There are a lot of fears that technology of various sorts is going to reduce the need for human labor to a point where we may need to provide universal basic income, reduce the work week radically, and/or have mass unemployment.
I have a different take on where things are headed.
I think we are undergoing a radical productivity gain in certain aspects of certain jobs. This will lead to lots of dislocation for the workers who are effected by it. It will in cases be gruesome in the short term.
At the same time I think there will not be enough productivity gain in many parts of the world to compensate for an aging population and lower immigration rates. I am worried about a loss of standard of living because we will have too few human workers.
But in any case, we are going to have to change the relative value of some sorts of work that almost any person could do if sufficiently motivated. We will need to re-evaluate the social standing of various job classes, and encourage more people to take them up.
The politics are going to be nasty.
I think that most of the disruption that is coming is from digitalization. Note that this word has one more syllable than digitization, and the two words have different meanings. Worse than that, though, there is some disagreement on what each of these words mean. I will define them here as I understand them and as how I see more interesting writing using them.
Digitization is the process of taking some object or measurement, and rendering it in digital form as zeros and ones. Scanning a paper document to produce a .pdf file is the digitization of the visible marks on the paper into a form that can be manipulated by a computer; not necessarily at the level of words on the paper, but just where there is ink versus no ink. In automobiles of an earlier age the steering wheel was mechanically linked to the the axles of the front wheels so there was a direct mechanical coupling between the steering wheel and the front wheels of the car. Today the position of the steering wheel is digitized, the continuous angle of that wheel controlled by the human driver, is constantly turned into a very accurate, but nevertheless still approximate, estimation of that angle represented as string of zeros and ones.
Digitalization is replacing old methods of sharing information or the flow of control within a processes, with computer code, perhaps thousands of different programs running on hundreds or thousands of computers, that make that flow of information or control process amenable to new variations and rapid redefinition by loading new versions of code into the network of computers.
Digitization of documents originally allowed them to be stored in smaller lighter form (e.g., files kept on a computer disk rather than in a filing cabinet), and to be sent long distances at speed (e.g., the fax machine). Digitalization of office work meant that the contents of those digital representations of those documents were read and turned into digital representations of words that the original creators of the documents had written, and then the ‘meaning’ of those words, or at least a meaning of those words, was used by programs to cross index the documents, process work orders from them, update computational models of ongoing human work, etc., etc. That is the digitalization of a process.
Likewise in automobiles, once every element of the drive train of a car was continuously being digitized, it opened the possibility of computers on board the car changing the operation of the elements of the drive train faster than any human driver could do. That enabled hybrid cars, and eco modes even in all gasoline engines, where the drive train can be exquisitely controlled and the algorithms updated over time. That is digitalization of an automobile.
Where is the productivity gain coming from?
Let’s look at an example of where digitalization has come together to eliminate a whole job class in the United States, the job of being a toll taker on a toll road or a toll bridge.
The tech industry might have gone after this particular job by building a robot which would take toll tickets (they were used to record where the car entered a toll road), and cash, including crumpled bills and unsorted change, from the reached out hand of a driver, then examined exactly what it was given, and finally returned change, perhaps in a blowing wind, to the outreached hand of the driver. This is what human toll takers routinely did. To be practical the whole exchange would need to happen at the same speed as with a human toll taker–toll booths were already the choke point on roads and bridges.
It would have been a very hard problem and today’s robotics technology could not have done the job. At the very least there would have had to be changes to what sort of cash could be given; e.g., have the human throw coins into a basket where it gravity fed into a counter. If it was required to accept paper cash that would be very hard, as the human is not in an ideal situation to feed the bills into a machine, and with wind, etc., it would have been a very difficult task for most people.
Instead the solution that now abounds is to identify a car by a transponder that it carries, and or reading its license plate. The car does not have to slow down and so there is an added advantage of reducing congestion.
However, this solution relies on a whole lot more digitalization than simply identifying the car. It relies on there being readable digital records of who was issued what transponder, who owns a car with a given license plate if the car has no transponder, web pages where individuals can go and register their transponder and car, and connect it to a credit card in their name, the ability for a vendor to digitally bill a credit card without any physical presence of the card, and a way for a consumer to have their credit card paid from a bank account electronically, and most likely that bank account having their wages automatically deposited into it without any payday action of the person. There is a whole big digitalized infrastructure, almost all of which was developed for other purposes. But now toll road or toll bridge operators can tap into that infrastructure and eliminate not just toll taker jobs, but the need to handle cash, collect it from the toll booths, physically transport it to be counted, and then have it be physically deposited at a bank.
This solution is typical of how digitalization leads to fewer people being needed for a task. It is not because one particular digital pathway is opened up. Rather it is that an ever increasing collection of digitalized pathways are coming up to speed, and for a particular application there may be enough of them, which when coordinated together in an overall system design, that productivity can be increased so fewer humans than before are needed in some enterprise.
It is not the robot replacing a person. It is a whole network of digitalized pathways being coordinated together to do a task which may have required many different people to support previously.
Digitalization is the source of the productivity increase, the productivity dividend, that we are seeing from computation.
Digitalization does not eliminate every human task, certainly not at this point in history. For instance any task that requires dexterous physical handling of objects is not made easier by digitalization. Perhaps the overall amount of dexterous manipulation can be reduced in a particular business by restructuring how a task is done. But digitalization itself can not replace human dexterity.
As an example think about how fulfillment services such as Amazon have changed the retail industry. Previously goods were transported to many different retail outlets, often just a few miles apart across the whole of the country, were arranged on shelves by stockers for consumers to see, and then they were handled by retail workers when a consumer was buying the object, taking it from the consumer to be scanned (in the olden days that step had not yet been digitalized, and instead at the point of sale the retail clerk had to read the price, and reenter it into some machine), put in a bag or box, and handed back to the consumer. And in between, retail workers had to retidy the shelves when consumers had looked at the goods, picked them up, and then put them down again without making a purchase. There were many, many dexterous steps in the path of a particular object from the factory to the consumer.
Today there are much fewer such steps, and many fewer workers who touch objects than before. Consumers purchase their goods from a web page, and the same digitalized payment chain that is used for toll roads is used to settle their accounts. The goods are taken to just a very few fulfillment centers across the country. Stocking the shelves there is done only once, and there is no need to tidy up after customers. Then the objects are picked and packed for a particular order by a human. After that the manipulation of the consumer goods is again done only in single rectanguloid boxes for the whole order of many good–much easier to manipulate. Robots bring the shelves to the picker, and take the boxes from the packer. There is much less labor that needs to be done by humans in this digitalized supply chain. Unlike the toll taking application there is still a dexterous step, and that is not yet solved by digitalization.
Increasingly digitalization is making more tasks more human efficient. Less people are needed to provide some overall service than were needed before. Sometimes digitalization replaces almost all the people who where necessary for some previous service.
Increasingly digitalization is replacing human cognitive processes that are routine and transactional, despite in the past them requiring highly educated people. This includes things like looking at a radiological scan, deciding on credit worthiness of a loan applicant, or even constructing a skeleton legal document.
Tasks that are more physical, even where they too are transactional, are not being replaced if they involve variability. This includes almost any dexterous task. For productivity increases in these cases the need for dexterity needs to be eliminated as our machines are not yet dexterous.
Likewise if there is a task step that absolutely involves physical interaction with a human that also is likely not yet ready to be eliminated. Large parts of elder care fall under this–we have no machines that can help an elderly person into or out of bed, that can help an unsteady elderly person get onto and off of a toilet, can wash a person who has lost their own dexterity or cognitive capability, can clean up a table where a person eats, or even deliver food right to their table or bedside.
Hmm. Not many of these things sound like tasks that lots of people want to do. Nor do they pay well right now. I assume many of these tasks will be hard to get robots to do in the next thirty years, so we as a society, with the support of our politicians, are going to have to make these jobs more attractive along many dimensions.
Where is the productivity gain going to?
First, a disclaimer. I am not an economist.
Second, an admission. I won’t let that stop me from blathering on about economic forces.
Now, to my argument.
The United States, from when it was an unfederated collection of proto-states, through to today, has relied on low cost immigrant labor for its wealth.
In the early days the “low paid” immigrants were brought, against their will, as human slaves. Thankfully those days are gone, if not all the after effects. There has also always been, up until now, a steady flow of “economic refugees”, coming to the United States, and taking on jobs that existing residents were not willing to do. In recent times a distinction has been made between “legal” and “illegal” immigrants. More than 10 million so called “illegal” (I prefer “undocumented”) immigrants currently live in the US and often they are exploited with lower wages than others would earn for the same work, as they have very little safe right of appeal. Now, in the United States, and many other countries, there has been a populist turn against immigrants, and the numbers arriving have dropped significantly. A physical wall has not been necessary to effect this change.
So, the good news is that now, just as we collectively have scared off immigrants who we can exploit1 with low wages, digitalization is coming along with a productivity bonus, which may well be able, in magnitude at least, plug that labor deficit which is about to hit us. With luck it will even also compensate for the coming elder care tsunami that is about to hit us– in a previous blog post I talked about how this is going to drive robotics development.
The big problem with this scenario is that there is by no means a perfect match between the skills gap demand that both reduced low cost immigrant labor and the need for massively increased elder care and services will drive, and the skills productivity that digitalization will supply.
There is going to be a lot of dislocation for a lot of people.
I am not worried at all that there will not be enough labor demand to go around. In fact I am worried that there still will not be enough labor.
And another piece of “good news” for the dislocated is that the unfilled jobs will not require years of training to do. Almost anyone will be able to find a job that they are mentally and physically capable of performing in this new dislocated labor market.
Easy for me to say.
The bad news is that those jobs may well not seem satisfying, that they will not seem as status admirable as many of the jobs that have disappeared, and that many of these jobs would, in our current circumstances, pay much less than many of the jobs that will have disappeared.
To fix these problems will require some really hard political work and leadership. I wish I could say that our politicians will be up to this task. I certainly fear they will not be.
But I think this is the real problem that we will face. How to make the jobs where we will have massive unfulfilled demand be attractive to those who are displaced by the productivity of of digitalization. This is in stark contrast to many of the fears we see that technology is going to take away jobs, and there just will not be any need for the labor of many many people in our society.
The challenge will really be about “different jobs”, not “no jobs”. Solving this actual problem, is still going to be a real challenge.
I have not used the term AI
I have not talked about Artificial Intelligence, or AI, in this post.
I was recently at a conference on the future of work, and AI was the buzz word on everyone’s lips. AI was going to do this, AI was going to do that, there was an AI revolution happening. Most of the people saying this would not have heard of “AI” just three years ago, despite the fact that it has been around since 1956. I realized that the phrase “Artificial Intelligence”, or “AI”, has been substituted for the word “tech”. Everything people were saying would have made perfect sense three years ago with the word “tech” rather than today’s “AI”.
In this post I have talked about digitalization. I think that is the overall thing which is changing. Certainly, real actual AI, machine learning (ML), and other things that people understand as AI are going to be able to be deployed more quickly because of digitalization. So that is a big deal. But lots of the productivity gains from digitalization will not particularly rely on AI.
That is, unless we redefine AI as being a superset of any and every sort of digital tech. I am not ready to do that. Others may already be doing it.