⚡ The dynamo, the computer, and ChatGPT: Explaining today's productivity paradox
Also: 5 Quick Questions for … R&D policy expert Matt Hourihan
In This Issue
The Essay: The dynamo, the computer, and ChatGPT
5QQ: 5 Quick Questions for … R&D policy expert Matt Hourihan
Micro Reads: CRISPR, small modular nuclear, a new environmentalism, and more …
Quote of the Issue
“You can see the computer age everywhere but in the productivity statistics.”
⚡ The dynamo, the computer, and ChatGPT
To play off the famous quote (above) by economist Robert Solow: You can see the age of AI/machine learning everywhere but in the productivity statistics. At least so far. And that’s an important observation because productivity growth is just about the whole ballgame as far as making us richer. At some point, scientific discovery and technological innovation need to broadly and deeply affect how we live and work.
For example: Computers, from mainframes to PCs, were hardly uncommon in the 1980s, along with software for spreadsheets and word processing. But the New Economy that Solow paradoxically didn’t yet see in 1987 was awaiting difference-making innovations — and the continuation of Moore’s Law — that built upon the computer: the internet, web, and e-commerce. Meanwhile, businesses and their workers needed to learn how to best use all this new technology. Because of that required learning and investment with important innovations, it may even seem like the innovation hurts productivity growth (at first) since new investment isn’t boosting output.
Which brings us to the passing of Stanford University economist Paul David, who died last week at age 87. His work on technological diffusion is the aspect of his scholarship that first came to my attention, specifically his much-cited 1990 analysis, “The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox.” In the short article, David attempts to explain what became known as the Solow Paradox via historical analogy: the spread of electrification throughout the economy and society from the late 1800s through the early 1900s. Although the lightbulb was invented in 1879 and patented in 1880, only 3 percent of all residences used electric lighting by the turn of the century, while electric motors accounted for less than 5 percent of factory mechanical drive. David:
It may be remarked that, in 1900, an observer of the progress of the “Electrical Age” stood as far distant in time from the carbon filament incandescent lamp by Edison and Swann (1879), and of the Edison Central generating station in New York and London (1881), as we stand today from comparable “breakthrough” events in the computer revolution: the introduction of the 1043 byte memory chip (1969) and the silicon microprocessor (1970) by Intel.
It would take until the 1920s for those measures of diffusion for lighting and motors to hit 50 percent and have an impact on productivity growth. What took so long? David:
The proximate source of the delay in the exploitation of the productivity improvements potential incipient in the dynamo revolution was, in large part, the slow pace of factory electrification. The latter, in turn, was attributable to the unprofitability of replacing still serviceable manufacturing plants embodying production technologies adapted to the old regime of mechanical power derived from water and steam.
At first, factories didn’t change much to accommodate electric motors. Owners kept the existing centralized mechanical power system and replaced the steam engine with a dynamo. But in the 1920s, factories started adopting the “unit drive” approach where individual electric motors powered each piece of equipment. As economist Hal Varian has noted, the benefits included greater energy efficiency as well as “the ability to build lighter, and more modular, single story factories using this new technology.” Learning how to optimize electric motors usage and factory floorplans took time. David:
Although all this was clear enough in principle, the relevant point is that its implementation on a wide scale required working out the details in the context of many kinds of new industrial facilities, in many different locales, thereby building up a cadre of experienced factory architects and electrical engineers familiar with the new approach to manufacturing.
The relevancy of this historical analogy became obvious as the 1990s productivity boom began to emerge. David looked prescient. Indeed, his observation continues to inform today’s analysis of technological change.
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