Summary

In this whitepaper I will use trends from automation and video game revenue models to make the following predictions about the future of low-skill work.

In broad outlines, the argument is that automation and other trends will dramatically increase inequality in technologically advanced countries. Low-skill workers will find themselves largely unemployable in most of their traditional occupations. Meanwhile, ongoing wealth gains at the top of society will increase the ability of privileged people to devote time and money to leisure activities, especially them video games. Big spenders already support the game industry’s current free-to-play revenue model: It only takes a few high-spending players to offset the free access given to anyone who wants to play. The model works because the free players, those who spend no money, make the high-spenders feel better: Their presence in the game creates a real human community. The presence of other people is valuable to the big spenders for several reasons: The thrill of being richer and more powerful than others, yes, but also the simple happiness of companionship. Whatever the reason, big spenders are willing to pay a company enough money that the company can afford to open the doors to anyone. It is a small step from this model to one in which the game company directly pays the underlings for their presence. For the company, the added cost from paying players to come into the game and be relatively poor and underprivileged will be exceeded by the added revenue from big spenders who will enjoy a larger virtual society to befriend (or dominate). The number of players for whom this kind of model makes sense will increase as the 21st century unfolds. The number of real-world low-skill unemployed will increase, and the incomes of the high-skill technocratic elite will rise. In other words, both extremes of the play-for-hire model will grow as automation increases. Within a generation, playing games for money will come to be seen as a legitimate occupational choice for those whose skills are not valued by brick and mortar labor markets. Play-for-hire will become a primary way that the income gains from technological progress will be distributed to the low-skill population.

1 The coming wave of inequality

The technological system within which we live has irresistible imperatives to promote the development of more efficient means of production. Intelligent systems are increasingly deployed to perform work that low-skill humans used to do. At the moment I write, people are no longer employed to handle money, and those who drive vehicles for pay are in the cross-hairs of automated driving systems. It is apparent that most jobs that require little skill will eventually be done by a digital entity.

In the past, the invention of new machines for doing low-skill work caused disruption, but also led to an explosion of new employment opportunities for low-skill workers. In the industrial revolution, automated looms put weavers out of work, but they also created a factory system whose explosive growth provided employment and wages for millions of low-skill workers. It is often overlooked that the industrial revolution caused a population explosion of unprecedented magnitude. That would not have been possible if low-skill people were unable to find work that would feed many new mouths.

When a technological change puts millions of people out of work, a social change must necessarily result, one in which some work becomes available. With the factory system, the work that did become available was dirty, oppressive, harsh, and crushing to the spirit. But it was work. People survived. They survived because, having lost their incomes from farming or weaving or whatever old craft they used to do, they sought about for some way to make money, some way to eat. In the 19th century, they found their way to factories. And so, populations migrated from countryside to towns, cities exploded in size, the urban proletariat was born, and so on and so forth. Automation put people out of work, but those people went off and did something else.

In our current moment we must ask, where will all the drivers go? Forrester predicts that automation will cause a net loss of 7 percent of current jobs over the next decade. That’s just the beginning. If we think about the low-skill people who are about to be displaced, we can wonder, what sort of work will they be able to find? Or, be driven into? Their children will come of age knowing full well that they cannot live by the usual jobs of low-skill people. By what means will these new generations of low-skill workers gather up enough food and housing to stay alive? For if there are any means at all, they will surely seek them and secure them. They will find something to do, something they can do that machines cannot, and that others who have means will pay them for.

Who are those others, the ones with means? They are the people with high skills. As the digital age progresses, there will continue to be high demand for the services of bright people, the creative ones, the emotionally intelligent ones, the best of the best human servants. Entertainers, technicians, engineers, performers of all stripes, will do better and better. Anyone whose special gifts are impossible for a machine to recreate, will find themselves doing very well indeed. And then the other group who will do well, of course, are those who own the machines themselves. Those who own a share of the profits produced by machines will gain income at the same rate that the machines displace low-skill workers. Every time a self-driving car puts a taxi driver out of work, the owner of the car earns more money. Thus there will be three types of wealthy people: Those who own machines, those who design / build / operate machines, and those who provide services that only people can provide.

The system as a whole will get richer and richer. Every time a machine replaces a person, it does so because it is better at the job. It produces more at the same cost, or the same amount at a lower cost. Otherwise, there would be no reason to make the replacement. But this means that each time a machine does a person’s job, the economy as a whole gets richer. More stuff is made at lower cost. Automation is a force for efficiency. It induces economic growth. It makes money. And that money will go to the people at the top, the people with ownership or irreplaceable skills.

Automation thus necessarily induces inequality, at least in the first moment. One man is out of a job, another man makes more money on his assets. But these unequal slices are part of a growing pie. The question becomes, what happens in the second instance - after the driver loses his job, after the car-owner gains more wealth. What happens then? What new social arrangement might happen? Is there some new way that the rich person can hire the poor person? A new system whereby the money of the wealthy moves into the pockets of those who are looking for anything to do in return for money. If the car driver can no longer provide car-driving, can he provide something else?

In the very near future, we will be facing the reality of hordes of low-skill workers with no meaningful work. Indeed, this is already happening. In the late 1970s, 7 percent of men in their 20s with less than a bachelor’s degree did no work at all in the preceding year. In 2015, the number was three times higher, 22 percent. Unpublished research by economists suggests that large numbers of low education young men have abandoned the world of work simply because of the the joys of video game play. Facing a choice between seeking work or staying at home playing games, many young, low-skill men seem to be choosing the games. It is a sign that the real world of work is becoming less rewarding for those with low skills.

2 Options for the low skilled

In the 19th century, low-skill workers went to work in factories. What will they do in the 21st century?

One common idea is that education can change these dynamics. It can’t. It is patently unfair to try to address this problem by pressuring people to go to engineering school. For surely all this will do is start an arms-race among high-skilled workers. If the technological economic system requires only 10 percent of the workforce to operate at full capacity, then only 10 percent of the workforce will be employed as operators. Training up millions more people to have the necessary operating skills will only unleash a vicious competition among them, driving down the wages of those who do get the jobs. Consider: If you have 100 people whose skill is ranked from 0 points to 100 points of ability, and you will hire only the top 10, it does not help anybody to teach them all 5 more points of skill. You will still only hire the top ten, the people with skills from 95 points to 105 points.

Skilling up the workforce only makes sense if there will be an increased need for high-skill people. But the dynamic of technological explosion in which we live is such that for every new high-tech job that is created, two lower-tech jobs will be destroyed. This is simply because people are more expensive than machines. The system will do everything in its power to get its work done with the minimum number of people. It is going to try to shed people whenever and wherever it can. Teaching low-skill people to be somewhat better technicians than they currently are is a losing strategy for them.

Instead, we must think of other ways that a low-skill person can do paid work for others. What kinds of things can low-skill people do that machines simply cannot? This question forces us to unpack the concept of “low skill.” What we really mean, by now, is that low-skill people are the ones that machines can replace. They are currently working in a way that a machine can do. Whatever is special and unique about human thinking, whatever we have that machines cannot have, may well be present in the minds of the “low skill” workers; but right now, that special sauce is not a part of their work. “Low skill” workers may have high skills, at something; but the work they do today is work that a machine will be doing soon enough.

If “low skill” workers are becoming defined as “those whose jobs will be automated,” it follows that if those people are to survive, are to eat, they must bring up within themselves, and express to the world, some set of skills that cannot be automated. It also follows that the term “low skill” applies to a lot more of us than would have been expected under traditional definitions of the term.

Earlier I argued that the only people who will be compensated in the automated future are a) those who own machines, b) those who operate machines, and c) those who perform services that only people can perform. If the “low-skill” displaced masses do not own machines and are unable to become operators, only one avenue of compensation is open to them: Service.

The question is, what kind of human-only services can low-skilled people provide, in massive numbers? For there will surely be huge masses of displaced low-skill people. The answer here is not going to be tennis instruction or lawn care. In the future we are facing, if every rich person had 10,000 butlers and maids, it would still not be enough employment. The technological disruption will therefore drive some kind of huge social disruption, that creates new ways for a few privileged people to move income toward massive numbers of the technologically unemployable population.

3 “Low skill” people can play games

All of us can play video games, regardless of skill. The game industry excels at creating systems in which both angry lawyers and stoned teenagers can make their way. Games offer a range of skill challenges, by design. Games are designed so that all the players have fun, including those whom the outside world would call “low skill.”

Skill effects within games are tightly managed by the designers. Designers make acutely conscious choices about when, where, and how the real-life cognitive and physical skills of the players will have an influence on game outcomes. Games are now designed to adjust dynamically and automatically to the perceived abilities of the players. Is this player dying quite a lot? Remove some of the zombies. Not dying enough? More zombies! It could be argued that games are designed to reward skills that the market finds less valuable, precisely in order to capitalize on the way people feel underappreciated. The point is that whatever the outside world may think of skills, game design seeks ways to make every player appreciated, regardless of skills.

Designers also carefully manage when, where, and how the real-life monetary resources of the players can affect the game. In many games, it is possible to spend extra money to get a better sword, or more life potions, or unlock a faster horse or a new level. Whereas in other games, no amount of outside money can affect what you can achieve in the game.  

Designers manage skill, money, and time as well: Some players have quite a lot of time to spend in a game, others don’t. It is up to the designers how long it takes to achieve things in the game.

As a result of these designer decisions, the game industry finds itself unwittingly serving as a vast global agora of skills, time, and money. Designers can increase or decrease the impact of player skill, money, and time input, and in so doing they give their games a certain profile. Different games appeal to different players. Players can move from game to game, according to their resources and tastes.

Some games are so big in scope, time length, and space that they can accommodate widely different types of players. Different parts of a single game may appeal to the skill-rich, the money-rich, and the time-rich. This is seen most clearly in the free-to-play revenue model. A game run on the F2P model opens its doors to anyone. Anyone can play the game, free of charge. At some point, however, some aspect of the game either requires or encourages payment. Perhaps the game has 100 levels, and the first 50 are free. You have to pay to unlock the other 50. Or the game has 100 levels, all completely free, but it takes two years to get to level 100, unless the player buys some sort of special equipment. F2P games make money by charging for extra game features.

The free to play model has exploded across the industry in the last decade. It has turned out to be fabulously lucrative. A free game has the lowest possible barriers to entry, and can quickly gain a large population of players. Those players create buzz and excitement; they confirm to the world that it is a good game. Production costs are such that even if only a fraction of players ever pay for something, the revenues gained far exceed the costs of providing the game free to all the others.

It is understood colloquially among game designers that the revenues of F2P games follow the same patterns as casinos, in that a few big spenders are enough to make the casino turn a profit - even if you give free drinks to hundreds of low-spending people. These big spenders are known as “whales.” The game industry has whales as well. There are people who spend thousands of dollars every month on the most trivial of game items. A very large portion of revenues are provided by a small percentage of the player base. Gamasutra reports that less than one-fourth of one percent of F2P players generate almost half the revenue. “Conversion rates” - the percentage of players who spend any money at all - can be as low as 3 percent or 1 percent, yet the game still turns a profit. The free spending of a few is sufficient to support the game.

What then is the role of all the other players? What purpose is served by all those people in the casino who drink their free drinks and gamble away comparatively tiny amounts of money? Those people are a critical part of the revenue model, for they form the social environment within which the whale can make friends, and compared to whom the whale looks like the awesome person he wishes to be. Without the free-drink gamblers, the casino whale has nobody to talk to and nobody to impress with his casino privileges and private rooms. The same holds for F2P games: Without the free gamers, the spending gamer has nobody to talk to and nobody to impress.

Thus there are two elements that explain why big spenders will provide revenues to companies that alow free access: A communion aspect and a comparison aspect. The communion aspect is easily enough understood: Rich people get lonely too, and a thriving game community gives them a social world for making friends. The comparison aspect is a little more complicated, so let’s unpack the social dynamics of a F2P game. Consider three ways that a person might spend real money.