In a brief essay, Anton Howes asks: “Is innovation in human nature?” That is to say, do people have some natural stock of innovative capacity, waiting to burst forth when conditions are right? By way of anecdote, Howes’ answer is: not really. He pushes back against the idea that the industrial revolution took place merely because the economic conditions were suitable for one: “The more I study the lives of British innovators, the more convinced I am that innovation is not in human nature… People innovate because they are inspired to do so. And when people do not innovate, it is often simply because it never occurs to them to do so. Incentives matter too, of course. But a person needs to at least have the idea of innovation—an improving mentality—before they can choose to innovate.”

Let’s ask more generally: What are the factors that drive economic growth? If we pull out and dust off our econ textbooks, we’ll read that growth is a function of higher investments, spending, trade, productivity, and so on. They can be broken down into ever more abstract categories, but technical enough that we can measure them to two decimal points and above. Howes’ framing prompts me to bring up some questions I was too dumbfounded to pose in four years of econ classes: How do beliefs about the future affect long-term economic growth? What role do optimism and pessimism play? How important are imagination and drive to growth?

And most of all: Why do we treat innovative capacity as some kind of fixed stock, constant across time and between countries, ready to be activated as soon as policymakers have finally gotten around to legislating the right conditions in place?

I’ve come to the view that creativity and innovative capacity aren’t a fixed stock, coiled and waiting to be released by policy. Now, I know that a country will not do well if it has poor infrastructure, interest rate management, tax and regulation levels, and a whole host of other issues. But getting them right isn’t sufficient to promote innovation; past a certain margin, when they’re all at rational levels, we ought to focus on promoting creativity and drive as a means to propel growth.

I wonder if economists overrate the easier-to-observe policy factors and under-theorize the idea that positive visions of the future drive long-term growth. To put it in a different way, I wish that they would consider definite optimism as human capital. In addition to education levels, human capital models should consider factors like optimism, imagination, and hope for the future.

When I say “positive” vision, I don’t mean that people must see the future as a cheerful one. Instead, I’m saying that people ought to have a vision at all: A clear sense of how the technological future will be different from today. To have a positive vision, people must first expand their imaginations. And I submit that an interest in science fiction, the material world, and proximity to industry all help to refine that optimism. I mean to promote imagination by direct injection.

***

Let’s start with the capacity of science fiction to improve imagination. One way of having a better idea of the technological future is to first read about one in a book or see one on screen.

Alas, for some reason, science fiction movies have taken a bleak turn in the last few decades. The dominant mode in modern sci-fi movies is dystopia, and perhaps even nihilism. Today, the contrarian project is to present an earnest, joyful vision of the technological future. That kind of undertaking will invite mockery from commentators posting essays on Medium, but one can hope that younger, less jaded people will find attractive that daring imagination.

If I had funding and access to studio talent, I would reshoot a bunch of films. Elysium, with a focus on the logistics behind the smooth functioning of a satellite habitat. Ex Machina, featuring an artificial intelligence whose greatest desire is not acceptance in human society. Gravity, with greater marveling of space and the desire to explore, not the aftermath of random mechanical failure. Her, in which artificial intelligences decide to improve humanity, instead of migrating en masse to a higher spiritual plane. Star Wars with no wars and no Jedis—and therefore no Sith—that instead draws out the gains from interstellar exchange under oversight of the Trade Federation. (Bonus points for working out rules that would govern countervailing duties and state procurement under a galactic trade regime.)

I confess I don’t know how to make these stories exciting. Doesn’t it sound though like an exciting challenge for the creative type? It is so conventional these days to watch yet another movie about how robots attempt to wipe out humanity, but ultimately fail, because they’re missing some essential soulful touch. So let me provide prompts to the enterprising screenwriter: What might society look like if we had energy too cheap to meter? If artificial intelligences must be otherworldly, how about we present them as angels of Rilke come down to Earth? When humanity manages to become a solar civilization, can we depict the inventions we need to colonize various moons and planets? How about the logistics of how colonies trade?

Books are less uniformly dystopian. I loved two that I read in the past year: *Seveneves* by Neal Stephenson and *The Three Body Problem* by Liu Cixin. Both present definite optimistic visions of the future: Calamity threatens humanity; but it allows some time for humanity to prepare; and humanity uses this time to plan out the technological future. It more or less fulfills what it set out to do, and for the most part people triumph over their threats. I am delighted by the theme of people working hard to overcome existential challenges.

And I hope that many more authors and directors get into this genre. Let’s have more movies and books that look forward to the technological future.

***

Economists tend to be dismissive of arguments for industrial policy. I usually agree with their arguments, but today I want to stick up for one potentially positive aspect: That manufacturing and engineering work can improve imaginative capacity through exposure to industrial processes. I sympathize more often with those who lament the decline of the US industrial base because I think that more people should have greater proximity to the world of manufacturing and engineering.

(A bit of context: According to FRED’s measure, the number of people employed in manufacturing peaked at nearly 20 million in 1979; that figure is slightly above 12 million today. As a share of working age population, that’s a decline of 14 percent in 1979 to 6 percent today. That decline in headcount has not translated to a decline in total output. Today, manufacturing output in real terms is higher than ever before. But it’s worth noting that the figure collapsed after 2008, and is now only a shade higher.)

The fewer the manufacturing workers and engineers, the more removed everyone is from the particulars of industrial processes, and the more remote that knowledge becomes in each successive generation. We become think tankers and app designers and restaurant hosts, while the details of the industrial world become further and loftier abstractions. How many of our grandparents were familiar with the details of ball bearings, wire production, concrete mixing, industrial chemicals, while we are not?

I regret this abstraction of the material world. Most of our living standards are tied to the world of atoms. Even when we spend a lot of time online and on our phones, we go to work in cars and subways; keep ourselves warm and cool using machinery and electricity; surround ourselves with objects that let us cook or relax; and on and on. The online world is not entirely free of the material world. Our phones require aluminum and rare earths and silicon chips; the internet is powered by cables that run under our streets and beneath the oceans; we mine our bitcoins with a great deal of electricity.

Manufacturing work tends to be hazardous or unpleasant in all sorts of ways. But it’s also associated with faster productivity growth and the greater possibility of technological upgrading. Here’s Andy Grove: “Abandoning today’s commodity manufacturing can lock you out of tomorrow’s emerging industry.” If a country gives up on manufacturing too early on, even if it’s very low value-add stuff, it also loses all the tacit knowledge and design expertise from a workforce familiar with industry. The US continues to retain the highest value-add work of R&D and marketing in many sectors; but a lot of the scaling expertise, supplier networks, and supply chain knowledge have dispersed to other shores. I predict over the long term that diminishes the country’s capacity to have the labor force ready to take advantage of scaling up a big, innovative technology; and it slightly reduces the chances that the country will have the talent to create it.

If a state has lost most of its jobs for electrical engineers, or nuclear engineers, or mechanical engineers, then fewer young people in that state will study those practices, and technological development in related fields slow down a little further. When I bring up these thoughts on resisting industrial decline to economists, I’m unsatisfied with their responses. They tend to respond by tautology (“By definition, outsourcing improves on the status quo”) or arithmetic (see: gains from comparative advantage, Ricardo). These kinds of logical exercises are not enough. I would like for more economists to consider a human capital perspective for preserving manufacturing expertise (to some degree).

***

I wonder if the so-called developed countries should be careful of their own premature deindustrialization. The US industrial base has faltered, but there is still so much left to build. Until we’ve perfected asteroid mining and super-skyscrapers and fusion rockets and Jupiter colonies and matter compilers, we can’t be satisfied with innovation confined mostly to the digital world.

Those who don’t mind the decline of manufacturing employment like to say that people have moved on to higher-value work. But I’m not sure that this is usually the case. Even if there’s an endlessly capacious service sector to absorb job losses in manufacturing, it’s often the case that these new jobs feature lower productivity growth and involve greater rent-seeking. Not everyone is becoming hedge fund managers and machine learning engineers. According to BLS, the bulk of service jobs are in 1. government (22 million), 2. professional services (19mn), 3. healthcare (18mn), 4. retail (15mn), and 5. leisure and hospitality (15mn). In addition to being often low-paying but still competitive, a great deal of service sector jobs tend to stress capacity for emotional labor over capacity for manual labor. And it’s the latter that tends to be more present in fields involving technological upgrading.

I read occasional arguments that liberal societies need to have a healthy level of engagement with its armed forces, or they risk revering but not understanding the military. I’d like to make a similar appeal for manufacturing. Until our world is much better built-up than the present, it’s too early to accept the diminishment of an industrial base, by which I mean little growth in output accompanied by a decline in the workforce. At a time when more tech companies are offering digital tools to industry, we should expect the number of people jumping in to take advantage of them to be increasing, not decreasing.

It’s sad that DuPont’s excellent slogan “Better living through chemistry” has been ironically twisted from a celebration of chemicals and plastics to enjoyment of recreational drugs. How far along is humanity in its progress toward its bright technological future? I submit that we’re less than 3 percent of where we should ultimately be. Let’s worry about premature deindustrialization in the developed world as well.

***

Here’s a bit more skepticism of service jobs. In an excellent essay on declining productivity growth, Adair Turner makes the point that many service jobs are essentially zero-sum. I’d like to emphasize and elaborate on that idea here.

There are plenty of service jobs that are meant to cancel out the efforts of other service jobs. One firm spends a few million dollars to hire a dozen ad agencies to convince you to purchase its car insurance policies; another firm hires a different dozen agencies and puts out other ads. One firm or person decides to sue another, creating the need for two sets of lawyers. One candidate attempts to raise a hundred million dollars to win an election, and the other side has to do the same, and meanwhile only one can win.

Worse, the zero-sumness is often asymmetric. A dozen hackers make a theft, and suddenly companies everywhere need to spend collective billions on staff or outside agencies to protect themselves. A few criminals plague a state, and suddenly the government needs to hire hundreds of officers to make people feel safe; or border agents and wall builders if it turns out the criminals were aliens. A few dozen people commit accounting fraud, and the ensuing uproar forces companies and banks to ramp up the size of their compliance departments by the tens of thousands.

Although manufacturing jobs can be wasteful, I don’t think it has this issue of being zero-sum.

I noted in my computer science piece that two of the big growth areas of US bachelors degrees have been healthcare and law enforcement. Much of the marginal growth has to deal with compliance—after all, in health care at least, the growth of new doctors has not accelerated. In addition, a lot of the marginal growth in financial services and higher education appears to be compliance-related as well.

Some of that is prompted by legislation. Without passing judgment on the overall merits of these new policies, I find them to be pretty remarkable as jobs programs. It almost feels like developed countries have shifted the focus of industrial policy to service jobs. If this was the principal aim of US policymakers, I find impressive that they’ve pulled this off in response to deindustrialization. Congress rises in my estimation.

Healthcare and finance are both high-margin industries, and I wonder if Congress will find another to take a more active role as a jobs provider. Technology, perhaps? Maybe something like hiring people to keep newsfeeds and search results free from dangerous content or fake news. In fact that’s something that sounds like it could well receive bipartisan support.

***

A Bloomberg piece prompts some of my questions about definite optimism and human capital. The current unemployment rate in Japan is 2.8 percent. Japanese millennials get to enjoy a fairly tight labor market, which means they ought to have their pick of company to work for. But few of them have an interest in switching jobs, because they want not high wages but perfect stability. The article attributes this risk aversion to lingering fears of the previous downturn. The country that lost a decade—or maybe two—has fostered a generation of youth highly averse to risk-taking. (Elsewhere in Bloomberg headlines: “Japan has the world’s gloomiest millennials.”)

By contrast, the article quotes a recruiter who says that China has a “fearless” employee base. When recruiters come around promising higher wages, Japanese millennials keep their heads down, while young Chinese are willing to try something new. Given that two generations of Chinese have never experienced recession, it might be that job hops don’t even feel like a risky move; there ought always be another opportunity waiting around the corner, so why not try something out for fit?

That theme dovetails into another of my recent pieces. I think it’s a puzzle that relatively few people major in computer science given how lucrative it is. After I wrote my piece, a great number of people responded that I’ve been focusing on the hangover of the 2001 dotcom bubble. Let’s say they’re right, i.e. the bubble drove a lot of people away from majoring in CS, such that the number of graduates in 2001 wasn’t surpassed until 2014. I see this as a pessimistic interpretation. It means that it took nearly 15 years for the number of graduates to recover to a previous high after a single, brief recession. (Meanwhile, the share of graduates remains below its ’01 high, because many more people are earning bachelors degrees today.)

It’s worrying that a recession was able to do all that. How many fewer startups have been founded, how many larger companies could have been better staffed, how many more VCs could have generated higher returns for LPs, if the field didn’t have to deal with this talent constraint caused by a brief recession? The lesson of both Japanese millennials and CS grads is that recessions leave deep psychological scars that hurt risk appetites for a much longer time than the downturn itself.

That lesson comes to mind when I read Andrew Batson on the hypothetical tradeoff between short-term and long-term growth in China. He suggests that in principle, it’s possible that China’s much-criticized debt-fueled stimulus policies are not hurting long-term income growth as much as people fear: “Officials could argue they do not need to spend time worrying about measures that might damage long-term productivity growth, since no one really knows what causes long-term productivity growth anyway, and are right to focus on preventing deep and damaging cyclical downturns.”

It’s straightforward to measure a recession’s effects on employment and output. But what if the psychological impact of a recession is much more severe than we thought, to the extent that it could make a dent in long-term productivity growth? If we accept the idea that recessions linger in the form of psychological scars, lower expectations, and greater risk aversion, then it makes more sense to do a lot to avoid them. And it weakens the Austrian case for recessions as healthy corrections that improve capital allocation, because they cause a great deal of unseen harm as well. If we treated definite optimism as a function in human capital and productivity growth, then we could be slightly more rigorous in considering the broader effects of recessions.

***

I submit that an underrated Trump phenomenon is how many people have been drawn to care about political scandal. I haven’t much changed the people I follow on Twitter, but my feed has gone something like 25 percent politics to 60 percent politics; I don’t have a Facebook, and I suspect that something similar happens there as well. So many people have become addicted to retweeting the very latest Trump embarrassment, or making identical jokes about it.

But what could be more boring?

This is the social risk: That the minds of many talented young people today will be permanently disfigured by this obsession with Trump embarrassments. The effect will persist when Trump is no longer in office. By that time, people will still be hypersensitive to whatever political news is happening at the moment, as they’re glued to social media looking for breaking jokes. Some people expressed this fear when George Bush was in the White House. I submit that it’s much more severe today: It’s Donald Trump, plus social media, and more cable news, in the midst of a flowering meme culture.

I confess guilt to taking pleasure in some of these memes myself. But I realize the glee is an unhealthy one, and that I have to break it before it breaks me. I entreat more people to consider their news consumption in these terms—most of us do not need to pay attention to the day-to-day goings on in the political world. There are too many sites and personalities that have completely re-oriented themselves to telling people how they ought to feel about the latest piece of news. I don’t blame them, because I think they’re delivering what we want. But we can change our preferences.

Call me a romantic, but I’d like everyone to think more about industrial lubricants, gas turbines, thorium reactors, wire production, ball bearings, underwater cables, and all the things that power our material world. I abide by a strict rule never to post or tweet about current political stuff; instead I try to draw more attention to the world of materials. And I’d like to remind people that there are many things more edifying than following White House scandals.

***

Let me be concrete. I have two suggestions on how to take on greater definite optimism to think more about technological future:

First, we can all try to engage more actively with the material world, not merely the digital or natural world. Go ahead and pick an industrial phenomenon and learn more about it. Learn more about the history of aviation, and what it took to break the sound barrier; gaze at the container ships as they sail into port, and keep in mind that they carry 90 percent of the goods you see around you; read about what we mold plastics to do; meditate on the importance of steel in civilization; figure out what’s driving the decline in the cost of solar energy production, or how we draw electricity from nuclear fission, or what it takes to extract petroleum or natural gas from the ground.

To be a bit more future-looking, consider what the technological civilization ought to look like in the year 2300. Then figure out what kinds of theoretical and practical breakthroughs people need to solve in the near future before we get to that stage.

Second, we should ask for more direct, unironic celebrations of innovation in popular culture. That means, for example, shooting more science fiction movies that are not fixated on the ways that technology will kill us all. Let’s see more examples of invention, exploration, and risk-taking in film. And also more images of what the world of tomorrow will look like.

It might be a good philanthropic undertaking to create exciting visions of the future. I humbly beg the various generous people who open up their pocketbooks to also consider funding culturally exciting projects. I’d like the altruistic millionaires and billionaires to step up funding of movies, books, World Fairs, murals, memes, whatever, to expand our imagination. More art, say, that depict societies of the future, like so much of what we had previously. Or focus the World Fairs to once again showcase applications of cutting-edge technologies. Or figure out how to make cool videos of industrial processes that people are happy to watch online.

Perhaps the mighty industrialists and financiers who steer so much money towards think tanks to promote their goals can consider culture more often. Fewer op-eds on how people should feel about upcoming legislation; instead, more creation of cultural products that get people excited about the technological future. These kinds of efforts to promote definite optimism, rather than a continuous focus on never-ending political battles, might result in greater economic growth in the long run.

***

It’s time to synthesize this piece with my previous. That was about the destructive results that follow when we keep our gaze fixed on the people around us, instead of towards our own goals. When we get sucked into Girardian dynamics, people get too competitive, always trying to one-up another in the group, until they reach places that look totally extreme to the outside world. The way to avoid this Girardian conflict is to direct our gaze outwards to the tangible things of the world.

When we all have different things to be interested in, we can avoid the narcissism of small differences. I’m hopeful that greater interest in the industrial world would decrease the amount of Girardian conflict in society, because manufacturing and engineering have so many different niches. It’s not the only one, however. The essay is in part an exhortation that the world has many interesting things to focus on instead of each other.

Here’s one more point that I’d like to add on Girard at college: I wonder if to some extent current dynamics are the result of the liberal arts approach of “college teaches you how to think, not what to think.” I’ve never seen much data to support this wonderful claim that college is good at teaching critical thinking skills. Instead, students spend most of their energies focused on raising or lowering the status of the works they study or the people around them, giving rise to the Girardian terror that has gripped so many campuses.

That makes me wonder if encouraging creativity and critical thinking skills is possibly overrated at current margins. Ian Leslie’s book, Curious, makes the point that we shouldn’t be so pleased to offload so much of our memory to search engines, such that the most key skill is learning how to Google instead. So I’m starting to better appreciate the Leninist system of education in France and China, in which children are endlessly stuffed with information (especially in technical subjects) and then sorted through rounds and rounds of examinations. Kids may develop critical thinking skills more easily if they have a vast base of knowledge to work with, when they’ll be able to make connections of facts on their own, instead of being taught some interesting rules and not enough content to practice them. But I throw this out as a hypothesis, not as a strong conviction.

Here is an illustration of a satellite habitat from Seveneves.

***

A few last thoughts:

An excellent objection to my points about manufacturing is that many parents worked darn hard to make sure their kids didn’t take the same kinds of jobs, and told them as such. I concede once more that much of the work is unpleasant and hazardous. Still, at some margin, there could be too little encouragement to enter the field, especially through not knowing many people not in services. I wish that the mix of adults that a high school student can expect to be exposed to include more manufacturing workers and engineers.

The digital world is indeed a lot of fun, and it’s entirely wrong to deny that the sector has been innovative. Still, I wish to remind people that changes in the physical world drive a lot of living standard improvements. Given how many people struggle in low-end jobs, and how quickly a few major expenditures are getting more expensive, reminders that the internet is really good smacks today of “Let them eat iPhones!”

It’s striking how much Neal Stephenson’s novels maintain the importance of the material world. It’s not all digital wonder for him. I chuckled at the bit in Seveneves in which Stephenson blamed social media for civil disorder, cannibalism, and general social collapse.

I wouldn’t change much about The Martian movie. More like it, please. I’m cautiously optimistic for the movie adaptation of the Three Body Problem, due to be out later this year. There’s no way it can be as good as the book. But the series is driven by a fundamentally optimistic vision, and that’s refreshing. And instead of an alien civilization that’s 70 or 80 percent more advanced than humans, it asks why aliens should not be 10,000 times more advanced than humans. That’s fun to wonder about.

Stephenson’s Project Hieroglyph sounds like a great idea, I wish that there were more institutions like it: “Inspiration is a small but essential part of innovation, and science fiction stories have been a seminal source of inspiration for innovators over many decades. In his article entitled “Innovation Starvation,” Neal Stephenson calls for a return to inspiration in contemporary science fiction.” But it doesn’t seem to be very active. Anyone know if it’s still an ongoing concern?

The most important essay I read in the last month is by Lant Pritchett. He asks why the scarcest economic resources—entrepreneurial ability and technical talent—are going into automating an abundant resource: cheap labor. In the developed world, labor is expensive because of policy restrictions, and it is neither efficient nor equitable to use scarce technological talent to displace globally abundant workers.

Please my followup essay: How Technology Grows

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Give a man a computer program to frustrate him for a day; teach a man computer programming, and frustrate him for a lifetime.

– ancient proverb

In 2005, about 54,000 people in the US earned bachelor’s degrees in computer science. That figure was lower every year afterwards until 2014, when 55,000 people majored in CS. I’m surprised not only that the figure is low; the greater shock is that was flat for a decade. Given high wages for developers and the cultural centrality of Silicon Valley, shouldn’t we expect far more people to have majored in computer science?

This is even more surprising when we consider that 1.90 million people graduated with bachelor’s degrees in 2015, which is 31% higher than the 1.44 million graduates in 2005. (Data is via the National Center for Education Statistics, Digest of Education Statistics) That means that the share of people majoring in computer science has decreased, from 3.76% of the all majors in 2005 to 3.14% of all majors in 2015. Meanwhile, other STEM majors have grown over the same period: “engineering” plus “engineering technologies” went from 79,544 to 115,096, a gain of 45%; “mathematics and statistics” from 14,351 to 21,853, a gain of 52%; “physical sciences and science technologies” from 19,104 to 30,038, a gain of 57%; “biological and biomedical sciences” from 65,915 to 109,896, a gain of 67%. “Computer sciences and information technologies?” From 54,111 in 2005 to 59,581 in 2015, a paltry 10.1%.

If you’d like a handy chart, I graphed the growth here, with number of graduates normalized to 2005.

(Addendum: Several people have pointed out that 2005 was an idiosyncratic year, and that I should not rebase figures from that date. I graphed it from this point because in the NCES dataset I’ve been using breaks out the data by one-year intervals only since 2005. Scroll to the end of the post to see data on graduates from 1975, which shows clearly that 2005 was a peak for graduates. A more full discussion would involve the impact of the dotcom bubble; see below.)

I consider this a puzzle because I think that people who go to college decide on what to major in significantly based on two factors: earning potential and whether a field is seen as high-status. Now let’s establish whether majoring in CS delivers either.

Are wages high? The answer is yes. The Bureau of Labor Statistics has data on software developers. The latest data we have is from May 2016, in which the median annual pay for software developers is $106,000; pretty good, considering that the median annual pay for all occupations is $37,000. But what about for the lowest decile, which we might consider a proxy for the pay of entry level jobs that fresh grads can expect to claim? That figure is $64,650, twice the median annual pay for all occupations. We can examine data from a few years back as well. In 2010, median pay for software developers was $87,000; pay at the lowest decile was $54,000. Neither were low, now both have grown.

Now we can consider whether someone majoring in computer science can expect to join a high-status industry. That’s more difficult to prove rigorously, but I submit the answer is yes. I went to high school during the late-aughts, when the financial crisis crushed some of Wall Street’s allure, and Silicon Valley seemed glamorous even then. Google IPO’d in 2004, people my age all wanted to buy iPhones and work for Steve Jobs, and we were all signing up for Facebook. People talked about how cool it would be to intern at these places. One may not expect to end up at Google after college, but that was a great goal to aspire to. Industries like plastics or poultry or trucking don’t all have such glittering companies that attract.

I tweeted out this puzzle and received a variety of responses. Most of them failed to satisfy. Now I want to run through some common solutions offered to this puzzle along with some rough and dirty argument on what I find lacking about them.

Note: All data comes from the Digest of Education Statistics, Department of Education.

***

1. Computer science is hard. This is a valid observation, but it doesn’t explain behaviors on the margin. CS is a difficult subject, but it’s not the only hard major. People who proclaim that CS is so tough have to explain why so many more people have been majoring in math, physics, and engineering; remember, all three majors have seen growth of over 40% between 2005 and 2015, and they’re no cakewalks either. It’s also not obvious that their employment prospects are necessarily more rosy than the one for CS majors (at least for the median student who doesn’t go to a hedge fund). Isn’t it reasonable to expect that people with an aptitude for math, physics, and engineering will also have an aptitude for CS? If so, why is it the only field with low growth?

On the margin, we should expect high wages to attract more people to a discipline, even if it’s hard. Do all the people who are okay with toiling for med school, law school, or PhD programs find the CS bachelor’s degree to be unthinkably daunting?

2. You don’t need a CS degree to be a developer. This is another valid statement that I don’t think explains behaviors on the margin. Yes, I know plenty of developers who didn’t graduate from college or major in CS. Many who didn’t go to school were able to learn on their own, helped along by the varieties of MOOCs and boot camps designed to get them into industry.

It might be true that being a software developer is the field that least requires a bachelor’s degree with its associated major. Still: Shouldn’t we expect some correlation between study and employment here? That is, shouldn’t having a CS major be considered a helpful path into the industry? It seems to me that most tech recruiters look on CS majors with favor.

Although there are many ways to become a developer, I’d find it surprising if majoring in CS is a perfectly useless way to enter the profession, and so people shun it in favor of other majors.

3. People aren’t so market-driven when they’re considering majors. I was a philosophy major, and no I didn’t select on the basis of its dazzling career prospects. Aren’t most people like me when it comes to selecting majors?

Maybe. It’s hard to tell. Evidence for includes a study published in the Journal of Human Capital, which suggests that people would reconsider their majors if they actually knew what they could earn in their associated industries. That is, they didn’t think hard enough about earning potentials when they were committing to their majors.

We see some evidence against this idea if we look at the tables I’ve been referencing. Two of the majors with the highest rates of growth have been healthcare and law enforcement. The number of people graduating with bachelor’s degrees in “health professions and related programs” more than doubled, from 80,865 in 2005 to 216,228 in 2015. We can find another doubling in “homeland security, law enforcement, and firefighting,” from 30,723 in 2005 to 62,723 in 2015. Haven’t these rents-heavy and government-driven sectors been pretty big growth sectors in the last few years? If so, we can see that people have been responsive to market-driven demand for jobs.

(Sidenote: if we consider the pipeline of talent to be reflective of expectations of the economy, and if we consider changes in the number of bachelor’s degrees to be a good measure of this pipeline, then we see more evidence for Alex Tabarrok’s view that we’re becoming a healthcare-warfare state rather than an innovation nation.)

In the meantime, I’m happy to point out that the number of people majoring in philosophy has slightly declined between 2005 to 2015, from 11,584 to 11,072. It’s another sign that people are somewhat responsive to labor market demands. My view is that all the people who are smart enough to excel as a philosophy major are also smart enough not to actually pursue that major. (I can’t claim to be so original here—Wittgenstein said he saw more philosophy in aerospace engineering than he did in philosophy.)

4. Immigrants are taking all the jobs. I submit there are two ways to see that immigrants aren’t meeting all the marginal demand. First, most immigrants who come to the US to work are on the H1B visa; and that number has been capped at 65,000 every year since 2004. (There are other visa programs available, but the H1B is the main one, and it doesn’t all go to software engineers.) Second, rising wages should be prima facie evidence that there’s a shortage of labor. If immigrants have flooded the market, then we should see that wages have declined; that hasn’t been the case.

To say that immigrants are discouraging people from majoring in CS requires arguing that students are acutely aware of the level of the H1B cap, expect that it will be lifted at some point in the near future, and therefore find it too risky to enter this field because they think they’ll be competing with foreign workers on home soil. Maybe. But I don’t think that students are so acutely sensitive to this issue.

5. Anti-women culture. Tech companies and CS departments have the reputation of being unfriendly to women. The NCES tables I’m looking at don’t give a breakdown of majors by gender, so we can’t tell if the shares of men and women majoring in CS has differed significantly from previous decades. One thing to note is that the growth of people earning CS majors has been far below the growth of either gender earning bachelor’s degrees.

More women graduate from college than men. (Data referenced in this paragraph comes from this table.) In 1980, each gender saw about 465,000 new grads. Since then, many more women have earned degrees than men; in 2015, 812,669 men earned bachelor’s degrees, while 1,082,265 women did. But since 2005, the growth rate for women earning bachelor’s has not significantly outpaced that of men. 32.5% more men earned bachelor’s degrees in the previous decade, a slightly higher rate than 31.5% for women. It remains significant that women are keeping that growth rate for over a higher base, but it may be that it’s no longer the case that their growth can be much higher than that of men in the future.

What’s important is that the growth rate of 30% for both genders is below that of 10% for CS majors over this time period. We can’t pick out the breakdown of genders from this dataset, but I’d welcome suggestions on how to find those figures in the comments below.

6. Reactionary faculty. The market for developers isn’t constrained by some guild like the American Medical Association, which caps the number of people who graduate from med schools in the name of quality control.

CS doesn’t have the same kind of guild masters, unless we want to count faculty to be serving this function on their own. It could be that people serving on computer science faculties are contemptuous of people who want high pay and the tech life; instead they’re looking for the theory-obsessed undergraduate who are as interested in say Turing and von Neumann as much as they are. So in response to a huge new demand for CS majors, they significantly raise standards, allowing no more than say 500 people to graduate if a decade ago only 450 did. Rather than cater to the demands of the market, they raise standards so that they’re failing an even higher proportion of students to push them out of their lovely, pure, scholarly field.

I have no firsthand experience. To determine this as a causal explanation, we would have to look into how many more students have been graduating from individual departments relative to the number of people who were weeded out. The latter is difficult to determine, but it may be possible to track if particular departments have raised standards over the last few decades.

7. Anti-nerd culture. Nerds blow, right? Yeah, no doubt. But aren’t the departments of math, physics, and engineering also filled with nerds, who can expect just as much social derision on the basis of their choice? That these fields have seen high growth when CS has not is evidence that people aren’t avoiding all the uncool majors, only the CS one.

8. Skill mismatch and lack of training from startups. This is related but slightly different to my accusation that CS faculty are reactionaries. Perhaps all the professors are too theoretical and would never make it as coders at tech companies. Based on anecdotal evidence, I’ve seen that most startups are hesitant to hire fresh grads, instead they want people to have had some training outside of a college. One also hears that the 10X coders aren’t that eager to train new talent; there isn’t enough incentive for them to.

This is likely a factor, but I don’t think it goes a great length in explaining why so few people commit to majoring in the field. Students see peers getting internships at big tech companies, and they don’t necessarily know that their training is too theoretical. I submit that this realization should not deter; even if students do realize this, they might also know they can patch up their skills by attending a boot camp.

9. Quality gradient. Perhaps students who graduate from one of the top 50 CS departments have an easy time finding a job, but those who graduate from outside that club have a harder time. But this is another one of those explanations that attributes a greater degree of sophistication than the average freshman can be observed to possess. Do students have an acute sense of the quality gradient between the best and the rest? Why is the marginal student not drawn to study CS at a top school, and why would a top student not want to study CS at a non-top school, especially if he or she can find boot camps and MOOCs to bolster learning? I would not glance at what students do and immediately derive that they’re hyperrational creatures.

10. Psychological burn from the dotcom bubble. Have people been deeply scarred by the big tech bubble? It bursted in 2001; if CS majors who went through it experienced a long period of difficulty, then it could be the case that they successfully warned off younger people from majoring in it. To prove this, we’d have to see if people who graduated after the bubble did have a hard time, and if college students are generally aware of the difficulties experienced by graduates from previous years.

11. No pipeline issues anymore. In 2014, the number of people majoring in CS surpassed the figure in 2005, the previous peak. In 2015, that figure was higher still. And based on anecdotal evidence, it seems like there are many more people taking CS intro classes than ever before. 2014 corresponds to four years after The Social Network movie came out; that did seem to make people more excited for startups, so perhaps tech wasn’t as central then as it seems now.

I like to think of The Social Network as the Liar’s Poker of the tech world: An intended cautionary tale of an industry that instead hugely glamorized it to the wrong people. The Straussian reading of these two works, of course, is that Liar’s Poker and The Social Network had every intention to glamorize their respective industries; the piously-voiced regrets by their creators are absolutely not to be believed.

Even if the pipeline is bursting today, the puzzle is why high wages and the cultural centrality of Silicon Valley have not drawn in more people in the previous decade. Anyone who offers an argument also has to explain why things are different today than in 2005. Perhaps I’ve overstated how cool tech was before 2010.

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A few last thoughts:

If this post is listed on Hacker News, I invite people to comment there or on this post to offer discussion. In general, I would push on people to explain not just what the problems are in the industry, but how they deter college students from pursuing a major in CS. College freshmen aren’t expected to display hyperrationality on campus or for their future. Why should we look for college students to have a keen appreciation of the exponential gradient between different skill levels, or potential physical problems associated with coding, or the lack of training provided by companies to new grads? Remember, college students make irrational choices in major selection all the time. What deters them from studying this exciting, high-wage profession? Why do they go into math, physics, or engineering in higher numbers instead?

I wonder to what extent faculties are too strict with their standards, unwilling to let just anyone enter the field, especially for those who are jobs-minded. Software errors are usually reversible; CS departments aren’t graduating bridge engineers. If we blame faculty, should people be pushing for a radical relaxation/re-orientation of standards in CS departments?

Let’s go to the top end of talent. Another question I think about now: To what extent are developers affected by power law distributions? Is it the case that the top say 25 machine learning engineers in the world as worth as much as the next 300 best machine learning engineers together, who are worth as much as the next best 1500? If this is valid, how should we evaluate the positioning of the largest tech companies?

Perhaps this is a good time to bring up the idea that the tech sector may be smaller than we think. By a generous definition, 20% of the workers in the Bay Area work in tech. Matt Klein at FT Alphaville calculates that the US software sector is big neither in employment nor in value-added terms. Software may be eating the world, but right now it’s either taking small bites, or we’re not able to measure it well.

Finally, a more meditative, grander question from Peter Thiel: “How big is the tech industry? Is it enough to save all Western Civilization? Enough to save the United States? Enough to save the state of California? I think that it’s large enough to bail out the government workers’ unions in the city of San Francisco.”

Thanks to Dave Petersen for offering helpful comments.

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Addenda, May 30th:

I’m pleased that this post has generated more discussion here in the comment section, on Hacker News, Reddit, and on Twitter. On Twitter, Evan Soltas pointed to an article from Eric Roberts, a professor at Stanford, discussing this question from a longer term view.

Several people remarked that my rebasing of majors to 2005 is misleading because of the impact of the dotcom bubble. I only gestured at it in the post above, but it probably explains a big chunk of why the number of CS majors hasn’t risen. So here’s a more full chart, from Eric Roberts’ article, with the number of CS majors starting from 1975.

Wow, the number of people graduating with CS degrees is really cyclical. The first peak in 1985 corresponds to the release of the IBM Personal Computer. The second peak corresponds to the 2001 dotcom bubble. I agree now that the ’01 bubble explains a lot of the decline afterwards; people graduated into a bad job market and that scared many students away. That year, however, may have been the worst of it; by 2005, Google had IPO’d, Facebook was spreading on campuses, the iPod was a success, and the iPhone would be released two years later. Those companies drew students back into studying CS, and we can see that from the rise again in 2009.

This is a neat story, but still I have to confess some surprise. Should it take 15 years before the popping of the bubble before we see that college students are graduating with the same degrees again? I guess so, and I’m interested if other industries have experienced a similar lag. Were people entering school say in 2003 acutely aware of how badly fresh graduates were suffering? Were they very well aware of then market conditions, and decided that things were too risky? Why didn’t freshmen/sophomores course correct earlier when they saw that the bubble had bursted?

Elsewhere, Matt Sherman points out this survey from Stack Overflow, which shows that three-quarters of developers have a bachelor’s degree or above, alongside much other interesting data. Alice Maz and an email correspondent remark that people decide on majors because they’re driven by fear of failure, not for high wages; that explains why so many people are fighting for med school spots. I like that Bjoern Michaelsen and commenters below have pointed out that developers suffer from significant skill depreciation and limited job security; I suppose that this is stuff that undergrads are able to intuit. And several people have remarked on mid-aughts fears that all software development would be outsourced to India; I had been unaware of the strength of this fear.

I’d like to finally remark that this could be an interesting project for more serious researchers to pick up. I wrote this out of fun on my leisure time, and invite others to study how cyclical demand for this major is, what the supply constraints are, and the quality gradient between the developers. Someone more serious than me can also discuss how the NCES aggregates different majors in these categories; perhaps a more granular breakdown is more helpful. Wage data especially might be helpful to overlay here. In the meantime, I invite people to keep commenting here.

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