renew existing industries and create new ones.
Perez provides a powerful framework that can be applied to the current state of AI. Given Perez’ conceptual model of the diffusion of technological innovations, the new AI industries and systems that are forming now can be located between phase one, the period of “paradigm configuration,” and the phase of “full constellation,” in which new industries emerge and infrastructures get installed. The explosive growth and innovation we are experiencing at the moment typically characterizes phase one. While new industries, technological systems, and infrastructures emerge in phase two — which results in intensified investment and market growth — the technological revolution is transforming its core industries, but has not yet permeated economies and societies as a whole.
While the recent extraordinary investments in AI might lead to another bubble — which might indicate the “turning point” or phase of readjustment in Perez’ model — it seems that the economic space today is, indeed, different than during the last AI bubble (or, perhaps, the bursting of the first AI bubble in the 1980s already marked the “turning point” — over-inflated expectations crashed when cheap UNIX workstations triggered the fall of over-priced expert systems running on LISP and the Dreyfus brothers published their Mind over Machine, which undermined some of the pretentious and flawed assumptions of the first generation of AI research). Not only has there been massive growth in computation, GPUs, storage, datasets, user demand, high levels of R&D, and VC investment, but governments have also started novel AI initiatives. The UK government recently announced increased funding for AI research; the Chinese government gave AI priority status in R&D and commercialization; and the US government has funded AI research last year with more than $1 billion.
The role of public R&D is singularly important for technological revolutions as the previous five major technological surges have all been, to some extent, government-sponsored (such as the canals and railways networks, or the Internet, which has been heavily funded by government agencies such as DARPA). Historically, the synergistic financing of governments and financial capital, such as venture capital, has been crucial for the diffusion and adoption of technological breakthroughs and their consolidation into techno-economic paradigms.
But in what sense, then, does AI share the features of the previous technological revolutions that can be historically identified? The emerging AI technology systems clearly exhibit the interconnectedness and interdependence in their technologies and markets, which characterize the previous technological revolutions. AI represents not just another new dynamic industry that is added to the existing production structure; rather it provides the means to modernize almost all existing industries and activities. New AI-powered industries and infrastructures are forming at the moment that not only fundamentally re-organize existing industries, but have started to deeply affect organizational structures, business models, and strategies. As it was the case with steam and electricity, these technological and scientific breakthroughs are not only productivity-enhancing in the core industries but are beginning to permeate various peripheral sectors and markets.
In this sense, AI has all the features of what economists call a general purpose technology (GPT). In economics, a GPT is defined as a generic technology, which (1) can be improved, (2) can be widely used and applied, and (3) expands the space of possible innovations and investments. Similar to historical GPTs, such as the steam engine, electricity, or microelectronics, these new interconnected and interdependent AI-based technology systems and markets have not only the potential to enable innovations in products, processes, and organizational structures — as previous GPTs did — but also to radically transform our economic, social, political structures.
AI has all the defining features of previous technological revolutions — it is becoming a cluster of interrelated generic technologies and organizing principles that are starting to spread far beyond the confines of a specific industry. At the core of all the previous technological revolutions has been an all-pervasive low-cost input, often a new material or energy source combined with novel products, processes, and infrastructures. Similar to electricity, steam, or microelectronics, AI — fueled by GPU-accelerated computing, massive increases in available data, and drastically reduced costs — seems to be on the cusp of becoming such a cheap and ubiquitous new input. Similar to steam in the 18th century or electricity today, distributed AI could soon power almost all products and processes and deeply permeate existing and novel infrastructures and industries.
Indeed, AI could become the “new electricity.” We are not there yet. But given Perez’ model of diffusion and adoption of technological innovation, we may indeed be at the cusp of a revolution.