Precarity and Artificial Intelligence: Review of Objective Functions, and A Contrarian Perspective

This post is a continuation of my series of posts on economic precarity.  As I mentioned in recent posts in this series, we have been exploring the subject of the educated precariat - that is, those people in the early 21st century who have obtained either bachelors or more advanced graduate degrees from a college or university, yet who cannot find stable work in their chosen profession.  However, the most recent previous post in this series began to explore the impact of machine artificial intelligence (AI) on the future of all work, whether that work requires advanced education or not.  

In my my most recent post in this series, I wrote that the greatest potential for the disruption of the future of work through machine AI lies in the development of machine AI tools that can tackle the increasingly complex  tasks that are normally associated with human (or at least highly developed animal) intelligence.  Such tasks include machine vision (including recognizing a human face or an animal), natural language processing, construction of buildings, navigating physically complex unstructured and random environments (such as forests), and optimization of problems with multiple objectives requiring multiple objective functions to model.  Today I'd like to amend that statement by saying that there is another potentially massive disruptive impact of machine AI on the future of work, namely, the ways in which the wide deployment of machine AI in a society might condition and change the humans in that society.  I'll have more to say on that subject in another post.  What I'd like to do right now is to take another look at mathematical objective functions and their place in the implementation of machine AI.  But even before that, let's review the two main types of applications we are talking about when we talk about "machine AI".  Also, let me warn you that today's post will move rather deep into geek territory.  I'll try to have some mercy.

As I mentioned in the most recent post in this series, AI applications can be broken down into two main categories.  The first category consists of the automation of repetitive or mundane tasks or processes in order to ensure that these processes take place at the proper rate and speed and thus yield the appropriate steady-state or final outcome.  This sort of AI has been around for a very long time and first came into existence in entirely mechanical systems such as steam engines with mechanical governors that regulated the speed of the engines.  An example of a mid-20th century electromechanical control system is the autopilot with mechanical gyroscopes and accelerometers and simple electronic computers which was invented to guide airliners and early guided missiles during long-distance flights.  Other early electronic examples include the programmable logic controllers (PLC's) which were developed in the 1960's to regulate assembly line processes in industrial plants.  In his 2022 paper titled "The two kinds of artificial intelligence, or how not to confuse objects and subjects," Cambridge Professor Alan F. Blackwell characterizes these systems as servomechanisms, which Merriam-Webster defines as "an automatic device for controlling large amounts of power by means of very small amounts of power and automatically correcting the performance of a mechanism" and which Blackwell himself defines as "...any kind of device that 'observes' the world in some way, 'acts' on the world, and can 'decide' to 'behave' in different ways as determined by what it observes."  

The construction (and hence performance) of servomechanisms can be increasingly complex as the number and type of processes regulated by the servomechanisms increases, but that does not mean that the servomechanisms possess any real native intelligence.  Consider, for instance, a very simple servomechanism such as the thermostat from a heating system in a house built during the 1950's.  Such a thermostat would regulate the timing and duration of the burning of a fuel in a heating furnace, and would most likely consist of a simple switch with a movable switch contact and a stationary contact with the movable contact attached to a bimetallic strip.  Because the shape of the bimetallic strip is regulated by the temperature of the air, when the air temperature drops, the movable switch contact eventually touches the stationary contact, closing the switch and turning on the flow of fuel to the furnace.  We can say that the thermostat "decides" when the furnace turns on or off, but that's all this thermostat can "decide" to do.  You certainly wouldn't want to rely on the thermostat to help you decide what movie to watch with your spouse on a weekend!  Servomechanisms are what Blackwell calls "objective AI" which "measures the world, acts according to some mathematical principles, and may indeed be very complex, even unpredictable, but there is no point at which it needs to be considered a subjective intelligent agent."  In other words, all a servomechanism can do is to mechanically or electronically regulate a physical process on the basis of process measurements provided to the controller by means of physical sensors that sense a process variable.  It can't think like humans do.

The second type of AI is designed to make value judgments about the world in order to predict how the world (or some small subset of the world) will evolve.  In the most optimistic cases, this AI uses these value judgments to generate the most appropriate response to the world which is supposedly evolving according to prediction.  But is this really a native intelligence created by humans, yet now embodied in a machine and existing independently of humans?  A possible answer to that question can be found in another paper written by Blackwell and published in 2019, titled, "Objective functions: (In)humanity and inequity in artificial intelligence."

The value judgments and predictions made by the second type of AI are made by means of objective functions. These objective functions are mathematical abstractions consisting of functions of several independent variables.  Each of the independent variables represents an independently controllable parameter of the problem.  If the purpose of the objective function is to predict the numerical value of an outcome based on historical values of independent input variables, then optimizing the function means making sure that for a given set of historical inputs, the objective function yields an output value that is as close as possible to the historical outcome associated with the particular historical inputs. This ensures that for any set of future possible inputs, the objective function will accurately predict the value of the output.  Two levels of objective functions are needed: the first level, which makes a guess of the value of an output based on certain values of inputs, then a second supervisory level which evaluates how close each guess is to a set of historical output values based on corresponding sets of input values.  The output of this second supervisory objective function is used to adjust the weights (in the case of a polynomial function, the coefficients) of the primary objective function in order to produce better guesses of the output value. 

Objective functions are mathematical expressions; hence, the second type of AI is a primarily mathematical problem which just happens to be solved by means of digital computers.  This also includes the implementation of multi-objective optimization, which is really just another mathematical problem even though it is implemented by machines.  Thus, the second type of AI is really just another expression of human intelligence.  This is seen not only in the development of the objective functions themselves, but also in the training of the supervisory objective function to recognize how close the output of the primary objective function is to the a value that actually reflects reality.  This training takes place by several means, including supervised learning (in which humans label all the training data), and partially-supervised and unsupervised learning (in which the training data is out there, but instead of it being labeled, a human still has to create the algorithms by which the machine processes the training data).  

An example that illustrates what we have been considering is the development of large language models (LLM's) such as ChatGPT which predict text strings based on inputs by a human being.  A very, very, very simple model for these AI implementations is that they consist of objective functions that guess the probability of the next word, phrase, sentence, or paragraph in a string on the basis of what a human has typed into an interface.  These AI implementations must be trained using data input by human beings so that they can calibrate their objective functions to reduce the likelihood of wrong guesses.  Cases like these lead scientists such as Alan Blackwell to conclude that the second type of AI is not really a separate "intelligence" per se, but rather the embodiment and disguising of what is actually human intelligence, reflected back to humans through the intermediary of machines.  The calibration of the objective functions of these AI deployments (or, if you will, the training of this AI) is performed by you every time you type a text message on your smartphone.  For instance, you start by typing "Hello Jo [the phone suggests "Jo", "John", "Joe", but the person you're texting is actually named "Joshiro", so as you type, your phone keeps making wrong guesses like "Josh", "Joshua", and "Josh's" but you keep typing until you've finished "Joshiro"]. You continue with "I'm at the gym right now, but I forgot my judo white belt [the phone guesses almost everything even though you misspelled "at" as "st" and the phone auto-corrected.  However, the phone chokes when you start typing "judo" so you have to manually type that yourself].  You finish with "Can you grab it out of my closet?"  The next time you text anyone whose first name starts with the letters "Jo", your phone will be "trained" to think you are texting Joshiro about something related to judo - or more accurately, the generative LLM in your phone will have determined that there is a statistically higher likelihood that your message will contain the words "Joshiro" and "judo".  Your phone's LLM is thus "trained" every time you correct one of its wrong guesses when you type a text.

Of course, the longer the predicted phrase or sentence or paragraph the AI is supposed to return, the more training data is required.  The boast of the developers of large language models and other similar AI implementations is that given enough training data and a sufficiently complex statistical objective function, they can develop AI that can accurately return the correct response to any human input.  This unfortunately leads to an unavoidable conclusion of the second type of AI: the assumption that the universe, reality, and life itself are all deterministic (thus there is no free will in the universe).  Why? Because the kind of intelligence that can accurately predict how the universe and everything in it will evolve and thus generate the most appropriate local response to the moment-by-moment evolution of your particular corner of the universe can always be modeled by an appropriately elaborate statistical objective function trained on an appropriately huge set of training data.  In other words, given enough data, a statistical objective function can be derived which accurately predicts that your spouse's sneeze at the dinner table tonight will provoke an argument which ends with you sleeping on the couch tomorrow night, and that this will lead to the invention of a new technology later in the week that causes the stock market of a certain country to crash, with the result that a baby will cry on a dark and stormy night five days from now, and that this cry will enable a computer to predict all the words that will be in the novel you sit down to write a week from today...  This is my rather facetious illustration of the "generative AI" of chatGPT and similar inventions.  The fallacy of determinism is that life, the Universe, and reality itself are full of phenomena and problems that can't easily be modeled by mathematics.  Scientists call them "wicked problems."  Thus the claims made about the second kind of AI may be overblown - especially as long as the implementation of this second kind of AI remains primarily dependent on the construction and optimization of appropriately complex statistical objective functions.

Yet it can't be denied that the second type of AI is causing some profound changes to the world in which we live, and even the first type of AI - the implementation of servomechanisms, or the science of cybernetics - has had a profound effect.  The effects of both types of AI to date - especially on the world of work - will be the subject of the next post in this series.

P.S. Although I am a technical professional with a baccalaureate and a master's degree in a STEM discipline, I am most definitely NOT an AI expert.  Feel free to take what I have written with a grain of salt - YMMV. 

P.P.S. For more commentary on ChatGPT and other LLM's, feel free to check out a 2021 paper titled, "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" by Emily Bender and others.  The authors of this paper were Google engineers who were fired by Google for saying things that their bosses didn't want to hear regarding LLM's.   Oh, the potential dangers of writing things that give people in power a case of heartburn...

 

Precarity and Artificial Intelligence: The Foundations of Modern AI

This post is a continuation of my series of posts on economic precarity.  As I mentioned in recent posts in this series, we have been exploring the subject of the educated precariat - that is, those people in the early 21st century who have obtained either bachelors or more advanced graduate degrees from a college or university, yet who cannot find stable work in their chosen profession.  Today's post, however, will begin to explore a particular emerging impact to employment for everyone, whether formally educated or not.  That impact is the impact of machine artificial intelligence on the future of work.

As I mentioned in a previous post, 

Labor casualization has been part of a larger tactical aim to reduce labor costs by reducing the number of laborers...This reduction of the total number of laborers can be achieved by replacing employees with machines.  That replacement has been occurring from the beginning of the Industrial Revolution onward, but in the last two or three decades it has accelerated greatly due to advances in artificial intelligence (AI).  A long-standing motive behind the recent massive investments in research in artificial intelligence is the desire by many of the world's richest people to eliminate the costs of relying on humans by replacing human laborers with automation.

So it is natural to ask what sort of world is emerging as the result of the use of increasingly sophisticated AI in our present economy.  Here we need to be careful, due to the number of shrill voices shouting either wildly positive or frighteningly negative predictions about the likely impacts of AI.  I think we need to ask the following questions:

• First, what exactly is artificial machine intelligence?  What is the theoretical basis of AI?  How does it work? ...

Today we'll start trying to answer the questions stated above.   And at the outset, I must state clearly that I am not an AI expert, although my technical education has exposed me in a rudimentary way to many of the concepts that will be mentioned in our discussion of AI.

First, let's paint a picture.  One of the original motives for trying to invent intelligent machines was the desire for machines that would reliably do the kind of mundane tasks that humans find to be distasteful or unpleasantly difficult.  This desire actually has a very long history, but was popularized in the science fiction of the mid-20th century.  Think of a kid from the 1950's or 1960's who wished he had a robot that could vacuum the living room carpet or take out the garbage or do homework or shovel snow out of the driveway so that the kid could play without being bothered by parents demanding that the kid himself do the tasks listed above.  What kind of "brain" would the robot need in order to know what tasks needed to be performed and when would that brain know the tasks had been performed to acceptable standards?

The question of the kind of "brain" required was solved by the invention of the first programmable all-electronic digital computer during World War Two.  This computer was itself an evolution of principles implemented in previous mechanical and electromechanical computers.  Once engineers developed digital computers with onboard memory storage, these computers became capable of automation of tasks that had been formerly automated by more crude mechanical and electromechanical means such as relays.  Thus the 1950's saw the emergence of digital control systems for automation of chemical processes at refineries; the 1950's and 1960's saw the emergence of computer-assisted or computer-based navigation for ships, aircraft, missiles, and spacecraft; and the late 1960's saw the emergence of programmable logic controllers (PLC's) for automation of factory processes at industrial assembly plants.

The digital electronic automation systems that have been developed from the 1950's onward have thus formed a key component of the development of modern machine AI.  But another key component consists of the principles by which these systems achieve their particular objectives.  These principles are the principles of mathematical optimization, and they also have a rather long history.

Mathematical optimization is the collection of techniques and methods for finding the maximum or minimum value of a mathematical function of one or more independent variables.  Some of the earliest methods of mathematical optimization were based on calculus.  More complex methods include such things as numerical methods for solving nonlinear differential equations.  These methods were only possible to implement easily once electronic digital computers became available.

The first step in optimizing real-world problems consists of turning a real-world problem into a mathematical abstraction consisting of a function of several independent variables.  Each of the independent variables represents an independently controllable parameter of the problem.  Then optimization techniques are used to find the desired maximum or minimum value of the function.  To put it another way,

"Optimization is the act of obtaining the best result under given circumstances.  In design, construction, and maintenance of any engineering system, engineers have to take (sic) many...decisions.  The ultimate goal of all such decisions is either to minimize the effort required or to maximize the desired benefit.  Since the effort required or the benefit desired in any practical situation can be expressed as a function of certain decision variables, optimization can be defined as the process of finding the conditions that give the maximum or minimum value of a function."  - Engineering Optimization: Theory and Practice, Rao, John Wiley and Sons, Inc., 2009

The function to be optimized is called the objective function.  When we optimize the objective function, we are also interested in finding those values of the independent variables which produce the desired function maximum or minimum value.  These values represent the amount of various inputs required to get the desired optimum output from a situation represented by the objective function.  

A simple case of optimization would be figuring out how to catch up with a separate moving object in the shortest amount of time if you started from an arbitrary starting position.  To use optimization techniques, you'd turn this problem into an objective function and then use calculus to find the minimum value of the objective function.  Since the velocity and acceleration are the independent variables of interest, you'd want to know the precise values of these (in both magnitude and direction) which would minimize the value of the objective function.  Note that for simple trajectories or paths of only two dimensions, adult humans tend to be able to do this automatically and intuitively - but young kids, not so much.  Try playing tag with a five or six-year-old kid, and you will see what I mean.  The kid won't be able to grasp your acceleration from observing you, so he will run to where he sees you are at the moment he sees you instead of anticipating where you'll end up.  Of course, once kids get to the age of ten or so, they're more than likely to catch you in any game of tag if you yourself are very much older than 30!

The easiest AI problems are those that can most easily be turned into mathematically precise objective functions with only one output variable.  Examples of such problems include the following: reliably hitting a target with a missile, winning a board game in the smallest number of moves, traveling reliably between planets, simple linear regression, regulating the speed or rate of industrial or chemical processes, and control of HVAC and power systems in buildings in order to optimize interior climate, lighting, and comfort.

Harder AI problems include machine vision (including recognizing a human face or an animal), natural language processing, construction of buildings, navigating physically complex unstructured and random environments (such as forests), and optimization of problems with multiple objectives requiring multiple objective functions to model.  The machine vision and natural language processing problems are harder because they require the use of logistical regression functions as objective functions, and in order to accurately assign the appropriate "weights" to each of the variables of these objective functions, the AI which implements these functions needs massive amounts of training data.  However, these and other harder problems are now being solved with increasing effectiveness through technologies such as deep learning and other advanced techniques of machine learning.  It is in the tackling of these harder problems that AI has the greatest potential to disrupt the future of work, especially of cognitively demanding work that formerly only humans could do.  In order to assess the potential magnitude and likelihood of this disruption, we will need to examine the following factors:

• The current state of the art of machine learning
• The current state of the art of designing objective functions
• And the current state of the art of multi-objective mathematical optimization.

I'll try tackling these questions in the next post in this series.

Introducing the Main Street Alliance

I'd like to take this opportunity to introduce readers to the Main Street Alliance, an organization which seeks to foster the creation and growth of small businesses in the United States.  As I resume my series of posts on the problem of economic precarity, I will also discuss solutions.  As I mentioned in a previous post, I believe that the eradication of the monopoly power of the rich and the fostering of small business among the poor are two strategic efforts which can reduce or eliminate economic precarity in the United States.  This is what the Main Street Alliance is working to achieve.

Those who read about the activities of the Main Street Alliance will also learn about how the rich and the powerful in the United States are trying to destroy small businesses, especially those run by minorities, and how these bad actors are using Republican-appointed Federal court justices in their attacks against small business.  This should be of great concern to those of you who are small entrepreneurs.  The latest attack against small business consists of judicial challenges to the Federal tax code.  Readers of this blog can learn from the Main Street Alliance website how they can join in the fight to foster and protect small business.

Precarity, Late Capitalism, And Artificial Intelligence: Pinocchio's Mischief

This post is a continuation of my series of posts on economic precarity.  As I mentioned in recent posts in this series, we have been exploring the subject of the educated precariat - that is, those people in the early 21st century who have obtained either bachelors or more advanced graduate degrees from a college or university, yet who cannot find stable work in their chosen profession.  The two most recent previous posts in this series discussed the fact that there are now more college graduates being produced in our society than there are jobs into which to plug those graduates.  The most recent post discussed why this is the case.  As I wrote last week, 

"...the decline in opportunities for college graduates (along with everyone else) is correlated with the rise in the concentration of economic power in the hands of an ever-shrinking elite.  In fact, I will go even farther and assert that the decline in stable employment for college graduates (even those with technical professional degrees) is a direct outcome of the concentration of economic power at the top of society.

Consider the fact that as of 2015, "America's 20 wealthiest people - a group that could fit comfortably in one single Gulfstream G650 luxury jet - now own more wealth than the bottom half of the American population combined..."  These people therefore have an enormous amount of economic and political clout.  And they have used (and continue to use) that clout in order to turn the American economy into a machine whose sole function is to make them as rich as possible.  The increase in precarity, the casualization of increasing types of employment, and the increasing use of task automation and artificial intelligence are typical of the strategies which these wealthy and powerful people have deployed in order to maximize the wealth they can extract from the American economy while minimizing the amount of wealth they give to the rest of us.  The aggressive expansion of the "gig" economy is another such strategy..."

A basic strategic aim in capitalism is that business owners should maximize profit.  A basic tactic for the achievement of this aim is to maximize profit per unit of goods sold by lowering the cost of production for each unit of goods sold.  Lowering costs can be achieved by attacking the cost of materials, capital machinery, energy, and labor.  In the limit, at the extreme of optimization, this leads to extremely flimsy goods sold for extremely high prices, goods that are produced by extremely poor laborers.

The labor part of this tactic is what we have been discussing in our consideration of precarity.  By making employment casual and temporary, with no fixed covenant between businesses and laborers and no benefits (other than a wage) granted to laborers, businesses have succeeded in driving down the cost of labor.  As mentioned in last week's post, that pressure on labor costs has reached even technical professions requiring a baccalaureate degree or above.  This is leading to an increasingly unsustainable situation in which, for instance, you might spend more than $40,000 to earn a four-year engineering degree - only to find yourself working for an engineering temp agency after graduation!

Labor casualization has been part of a larger tactical aim to reduce labor costs by reducing the number of laborers.  If you're the CEO of a large company, the progression of this tactic can be sketched as follows: First, destroy any expectation of stable employment or decent wages among your labor pool.  Then, reduce the actual number of laborers you use.  This reduction of the total number of laborers can occur by a number of means (including working employees to death by giving each employee the amount of work that should normally be handled by two or three such employees).  It can of course also be achieved by replacing employees with machines.  That replacement has been occurring from the beginning of the Industrial Revolution onward, but in the last two or three decades it has accelerated greatly due to advances in artificial intelligence (AI).  A long-standing motive behind the recent massive investments in research in artificial intelligence is the desire by many of the world's richest people to eliminate the costs of relying on humans by replacing human laborers with automation.

So it is natural to ask what sort of world is emerging as the result of the use of increasingly sophisticated AI in our present economy.  Here we need to be careful, due to the number of shrill voices shouting either wildly positive or frighteningly negative predictions about the likely impacts of AI.  I think we need to ask the following questions:

• First, what exactly is artificial machine intelligence?  What is the theoretical basis of AI?  How does it work?
• What can AI do and not do?
• What countries are at the forefront of AI deployment in their societies?
• How will AI capabilities likely evolve over the next few decades?
• What effects might AI have on human life and human societies over the next few decades?
• How will AI affect the world of work over the next few decades?

The next few posts in this series will attempt to tackle these questions.  I must warn you that what you'll get in those posts are merely my guesses at an answer.  However, because I want the guesses to be educated guesses, I'm going to need to do some research.  So these guesses might be slow in coming.

The Educated Precariat: Why The Mismatch?

This post is a continuation of my series of posts on economic precarity.  As I mentioned in recent posts in this series, we have been exploring the subject of the educated precariat - that is, those people in the early 21st century who have obtained either bachelors or more advanced graduate degrees from a college or university, yet who cannot find stable work in their chosen profession.  The most recent previous post in this series discussed the university system as a machine that produces graduates for use within the larger machinery of modern late-stage capitalism, and what is happening to those graduates because of the fact that there are more graduates being produced than there are jobs into which to plug those graduates.

That previous post highlighted the fact that from at least the 1990's onward (and possibly starting from the 1970's onward), there has been a growing number of college graduates who have found themselves underemployed after graduation.  Moreover, as time has passed, the number of college graduates who have entered long-term underemployment after graduation has increased as a percentage of total college graduates.  Note that to be underemployed as a college graduate means to hold a job that does not require the knowledge, skills, and abilities that a person would acquire as part of a college education.  As a hypothetical example, think of a gas station cashier with a recent baccalaureate degree in organizational psychology.  Moreover, the sources cited in that post listed the types of college major most likely to lead to underemployment and precarious work.  From those sources it would seem that baccalaureate degrees in STEM (science, technology, engineering, and mathematics) offer the greatest likelihood of full employment and decent wages.  However, note that a 2018 Canadian study titled, "No Safe Harbour: Precarious Work and Economic Insecurity Among Skilled Professionals in Canada" cited the fact that a technical professional degree is no longer an ironclad guarantee against precarious employment.  

Why then is there such a huge mismatch between the number of people obtaining degrees and the number of available jobs which would utilize the skills implied by these degrees while paying the degree holders a decent living wage?  That is the question which today's post will try to answer.  

First, let's consider the answer offered by people like Peter Turchin, the well-fed Russian emigre to the United States whom I mentioned in another post in this series on precarity.  Turchin asserts that the supposed "excess" of college graduates, the supposed "mismatch" between the number of college graduates and the number of appropriate jobs for these graduates, is the result of an imbalance between the higher education sector and the rest of the economy.  He also asserts that the "excess" of college graduates is increasing the likelihood of instability in society caused by the radicalization of these "excess" graduates.  To put it in the language of Wikipedia, 

"Elite overproduction is a concept developed by Peter Turchin, which describes the condition of a society which is producing too many potential elite members relative to its ability to absorb them into the power structure. This, he hypothesizes, is a cause for social instability, as those left out of power feel aggrieved by their relatively low socioeconomic status." [Emphasis added.]

Note the first sentence and its mention of the capacity of a society to absorb newly educated citizens into an existing power structure.  I will return to the notion of existing power structures later in this post.  Note also that Turchin's "solution" to this problem of "overproduction" is to limit access to higher education.  This "solution" is remarkably similar to the "solution" proposed by Richard Vedder, Christopher Denhart, and Jonathan Robe in their 2013 report titled, "Why Are Recent College Graduates Underemployed? University Enrollments and Labor-Market Realities" which I cited in the previous post in this series.  To quote their report,

"The mismatch between the educational requirements for various occupations and the amount of education obtained by workers is large and growing significantly over time. The problem can be viewed two ways. In one sense, we have an “underemployment” problem; College graduates are underemployed, performing jobs which require vastly less educational tools than they possess. The flip side of that, though, is that we have an 'overinvestment' problem: We are churning out far more college graduates than required by labor-market imperatives. The supply of jobs requiring college degrees is growing more

slowly than the supply of those holding such degrees. Hence, more and more college graduates are crowding out high-school graduates in such blue-collar, low-skilled jobs as taxi driver, firefighter, and retail sales clerks..."

In evaluating whether these assertions are valid, it is helpful to consider the present-day structure of the American economy as a representative of the typical economies of the Global North.  It is also helpful to consider the background of the people who have made these assertions in order to glimpse something of their possible motives.  As I mentioned previously, Peter Turchin is an academic who is already both tenured and well-established (thus well-fed, with multiple income streams), and his assertions of the need to limit access to higher education are not likely to hurt him in any way.  As for Vedder, Denhart, and Robe, Vedder is an adjunct member of the American Enterprise Institute (AEI).  Denhart is one of Vedder's former students.  I don't know how much of Vedder's ideology was passed on to Denhart and Robe, but I do know that Vedder is a strong supporter of big business even when it pays exploitative wages to workers, as seen in his support of Wal-Mart and of the 2008 taxpayer bailout of American businesses deemed to be "too big to fail".  (Note that that 2008 taxpayer-funded bailout is one of the biggest reasons why the richest Americans are now so rich!) Moreover, the AEI itself has the policy goal of supporting big business at the expense of small businesses, going as far as advocating that the role of the American government should be to help big businesses grow bigger.  The AEI wants further to eliminate all government support for small business, especially small business incubation, as I pointed out in a previous post.

From such observations, it is possible to move to a consideration of the structural reasons for the mismatch between jobs requiring a college education and the supposed "excess" of college graduates.  I will once again state my belief that high-quality, advanced education should be made available to as many people as want it - regardless of race, creed, national origin, or economic status.  Moreover, I once again assert that education is one of the great equalizing factors in a society, as it is a key component in the struggle of historically oppressed peoples to liberate themselves from historical and ongoing oppression.  This, for instance, was the motivation for the Polish underground "flying universities" which were organized in the 1800's when Poland had been partitioned by Germany, Austria, and Russia, and these nations had forbidden Poles from having access to higher education.  This was also the motivation for the underground "freedom schools" which sprang up in the American South during the antebellum days when white Southern power made it illegal to teach Black people (my people) to read.

But education alone is rather impotent without an opportunity to use it.  And the opportunities for the use of education are constrained by the structure of the society in which that education must operate.  Too often, the structure of a society is dictated and constrained by the dominant power-holders in that society.  I will therefore suggest that the decline in opportunities for college graduates (along with everyone else) is correlated with the rise in the concentration of economic power in the hands of an ever-shrinking elite.  In fact, I will go even farther and assert that the decline in stable employment for college graduates (even those with technical professional degrees) is a direct outcome of the concentration of economic power at the top of society.

Consider the fact that as of 2015, "America's 20 wealthiest people - a group that could fit comfortably in one single Gulfstream G650 luxury jet - now own more wealth than the bottom half of the American population combined..."  These people therefore have an enormous amount of economic and political clout.  And they have used (and continue to use) that clout in order to turn the American economy into a machine whose sole function is to make them as rich as possible.  The increase in precarity, the casualization of increasing types of employment, and the increasing use of task automation and artificial intelligence are typical of the strategies which these wealthy and powerful people have deployed in order to maximize the wealth they can extract from the American economy while minimizing the amount of wealth they give to the rest of us.  The aggressive expansion of the "gig" economy is another such strategy, as is the crafting of laws and regulations (especially by Republicans) which disadvantage small businesses (and all the rest of us, especially those of us who are not of their "tribe") while giving breaks to big business.  

What would a society look like if it provided citizens with the maximum optimal education and the maximum optimal opportunity to use that education in the pursuit of meaningful work?  I'd like to suggest that first, such a society would have a mechanism in place to prevent any one person or entity from concentrating more than a very small fraction of economic output into one set of hands.  Second, I suggest that such a society would be composed largely of artisans, artists, and small businesses owners who exercised their knowledge, education, and creativity to a maximal extent.  In other words, this society would be largely composed of "yeoman entrepreneurs" similar to the "yeoman farmers" idealized by Thomas Jefferson.   Some might say that such a society would be impossible in the 21st century, but I'd like to suggest that some positive aspects of what such a society might look like can be found in the depiction of the fictional Mars City in Hao Jingfang's novel Vagabonds.  I will mention that novel again in a future post. (Note also that although there was much to like about Mars City, it was not exactly a perfect utopia - there were indeed a few flies in that ointment, so to speak.)

Lastly, I suggest that such a society would be resilient - much more so than a more stratified, unequal society would be.  This is because such a society would have a much higher degree of decentralized group intelligence than would exist in a society of stratification and inequality.  This would make the more egalitarian society much more able to respond to emergent threats and opportunities than the more stratified society.  Consider the late 19th century and early-to-middle 20th-century history of Britain as a stratified society of the Global North.  Consider how its rigid class hierarchy and caste system prevented some of its principal actors from seeing the big picture and acting appropriately in the face of challenges.  Cases in point include the failure of Robert Scott's Antarctic expedition in comparison to the successful expedition of Roald Amundsen, as well as failures in World Wars 1 and 2 that resulted from a hidebound British system of honor, privilege and caste which blindsided British leadership.  The strident attempt by the Republican Party and other right-wing elements in the United States to re-establish an American system of caste and privilege constitutes the real threat to the "existing power structures" cited by Turchin, because it is leading to the "fragilization" of these structures.

The Educated Precariat: The Seedlings Of Early Trees

This post is a continuation of my series of posts on economic precarity.  As I mentioned in recent posts in this series, we are now starting to delve the subject of the educated precariat - that is, those people who have obtained either bachelors or more advanced graduate degrees from a college or university, yet who cannot find stable work in their chosen profession.  I suggest that the troubled lives of the educated precariat are a symptom of the troubled state of higher education generally - especially in the First World (also known as the Global North).  Two troubled groups come immediately to mind, namely, academics (college professors or salaried researchers) and college or university graduates.  We will explore the plight of new college professors and researchers later.  But suffice it to say that the guaranteed career of a tenured professor is increasingly out of reach for this group.  (See also, "Tenure Track for Professors In States Like Texas May Disappear," USA Today, 13 April 2023.)  A third group that may not know it's in trouble consists of new and continuing college and university students whose necks will one day be broken by the mousetrap of student loan debt.  A fourth group consists of the administrators and employees of the system itself.  Their trouble arises from the fact that they are running out of a key resource, namely, new students!  This is due to a number of factors, such as declining birth rates, as well as a sober realization on the part of young men and women that college education itself has begun to yield sharply diminished returns even as it has become unbearably expensive.

In considering the historical role of higher education in the development of global civilizations, it is natural to ask how things got to this state in which American higher education has begun to crumble. Where exactly did we come from that we have arrived at this destination?  To answer that question, we need to look at where we started from - in other words, it's time to look at the historical origins of education in general and of higher education in particular.

The first thing we notice is that there are records on almost every continent from almost every civilization describing the origins and evolution of formal education and of the creation of higher education systems. Ancient places of higher learning can be found in places such as these (this is a very partial list, by the way):

• Mali, African Continent (University of Timbuktu containing the Sankore Madrasah)
• Tunisia, African Continent (University of Ez-Zitouna)
• China 
• Academy of the White Deer Cavern (白鹿洞書院); 
• Songyang Academy (嵩陽書院) (This was a private rather than public institution.)
• Taixue (太學) ("National University" established by Emperor Wu)
• Greece, European Continent
• The school of Isocrates
• The school of Plato (Also known as the "Academy", which was the first historical use of this term in the West.)  (See also Higher Education In Greece, Kyriazis and Asderaki, CEPES, 2008)
• The school of Pythagoras
• The Byzantine Empire
• The Pandidakterion (known today as the University of Constantinople)

Note that although some of these institutions are called "universities," the actual entity known as the modern university did not come to being until the Middle Ages in Europe.

The entire educational process including both primary and higher education has been documented for the Greco-Roman and Chinese cases, and so it is useful to examine these cases in more detail.  First, let's consider the Greco-Roman case.  And in the case of Greece, we must consider the distinction between education in the Athenian city-state and education in Sparta.  According to Wikipedia, formal education in Athens was reserved for boys who were free-born.  The education of slaves was forbidden.  Formal education was conducted by either public schools or by private tutors.  I was not able to find out how much access to public schooling depended on family wealth, but the sources I have found do indicate that the extent of this formal education did depend on how much a family could afford to pay.  Access to higher education was strictly on the basis of a student's ability to pay, and it appears that the system of higher education was largely created and run by private individuals with sufficient means for leisure.  Thus figures such as Aristotle and Plato could be considered a kind of educational entrepreneur.  As for Sparta, while both free men and free women could participate, the purpose of Spartan education was solely to train the nation for war-fighting.

A funny thing happened to educated Athenian Greeks who had enjoyed the status of free-born intellectuals: when the Greek city-states were conquered by and absorbed into the Roman Empire, these free-born intellectuals became slaves themselves.  However, these educated slaves were able to lighten the burden of their slavery by becoming tutors and founding their own private schools (often with very slim profit margins).  This system of private education began to assume the role which Roman fathers as heads of households had traditionally held as the educators of their children.  In the Roman empire, there was no state-funded public education, either at the primary or the secondary level.  Yet those who wanted to participate in Roman politics were required to obtain a formal higher education.  This limited participation in Roman politics to the wealthy.  Also, whereas in Greece, higher education was seen as an activity of leisure which should not be tainted by any practical application (From Formal to Non-Formal: Education, Learning and Knowledge, pages 8 and 9), in the Roman empire the situation was different.  For Romans insisted that all education should have some practical purpose.  

In China, primary education began as an informal, communal process.  According to Dr. Ulrich Theobald, "The oldest word for "school" is xiang 庠, which actually means a building for livestock with two facing walls, where elderly people reared sheep, pigs or cattle and at the same time were entrusted with the duty to watch children and instruct them."  Primary education in China eventually evolved into a system of both private and public schools.  The public schools came into being during the Tang and Ming periods.  These schools, along with private primary schools and tutors, prepared students to enter the Chinese academy system, which then prepared promising students for posts in the Chinese civil service.  A couple of noteworthy facts regarding these academies is that there were times when private academies were either outlawed, disbanded, or taken over by the state as exemplified by the emperor.  Also, there were periods in which the state created or funded public academies in the academy system.  Lastly, some of the academies of the 18th and 19th centuries assumed research duties in addition to teaching.  The Taixue 太學 "National University" had already assumed a research role during the Southern Dynasties period from 420 to 589 AD.  

From the Chinese and Greco-Roman cases we can see that a key function of ancient higher education was to produce an elite class - that is, people who could either participate in politics and governance as ruling practitioners of statecraft, or as people who could serve as competent administrators/bureaucrats under these ruling elites.  Therefore the function of many ancient institutions of higher learning was not primarily research, although, as noted above, exceptions to this did exist in both ancient Greece and in China.  Stronger examples of a focus on both research and applied knowledge can be found in the Academy of Gondishapur in what is now modern Iran.  This academy was a center for the learning of medicine and science, among other subjects, and the modern hospital system owes much of its inspiration and foundational philosophy to this academy.  The Sankore Madrasah on the African continent also evolved a research function, although its main original purpose was Islamic education.  We don't have time today to explore the beginnings of the modern European university, but suffice it to say that the modern university system seems from the outset to have had the dual purposes of research and teaching.  Thus the early modern universities took over the function of producing the clerics of the Roman Catholic Church (the Western form of the mandarin administrator) in addition to producing research.

What is interesting to note is how systems of higher education fare in societies undergoing decline.  The Byzantine system of higher education is a key example.  The vicissitudes of the Byzantine empire in the 7th and 8th centuries and in the 13th century dramatically decreased the central government's ability to fund higher education and led to the privatization of higher education.  It is certain that this influenced the supply of competent practitioners of statecraft as well as competent administrators.  It is also true that declining Byzantine imperial power also produced declines in the number of jobs available to would-be mandarins who graduated from any Byzantine program of higher education.  This has significant implications for the American system of higher education, as the process of accelerating inequality continues in the United States, and as the rich parasites at the top of the food chain continue to suck nutrients from the rest of society.  More on that in another post.

The Educated Precariat - A Preview

It is now nearly time to consider a particular subset of the precariat, namely, those people who have college degrees yet who have been forced into precarious employment - especially, those who are in low-wage jobs.  In this consideration we will move beyond the United States to look at the surplus of college graduates and the lack of appropriate employment for these graduates as a global phenomenon.  We will find that among the ranks of these are coffee shop baristas with graduate training in fields such as psychology as well as technical professionals hired by temp agencies and the legions of adjunct professors at public and private universities throughout the United States.  We will consider the underemployed college graduate in both American, European and Chinese contexts, and compare these to the ranks of underemployed graduates in the developing world.  We will also try to examine the phenomenon of college graduate precarity as it exists in Russia.  However, examining the Russian case may prove difficult if one wants a recent and accurate snapshot, due to the fact that the regime of Vladimir Putin has been trying as hard as possible over the last few years to patch up the fig leaf dress which Russia has sewn to cover up its putrid nakedness.  (In fact, it has become much easier to obtain an accurate picture of daily life for ordinary people in China than in Russia.  China is actually more open and honest!)

Today's post will ask some preliminary questions.  First, how did we get to this present place in which a four-year or advanced college degree is no longer a guarantee of stable, middle-class employment?  To answer this question, we will need to answer the following questions:

• What was the original purpose of college?  Note that the word "college" comes from the Latin word collegium, defined by Wiktionary as "colleagueship (connection of associates, colleagues, etc.", guild, corporation, company, ... (persons united by the same office or calling or living by some common set of rules), college (several senses), school ..."
• What did the world's first colleges look like?  You may not know this, but one of the world's oldest continuously operating universities is the University of Ez-Zitouna, which was founded in Tunisia on the African Continent.  What was the mission of the world's first and earliest universities, and how was that mission funded and carried out?  How did the roles of education and research interact?
• What was the origin of the system of public universities in the United States?  (For instance, what was the role of the presidency of Abraham Lincoln in the birth of American public universities?)
• What are the origins of the for-profit college or university, and how did these institutions cause the purpose of college to mutate over time?
• How has the decline in public and private funding for basic research affected the employment landscape for academics?  (You may not know this, but the United States no longer has any major corporately-funded laboratories dedicated to pure research.  Bell Labs, which was responsible for the discovery of radio astronomy and many other scientific breakthroughs, is now a wholly-owned subsidiary of Nokia, a Finnish corporation.)
• What is the impact of declining numbers of youth and declining college enrollment on universities and colleges?
• How will the defunding of public colleges and universities affect the future of those nations such as the United States which pursue rabidly conservative "free-market" principles?  See, for instance, "Modeling research universities: Predicting probable futures of public vs. private and large vs. small research universities", 2018.
• What can college-educated members of the precariat (especially those college-educated who have been historically marginalized, such as people of color) do both individually and collectively to create a better situation for themselves?  For the present-day contraction of opportunities for the college-educated is being orchestrated by the present masters of our society in an attempt to maintain and amplify existing inequality.  What steps can we therefore take to create our own alternative spaces of collective self-reliance?

I hope to answer these questions (maybe with a little help from some friends) during the next few posts in this series.  I'd like to end with something that's somewhat related to this series of posts and to other posts which I've written for this blog over the last four or five years, namely, another link to a short fiction story which I recently enjoyed.  The name of the story is "Tempus Fugit" and the author is Ketty Steward.

Precarity, American-Style: The American Enterprise Institute and Small Businesses

This post is a continuation of my series of posts on economic precarity and the precariat.  Past posts explored the manifestation of precarity in Russia and China, two nations which returned to the capitalist fold at the end of the 20th century after abandoning free-market capitalism during the early and middle decades of the 20th century.  More recent posts have explored the spread of precarity in the United States, a nation which has been characterized from its birth by a cultural emphasis on laissez-faire, free-market capitalism and the defense of the "property rights" of those who are wealthy.  This post continues the exploration of precarity in the United States.

At the outset, I'd like to state my belief that the solution to the problem of economic precarity and rampant wealth inequality is to create a society in which the role of small businesses is central and in which private concentrations of wealth and power above a certain size are eliminated by a steeply progressive tax with no loopholes for the rich.  Such an arrangement would fulfill the ostensible goal of socialism without requiring the government to be the owner of the societal means of production.  For such an arrangement would place the means of production directly in the hands of even the poorest of people.

I can already hear the screams of rage which the emergence of such a society would produce among the leaders of the American right wing.  That's okay - sometimes people need to see their sacred cows turned into hamburger.  Yet one area in which we all seem to agree is the importance of small businesses in the American economy and the need to provide support to these businesses.  Presidents and members of Congress from both sides of the aisle have made strong and warm statements of support for small business from the days of Reagan onward.  Indeed, the Republican Party in particular has branded itself the champion of small business.  This has been part of the Republican Party's branding of itself as the party of economic growth in general and of the promotion of economic policies which guarantee prosperity for all.  (Of course, the fact that Republican policies have created many more losers than winners is blamed on the losers, but that's a story for another post.)

Can the Republican Party truthfully say that it has been and continues to be a champion of American small business?  The answer to that question can be found in the policies and activities of some of the lobbying groups and think tanks which are part of the American right wing.  Let's look at one of those groups today, namely, the American Enterprise Institute, or AEI.  According to Wikipedia, the AEI is "...  a center-right think tank based in Washington, D.C., that researches government, politics, economics, and social welfare... Founded in 1938, the organization is aligned with conservatism and neoconservatism ..."  To call them "center-right" may be quite misleading, as their membership has included several figures who are very much hard-right - figures such as Robert Bork, Newt Gingrich, John Lott, Antonin Scalia, and Dick Cheney.  In addition, the AEI is closely aligned with the Koch brothers, according to a Sourcewatch article.  Moreover, some of the recent posts and articles on the AEI website have seemed to give support to the regime of Vladimir Putin.  The AEI has become the dominant brain trust of the American right wing, "the crown jewel of the conservative policy infrastructure," according to a recent Johns Hopkins University case study.  

In 2005, the AEI published a paper titled, "Are Small Businesses the Engine of Growth?"  The abstract of that paper provides a concise summary of AEI's desired policy toward small business: 

"It is a common belief among entrepreneurs and policymakers that small businesses are

the fountainhead of job creation and the engine of economic growth. However, it has

become increasingly apparent that the conventional wisdom obscures many important

issues. It is an important consideration because many government spending programs, tax

incentives, and regulatory policies that favor the small business sector are justified by the

role of small businesses in creating jobs and is the raison d’etre of an entire government

agency: the Small Business Administration (SBA). This paper concludes that there is no

reason to base our policies on the idea that small businesses are more deserving of

government favor than big companies. And absent other inefficiencies that would hinder

small businesses performances, there is no legitimate argument for their preferential

treatment. Hence the paper suggests ending all small businesses’ subsidies." [Emphasis added.]

The paper sought to make a case for eliminating all government agencies and programs that support or incubate small businesses, both at the Federal and State levels.  It twisted a number of statistics in its attempt to make its case, attempting for instance to convince readers that the net gains in job creation  should be ignored in favor of gross job creation when analyzing the impact of small businesses during any time period of analysis.  This position, by the way, is proven false by the fact that reputable agencies such as the World Bank do count the impact of net job creation in evaluating economic performance.  For an example of the paper's mishandling of statistics, consider the part where the author tries to use gross job gains and gross job losses to "prove" that employment in the small business sector was much less stable than in large companies during the year 2000.  The author neglected to notice that during the time period in question, the net addition of jobs by small businesses was always positive, and for firms between 1 and 49 employees, exceeded 10 percent.  Lastly, I would point out the laughably false claim made by the paper that "... larger employers offer greater job security. For both new jobs and the typical existing job, job durability increases with employer size."  (That has definitely not been my experience as a working stiff and cubicle rat!  I guess the author of the paper never heard of the words "downsizing" or "redundancy"!)

The 2005 AEI paper cited above was part of a sustained effort on the part of American conservatives to make a case for eliminating all government support for small businesses.  One such example is the article, "Terminating the Small Business Administration" (2011), along with articles published from 2008 onward which suggested that government support of small businesses leads to negative economic growth.  I argue that the AEI paper, on closer examination, does not present a scientifically rigorous or accurate case.  However, it definitely does express what rich American conservatives want to do to American small businesses.  Consider the following quotes:

"... the real job growth comes not from people dreaming of being small business owners but from people committed to building big companies." [Emphasis added.]

"The paper will examine whether the pervasiveness of the belief that small businesses are the economy’s main source of job creation is warranted. Section 2 will show how this belief is the foundation for many government policies. Section 3 will expose the statistical fallacies that lead people to see job creation patterns where none exist. Besides it shouldn’t matter. Although job creation receives enormous attention in policy discussions, it is rather misplaced. The mere creation of jobs is not by itself an appropriate economic policy objective. Economic growth whether it takes the form of additional jobs or increase of productivity in existing jobs is all that matters. The paper concludes that there is no reason to base policies on the idea that small businesses are more deserving of government favor than big companies." [Emphasis added.]

In other words, the AEI has backed a policy which favors the continued growth of large companies, and the continued growth of American economic productivity even when that growth is not accompanied by the growth of jobs.  We have already seen the results of such a policy in action, namely, in the jobless "recoveries" from economic crises which occurred during the presidencies of Ronald Reagan and both Bushes.  Such "recoveries" left a lot of people out of work for a long time, while those who still had jobs were subjected to ever-increasing demands on their time from their employers in the name of increasing productivity.  To put it another way, these "jobless recoveries" resulted in ever-increasing concentrations of wealth among the richest members of society while drastically increasing economic precarity among everyone else.  It is quite telling that the AEI has pushed so hard for the elimination of all government help for small businesses even though large corporations are the biggest recipients of corporate welfare from both Federal, State and local governments.

Let us close with a couple of questions.  Does real job growth come not from people being small business owners but from people committed to building big companies?  Is it true that the only thing that matters is economic growth, regardless of whether it takes the form of additional jobs or increase in productivity in existing jobs?  I'd like to give my answer to these questions, but I don't have time today, so that will have to wait.  But as a partial answer, consider the following questions:

• How many really big companies can exist in a society whose economy is of finite size?
• Why should most people rally behind continued economic growth if the fruits of that growth are not fairly and equitably distributed?
• Who wants to volunteer to be one of the many poor, disenfranchised, and unemployed who are produced by a system in which the fruits of increased productivity are not fairly distributed?
• Who wants to volunteer to be a member of the salariat in such an economy if the only way to be a member of the salariat class is to work 80-hour weeks?

Precarity in the United States: A Preview of Coming Attractions

I have begun research on my next posts in my series on precarity and the precariat.  My focus will shift from precarity in formerly communist countries to precarity in the United States.  I believe we will see a surprising similarity of patterns to those patterns we observed in the Russian and Chinese cases.  We will also see that very few people in the Unites States can afford to be complacent anymore.  I have gathered a lot of material, and like a person who has just binge-shopped a gourmet supermarket, I'll need time to digest it all.  In the meantime I may write a post on another subject tomorrow, but if I do, it will be a short post.  Those who want to get a head start on me in my research on precarity, American style, can consult the following sources:

• The Educated Underclass: Students and the Promise of Social Mobility, Gary Roth, Pluto Press, 2019.
• Immigrant Labor and the New Precariat, Ruth Milkman, Cambridge: Polity Press, 2020.  (Note: Try not to order an e-book copy of this through the John Wiley website.  Wiley has e-book download policies that will make you want to kick furniture and punch walls...)
• "Not 'Just' a Barista: The Story of Portland's College-Educated Baristas, Ned William Tilbrook, Portland State University, 2020.  (Now this sounds interesting!)

And there's much, much more!  Stay tuned . . .

The Precariat In The East: The Chinese Case

Today's post is the fourth installment in my series of posts on precarity as a feature of 21st century life and the precariat as a global cultural phenomenon.  For context, please also read Part 1, Part 2 and Part 3.  In the third post in this series, I wrote the following:

But the precariat has also arisen outside of the West.  What has been striking is its origin and spread in those regions which withdrew themselves from global capitalism in the early 20th century only to return to the capitalist fold near the end of the 20th century . . .

Today's post will consider the emergence of the precariat in China during the last forty-five years.  And it must be said that while precarity is a definite sign of economic inequality in a society, it is also true that there have been unequal societies in which precarity did not exist.  Chinese history spans both cases.  In fact, according to a paper titled, "Understanding Inequality in China" (Yu Xie, University of Michigan, 2010), ". . . inequality has been a part of Chinese culture since ancient times."  Historically, this inequality did not contribute to precarity among the poor in Chinese society.  However, this culture of inequality was a contributing factor in the precarity that emerged after the death of Mao Zedong.  So let us consider the evolution of inequality and class mobility in China from ancient times to now.  

Ancient China

In ancient China, the emperor was the only person with a permanent hereditary position of wealth, privilege, and power.  According to Yu Xie's paper, the emperor governed by two means: first, by the promulgation of the doctrines of Confucius and Mencius who taught that the mission of rulers is to work for the public good; and second, by the use of a vast corps of semi-autonomous administrators and bureaucrats scattered throughout the provinces of the Chinese empire.  The relationship between ordinary peasants and the emperor and his bureaucrats was therefore shaped by two points of propaganda: first, that the emperor and his administrators were actually working for the public good, and second, that for the emperor and his administrators to do their job, structural inequality was necessary.  According to Mencius, "‘There are those who use their minds and there are those who use their muscles. The former rule; the latter are ruled.  Those who rule are supported by those who are ruled.’ This is a principle accepted by the whole Empire . . ."  Therefore, the mission of the peasants was to use their labor to provide material support to this cadre of rulers.  

In order to make sure that the peasants did their part to support their rulers, a system of taxation was developed, and as part of that system, a system of personal registration (hukou (户口)) and household registration (huji (户籍)) was developed.  According to a paper titled, "Governing neoliberal authoritarian citizenship: theorizing hukou and the changing mobility regime in China" by C. Zhang, Queen's University Belfast (2018), this household registration system ". . . continuously served important social and political functions, including military conscription, taxation, local policing, social security and mobility control, for about two millennia in the centralized bureaucratic empire . . ."  Note especially the mention that from time to time, the huji system was used to limit the ability of subjects to move around from region to region in the empire.  This is corroborated by a mention in another paper of how the Qin dynasty used the huji system to limit movement of individual subjects from region to region: "The Qin people [sic] could not freely move outside an administrative unit to which he or she belonged; thus, they had to use credentials for traveling and transfer certain personal documents when moving from one unit to another."  ("In the Government's Service: A Study of the Role and Practice of Early China's Officials Based On Excavated Manuscripts," Daniel Sungbin Sou, University of Pennsylvania, 2013)

Even with this system of registration in place, however, social mobility was still possible in ancient China.  For the rich, whose riches under the existing economic and cultural system were not easily inheritable, there was always the possibility of downward economic movement.  According to Yu Xie's paper cited above, ". . . except for the emperor, the aristocratic and privileged classes were not stable . . . In fact, the emperor did not want the inheritance of the aristocratic and privileged class."  People who got too rich could in fact be repressed and have some of their possessions confiscated.  Also, poor people could advance their family prospects by investing in the education of their sons.  By this means the next generation could climb the rungs of the Chinese meritocracy and become administrators themselves.

By these arrangements, ancient Chinese society was conditioned to accept inequality as the "inevitable" price of the promotion of the social welfare of the entire society.  The system worked and was acceptable to all as long as emperors and their administrators actually ruled for the benefit of all, and as long as there was some room for social mobility among the poor.  However, between ancient times and the present, China underwent subjugation by Western powers, followed by a revolutionary fight for independence.  As a result, its internal systems went through a period of readjustment.  

Maoist China

Maoist China inherited most of the existing cultural institutions which had endured from ancient times.  Maoist China also inherited the toxic mess which Western colonialist powers had made of Chinese society.  However, the responses of the government of Mao Zedong to this mess created new challenges.  One of Mao's early goals was to transform China from a primarily agrarian society to a modern industrial society as quickly as possible.  This led to such disasters as the Great Leap Forward which was launched in 1958.   

In 1958 the system of internal household registration was also transformed into a much more rigid modern hukou system modeled on the Soviet Russian system of propiska (пропи́ска).  It is interesting to note that in its original form, the Russian propiska system, hundreds of years old, was designed to prevent the upward social mobility of Russian serfs.  The Chinese system, borrowing from the Russian system, thus created a society which was the opposite in certain key aspects from the socialist promise of a "classless" society.  

The hukou system had the following elements:

• Starting in 1958, all people had to be registered according to birthplace.
• The person's birthplace was the determinant of whether the person received State welfare services and what kind of services would be received.
• Those whose birthplace registration was urban received State services.
• Those whose birthplace registration was rural received no State services.  Any welfare services they received had to come from communal social arrangements in their village of registration.
• Those whose birthplace was urban were categorized as non-agricultural.  Those whose birthplace was rural were categorized as agricultural.
• The children of the people registered in 1958 inherited the hukou status of their parents.  The children of these children, in turn, inherited their parents' hukou status.  Thus even if you were a child born in the 1990's in a city, if your parents had a rural hukou status, you inherited the same rural hukou status.

The Maoist hukou system created a social hierarchy in which the members of the Communist Party were at the pinnacle.  Immediately below them were the city dwellers who were involved in industrial production.  Below them were the rural peoples, whose mission was to provide food to the industrial urban centers and the leadership of the country in order to fulfill the mission of rapid industrialization.  Therefore, the social mobility of the rural, agricultural hukou holders was severely restricted.  Anyone who held an rural agricultural hukou who tried to move to a city without permission was likely to be severely punished.  Moreover, anyone from the countryside who moved to the city without permission would be denied access to the social services available to the residents of the city who held urban, nonagricultural hukou status.  And the Chinese government made it very hard for anyone with a rural hukou status to change to an urban hukou status.  (See "China's Household Registration (Hukou) System: Discrimination and Reform", Fei-Ling Wang, Georgia Institute of Technology, 2005.)  According to "China’s Hukou System: How an Engine of Development Has Become a Major Obstacle" (Martin King Whyte, Harvard University, 2009), the holders of rural, agricultural hukou comprised 80 percent of the total Chinese population in Maoist times.

One last feature of note in the Maoist system was the danwei (单位) system.  A danwei was a work unit organized in Maoist China.  According to Wikipedia, the workers assigned to a danwei were the bottom rungs of the social hierarchy whose head was the central Communist Party.  Danwei referred not only to the place of work but also to the organization of the work unit.  The danwei also served the purpose of dispensing social welfare benefits to their subjects.  Thus things like health care, schooling and day care for children, and other benefits were dispensed to workers through their danwei.  Once assigned to a danwei, it was very hard for a worker to be fired, because the danwei provided an "iron rice bowl" to their workers, a system of social welfare and livelihood that, while often not comfortable, at least prevented them from having to live a precarious existence.  While this security had its good features, it was part of a system that did not deliver prosperity and national advancement as rapidly as was wished by some of the more forward-thinking members of the Chinese Communist Party.  Therefore, after Mao's death, Chinese social arrangements were again altered in order to attempt to harness capitalism as an accelerator of growth and advancement.  While the alteration did produce results, it also accelerated the increase of inequality in China and began to introduce a rapidly-growing element of precarity in Chinese society.

From The End of Maoism to Today

The changes wrought by the reforms begun in 1978 have been profound.  Two changes are especially relevant, as they have contributed most greatly to the emergence of the precariat in China.  The first is the smashing of the "iron rice bowl" danwei system.  According to Wikipedia, when individual private enterprise became possible once again, private enterprises and foreign multinational corporations were able to out-compete state-run danwei.  This led to the weakening and shrinkage of the danwei, and the increasing number of workers who were thrust out of stable careers with guaranteed benefits into an uncertain labor market.  Thus these refugees from the danwei system became an element of today's precariat in China.  In losing their danwei, these displaced workers lost the social units that once gave them status, identity, and access to benefits.

The hukou system was also changed.  The changes have been coordinated between the Chinese government and large holders of capital in the Chinese economy, and their goal has been to create and expand a large, flexible, and cheap workforce.  The elements of this change are as follows:

• Restrictions on physical movement under the Maoist hukou system have been relaxed somewhat but definitely not eliminated.  
• Hukou status has largely remained unchanged in the sense that it is still difficult for holders of rural hukou to change their status to urban.
• Legal migration of rural residents to urban centers is more possible now than in Maoist times.  However, rural residents who do migrate are still denied access to the social welfare services and legal citizenship rights granted to holders of urban hukou.  
• This arrangement has therefore created a very large class of migrant workers who are paid very cheaply and have few or no rights.  
• Those who migrate legally are more likely to be integrated into the formal economy of the cities to which they migrate, whereas those who migrate illegally tend to wind up in the informal economy.
• Whether formally or informally employed, these migrant workers are not granted stable, long-term employment contracts.  Therefore they comprise another very large sector of the Chinese precariat.
• Many of these people are forced to work like dogs, as evidenced by the "996" schedule imposed by many employers, a schedule which was only recently ruled illegal by the Chinese Supreme Court.
• Those who migrate illegally are subject to the threat of violence either by the State or by their employers.

One other thing to note is that in China as elsewhere, education is no longer the guaranteed road out of precarity into a more stable life.  A 2021 paper titled, "After the Foxconn Suicides in China: A Roundtable on Labor, the State and Civil Society in Global Electronics" describes the exploitation of young Chinese students by the tech industry, thus highlighting the struggle of the large percentage of youth in the Chinese precariat.  This is also pointed out in another paper titled, "The Chinese Race to the

Bottom: The Precarious Lives of Unemployed University Graduates in Beijing’s ‘Ant Tribe’".

Lastly, it should be noted that although the precariat in China is expanding, expressions of resistance to exploitation are beginning to appear as well.  For further information on these, you can read the first pages of Building China: Informal Work and the New Precariat by Sarah Swidler.

I have one or two more global regions to examine in sketching the precariat as it exists in the world today.  Those will require more research, so the next post in this series may need to wait a couple of weeks.

Research Week - End of January 2023

As I noted in my most recent post on the subject of precarity, there is a fairly wide body of research which has been done on the origins and spread of the precariat in the developed nations of the West.  I think it is good also to see how the precariat has come into being and has evolved in those nations that are not historically of the West.  The last post in the series therefore covered precarity as it exists in Russia.  I promised that the next post in the series would cover other non-Western cases.

In preparation for that next post I have therefore downloaded several articles concerning another nation of interest to this discussion.  However, I need time to read and analyze everything I've downloaded so that my next post does not wind up shooting from the hip.  Hopefully I'll be ready by next weekend . . . 

The Global Origins And Spread of the Precariat (Part 1)

Last week's post described my own experience of precarity - an experience which continued in surprising ways even through the world of white-collar professional work.  This week's post will begin to explore the theoretical foundations for understanding the precariat, and will begin to trace the present existence of the precariat in the societies of certain nations of interest.  

Precarity can be understood as a social bargain that has been lost.  The loss of this bargain can be described thus: "The emergence and strengthening of [the] precariat are associated with regulatory dysfunction . . . Precariat is a consequence of the lack of effective institutions for regulating emerging new social relations. Such institutions cannot be replaced by designing effective market mechanisms . . .   Precariat is formed wherever stable forms of employment are destroyed."  [Emphasis added.]  ("Socio-Economic Sustainable Development and the Precariat: A Case Study of Three Russian Cities," Volchik, Klimenko, Posukhova, International Journal, Entrepreneurship and Sustainability Issues, September 2018)   Precarity is therefore the loss of the social bargain between workers and employers which was forged in the labor movements of the late 19th and 20th centuries in industrial nations.  It can also be seen as the destruction of the social arrangements which were forged and codified into law (such as antitrust and anti-monopoly laws) between ordinary people and the rich.

The destruction of this pre-existing social arrangement has been documented by observers such as economist Guy Standing, a Professorial Research Associate at SOAS University of London.  Mr. Standing did pioneering research into the topic of precarity and the precariat, and captured his observations and conclusions in two books which he wrote, titled, The Precariat: The New Dangerous Class, and A Precariat Charter: From Denizens to Citizens.  To quote from a 2018 essay by Mr. Standing, "Since 1980, the global economy has undergone a dramatic transformation, with the globalization of the labor force, the rise of automation, and—above all—the growth of Big Finance, Big Pharma, and Big Tech. The social democratic consensus of the immediate postwar years has given way to a new phase of capitalism that is leaving workers further behind and reshaping the class structure. The precariat, a mass class defined by unstable labor arrangements, lack of identity, and erosion of rights, is emerging as today’s “dangerous class.” As its demands cannot be met within the current system, the precariat carries transformative potential . . . "

In his essay, Guy Standing traces the beginnings of the precariat to the deliberate dismantling of social arrangements between owners of big business and workers at the start of the 1980's.  This dismantling was part of the process of radical, rabid free-market capitalism pushed by people such as Ronald Reagan and Margaret Thatcher.  According to Standing, those who pushed this process ". . . preached 'free markets,' strong private property rights [at least for those who were filthy rich!  Not so much for little people . . .], financial market liberalization, free trade, commodification, privatization, and the dismantling of all institutions and mechanisms of social solidarity, which, in their view, were 'rigidities' holding back the market. While the neoliberals were largely successful in implementing their program, what transpired was very different from what they had promised."

Standing describes the process of precarization as it began in the West (especially the United States, the other nations of the Five Eyes, and Europe) and as it was promulgated by various institutions of Western economic hegemony such as the World Trade Organization.  But the precariat has also arisen outside of the West.  What has been striking is its origin and spread in those regions which withdrew themselves from global capitalism in the early 20th century only to return to the capitalist fold near the end of the 20th century.  Indeed, it can be argued that wherever there is a society characterized by connection to the global economy, extreme levels of inequality, and a very small class of plutocrats who control an enormous percentage of that nation's economy, there you will find the precariat in existence.  What is more, you will find that the plutocrats of each of the world's major societies share a lot in common with each other.  So I'd like to take this post and the next post in this series to describe the process of precarization as it has worked itself out in other regions of the world.  Let's start with Russia.

"Funeral for the Middle Class", a protest which took place 

in Russia in 2015.  In the picture, the "casket" being placed

by the man in the center has the words "средний класс" ("middle class")

written on it.  Image retrieved from Obschchaya Gazeta on 21 January 2023.

In Russia, the transition from Soviet communism to free market capitalism was a transition from the Soviet arrangement where "formalization, legal confirmation, and guarantee of a workplace for a worker were the methods which prevented the spread of precarization.  The system was oriented toward distribution of social benefits, consolidation of the worker's professional status in the consequent sphere, and work, labour, employment, and housing related stabilities . . ." (Quote taken from "The Precariat In The Socio-Economic Structure of the Russian Federation," Maria Fedina, International Department of Movement for Decent Work and Welfare Society, September 2017.)  It was a transition into an employment market which has ". . . 'responded to unfavorable economic transformations by such means of adaptation as part-time and seasonal work, forced vacation leave, secondary employment and employment in the informal sector'. Other forms of adaptation include fixed-term employment contracts, outsourcing of workers, employment on the basis of employment contracts with a condition of work outside the employer’s location, and employment of individual entrepreneurs who have no possibility to run their own business by other entrepreneurs." [Emphasis added.]  To break this down into plain language, Russians moved from an economic environment in which housing and employment were stable and secure, and moved into an environment in which many Russian workers today may be forced to work part-time, may be forced into involuntary unpaid time off, or be forced into gig/temporary work where they must assume all of the liabilities of being "independent contractors" yet have no legal way of acting as actual entrepreneurs.  

According to the sources cited by Maria Fedina in her essay, up to 85 percent of the Russian labor force faces the possibility of falling into the precariat, while 30 to 40 percent of the labor force belongs to the precariat at any one time.  A large percentage of the Russian precariat consists of highly skilled professionals and highly educated people, having achieved at least a bachelors degree.  However, the prestige of their professions has been devalued in the minds of the Russian public as a tool to force these professionals into precarious, low-wage arrangements.  This is especially true of teachers, as noted in the paper by Volchik, Klimenko, and Posukhova cited above.  Also of note is the fact that a large number of the members of the precariat are involved in the informal economy in Russia, where legal workplace and worker protections are entirely absent.

Precarity is therefore a design feature of the present system of Russian capitalism.  The origins of this system lie with the Russian oligarchs who arose from the wreckage of the crashed Soviet system.  (To see where these oligarchs came from, please read "The Role of Oligarchs in Russian Capitalism," Guriev and Rachinsky, Journal of Economic Perspectives - Volume 19, Number 1, Winter 2005).  These oligarchs controlled betweewn 70 and 90 percent of the Russian economy by the time the transformation to a capitalist society had been completed.  (See "The Piratization of Russia: Russian Reform Goes Awry," F. Joseph Dresen, Wilson Center.)  In the early years of the 21st century, Vladimir Putin used Russian state power to transform these oligarchs into Putin's pillars of support.  (To see the definition of "pillars of support", click here.)  Therefore, the birth and growth of the Russian precariat can be quite accurately seen as part of the goals and policy of the Russian elites both in government and in the private sector.  For their overarching goal is to enrich themselves at everyone else's expense.  And Putin truly has shown himself to be a thieving little man in a bunker.  For when Putin's government arrested (or in many cases killed) those oligarchs who dared to oppose him, it was not to fight corruption, but rather to establish a loyal base of Russia's wealthiest citizens.  The Russian oligarchy is alive and well under Putin (although during the last year they've begun to feel a bit ill.  Sanctions can lead to indigestion . . . ).

For members of the Russian precariat, life has become surprisingly similar to life for members of the precariat in the rest of the developed world.  These include long working hours, an absence of benefits, no guarantee of employment stability, and a refusal of employers to manage the safety and work environments in which their employees must operate.  In an increasing number of cases this has led to deaths of workers and of bystanders, as documented by Katya Zeveleva's piece titled "Russian gig economy violates worker rights with society’s tacit acceptance" (Oxford Human Rights Hub, July 2019).

Russia is but one example of the re-creation of the precariat in a non-Western context.  Next week, we shall consider other cases, God willing.