vimothy
yurp
dominic's great posts (and Gavin's criticism of my response) in the A Few Things... thread got me thinking about labour markets and their movements under the conditions of globalisation. The real issue (for developed economies) is at least as much one of jobs lost to technology as globally liberalised competition. In any case it is a fascinating and important subject. Ed Leamer, in his "review" (it's not really a review) of The World Is Flat, identifies a new trend: that technological advancements, in the post-industrial age, will no longer reduce inequality, as they did in the industrial age, but increase it.
The Coming of the Post-Industrial Age
Finally, I want to comment on what I think is the big issue. It isn’t globalization or a flat world; it’s technology and the post- industrial labor markets.
The US is in the midst of a radical transformation from industrial to post-industrial society. Some of this transition is associated with the movement of mundane manufacturing jobs to low-wage foreign locations, but much of it comes from the dramatic changes in technology in the intellectual services sectors. The policy response to the globalization force is pretty straightforward: we need to make the educational and infrastructure investments that are needed to keep the high-paying non-contestable creative jobs here at home and let the rest of the world knock themselves silly competing for the footloose mundane contestable jobs. The response to the technological trends that are altering the nature of the relationship-based jobs is not so clear-cut.
The US transition from an agrarian to an industrial economy that began in the 18th Century was put on hold during the Great Depression but accelerated during both WWI and WWII. Excluding the war years of 1942-45, the transition to an industrial society reached its zenith in the 1950s with 30% of our workforce in manufacturing and 10% in agriculture. The high-growth Kennedy/Johnson expansion of the 1960s kept the jobs in manufacturing at 28%, but the transition to a postindustrial society began in earnest in the 1970s. While jobs in agriculture continued to decline throughout the century, dropping now to only about 1% of our workforce, there has also been a sharp drop in employment in manufacturing in the last three decades, falling in the most recent data (2005) to only 11% of our workforce. The speed of this decline after 1970 from a 28% share to a 11% share in manufacturing is every bit as rapid as the speed in the decline of agricultural jobs in the first seven decades of the 20th Century.
This transition to the post-industrial age has consequences that are at least as profound as the transition from agriculture to industry. This will alter the way wealth is created and all that flows from the “means of production,” including politics and social structures.
Marx and The Transition from Agriculture to Industry
Studies of the transition from agrarian age to industrial age hint at what the next transition might entail. Nathan Rosenberg, Inside the Black Box, page 42, offers a cogent view of technology and production in the industrial age:
Not all tasks can be embodied in equipment
Thus, per Marx, we are what we operate, and what was essential about the industrial age is not what we produced but how we produced it. During the industrial age, Science and Industry collaborated to embody in equipment those tasks that are repetitive, codifiable and programmable, thus freeing the productive process from the caprice of human intervention. Mechanization of work was not limited to manufacturing and occurred also on the farm. But mechanization of services was much more limited. Getting a haircut in 2005 is not much different from getting a haircut in 1850. And having a will drawn up in 1970 was about the same as having a will drawn up in 1900.
The mundane physical tasks that have been left to humans require a degree of dexterity that is difficult (expensive) to achieve with a machine, but year after year advances in Science transfer more and more of these functions to machines. Meanwhile, the economic liberalizations over the last three decades have added to the global workforce an enormous number of workers in Mexico, and Brazil and China and India and so on, offering to do the mundane physical tasks at rates of pay that are barely subsistent. Thus globalization and technology have ganged up after 1970 to rapidly reduce the demand for mundane physical labor in the US.
Most of the innovations of the Industrial age have made very little encroachment on intellectual tasks, mundane or otherwise. An attorney, an architect, a teacher all did about the same work in 1970 as they did in 1800. Absent innovations in production and communication, one might imagine a globalized post-industrial US in which mundane physical tasks like cutting hair would remain only in the local non-traded sector, and the rest of the jobs would be mixtures of mundane- intellectual tasks (clerks), creative-intellectual tasks (designers and researchers and repairmen) and social/organizing/motivating tasks (managers).
But the microprocessor has changed the future of intellectual work, eliminating the mundane-intellectual tasks. Think about an architect. In 1970 the time of a creative architect was partly consumed by the task of rendering the drawings. Some of this work could be done by assistants, but the communication costs were often so high that it made more sense to have the master do the drawings. The personal computer, however, allowed the architect to render the drawings with great efficiency, thus freeing up time to do the creative tasks that the computer cannot ever perform. While for mundane programmable tasks, it is true that “human beings have wills of their own and are therefore too refractory to constitute reliable, that is, controllable inputs in complex and interdependent productive processes,” the opposite is true for creative tasks. It is machines that lack wills of their own and are therefore too obedient to constitute reliable, that is, innovative inputs in complex and interdependent creative processes. Indeed, when I teach data analysis I emphasize the constant struggle between machine and man for control of the process. We data analysts really want to be able to press a button and have the computer do the work, but the creative task of drawing inferences from data always requires a heavy human input, and if, through laziness and seduction, we come to imagine that the computer can think, we will surely be making major misinterpretations of the data. When one starts to lose control and not know if one button on the computer is any different from another, it is wise to shut the computer down and go play a round of golf. The human will be better able to maintain control after a little time off.
Finally, I want to comment on what I think is the big issue. It isn’t globalization or a flat world; it’s technology and the post- industrial labor markets.
The US is in the midst of a radical transformation from industrial to post-industrial society. Some of this transition is associated with the movement of mundane manufacturing jobs to low-wage foreign locations, but much of it comes from the dramatic changes in technology in the intellectual services sectors. The policy response to the globalization force is pretty straightforward: we need to make the educational and infrastructure investments that are needed to keep the high-paying non-contestable creative jobs here at home and let the rest of the world knock themselves silly competing for the footloose mundane contestable jobs. The response to the technological trends that are altering the nature of the relationship-based jobs is not so clear-cut.
The US transition from an agrarian to an industrial economy that began in the 18th Century was put on hold during the Great Depression but accelerated during both WWI and WWII. Excluding the war years of 1942-45, the transition to an industrial society reached its zenith in the 1950s with 30% of our workforce in manufacturing and 10% in agriculture. The high-growth Kennedy/Johnson expansion of the 1960s kept the jobs in manufacturing at 28%, but the transition to a postindustrial society began in earnest in the 1970s. While jobs in agriculture continued to decline throughout the century, dropping now to only about 1% of our workforce, there has also been a sharp drop in employment in manufacturing in the last three decades, falling in the most recent data (2005) to only 11% of our workforce. The speed of this decline after 1970 from a 28% share to a 11% share in manufacturing is every bit as rapid as the speed in the decline of agricultural jobs in the first seven decades of the 20th Century.
This transition to the post-industrial age has consequences that are at least as profound as the transition from agriculture to industry. This will alter the way wealth is created and all that flows from the “means of production,” including politics and social structures.
Marx and The Transition from Agriculture to Industry
Studies of the transition from agrarian age to industrial age hint at what the next transition might entail. Nathan Rosenberg, Inside the Black Box, page 42, offers a cogent view of technology and production in the industrial age:
“Although, therefore, the manufacturing system achieved a growth in productivity through the exploitation of a new and more extensive division of labor, a rigid ceiling to the growth in productivity continued to be imposed by limitations of human strength, speed and accuracy. Marx’s point, indeed, is more general: Science itself can never be extensively applied to the productive process so long as that process continues to be dependent upon forces the behavior of which cannot be predicted and controlled with the strictest accuracy. Science, in other words, must incorporate its principles in impersonal machinery. Such machinery may be relied upon to behave in accordance with scientifically established physical relationships. Science, however, cannot be incorporated into technologies dominated by large-scale human interventions, for human action involves too much that is subjective and capricious. More generally, human beings have wills of their own and are therefore too refractory to constitute reliable, that is, controllable inputs in complex and interdependent productive processes.” (My italics.)
“Relics of by- gone instruments of labor possess the same importance for the investigation of extinct economical forms of society, as do fossil bones for the determination of extinct species of animals. It is not the articles made, but how they are made, and by what instruments, that enables us to distinguish different economical epochs.” Marx, Capital, quoted by Rosenberg, page 40.
“Relics of by- gone instruments of labor possess the same importance for the investigation of extinct economical forms of society, as do fossil bones for the determination of extinct species of animals. It is not the articles made, but how they are made, and by what instruments, that enables us to distinguish different economical epochs.” Marx, Capital, quoted by Rosenberg, page 40.
Not all tasks can be embodied in equipment
Thus, per Marx, we are what we operate, and what was essential about the industrial age is not what we produced but how we produced it. During the industrial age, Science and Industry collaborated to embody in equipment those tasks that are repetitive, codifiable and programmable, thus freeing the productive process from the caprice of human intervention. Mechanization of work was not limited to manufacturing and occurred also on the farm. But mechanization of services was much more limited. Getting a haircut in 2005 is not much different from getting a haircut in 1850. And having a will drawn up in 1970 was about the same as having a will drawn up in 1900.
The mundane physical tasks that have been left to humans require a degree of dexterity that is difficult (expensive) to achieve with a machine, but year after year advances in Science transfer more and more of these functions to machines. Meanwhile, the economic liberalizations over the last three decades have added to the global workforce an enormous number of workers in Mexico, and Brazil and China and India and so on, offering to do the mundane physical tasks at rates of pay that are barely subsistent. Thus globalization and technology have ganged up after 1970 to rapidly reduce the demand for mundane physical labor in the US.
Most of the innovations of the Industrial age have made very little encroachment on intellectual tasks, mundane or otherwise. An attorney, an architect, a teacher all did about the same work in 1970 as they did in 1800. Absent innovations in production and communication, one might imagine a globalized post-industrial US in which mundane physical tasks like cutting hair would remain only in the local non-traded sector, and the rest of the jobs would be mixtures of mundane- intellectual tasks (clerks), creative-intellectual tasks (designers and researchers and repairmen) and social/organizing/motivating tasks (managers).
But the microprocessor has changed the future of intellectual work, eliminating the mundane-intellectual tasks. Think about an architect. In 1970 the time of a creative architect was partly consumed by the task of rendering the drawings. Some of this work could be done by assistants, but the communication costs were often so high that it made more sense to have the master do the drawings. The personal computer, however, allowed the architect to render the drawings with great efficiency, thus freeing up time to do the creative tasks that the computer cannot ever perform. While for mundane programmable tasks, it is true that “human beings have wills of their own and are therefore too refractory to constitute reliable, that is, controllable inputs in complex and interdependent productive processes,” the opposite is true for creative tasks. It is machines that lack wills of their own and are therefore too obedient to constitute reliable, that is, innovative inputs in complex and interdependent creative processes. Indeed, when I teach data analysis I emphasize the constant struggle between machine and man for control of the process. We data analysts really want to be able to press a button and have the computer do the work, but the creative task of drawing inferences from data always requires a heavy human input, and if, through laziness and seduction, we come to imagine that the computer can think, we will surely be making major misinterpretations of the data. When one starts to lose control and not know if one button on the computer is any different from another, it is wise to shut the computer down and go play a round of golf. The human will be better able to maintain control after a little time off.
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