Unemployment and Technology

My last post, Structural Unemployment: The Economists Just Don't Get It, generated some interesting comments. Here's an especially good one that was posted by an irate economist over at Mark Thoma's blog:

This is the second link I've seen to Mr. Ford's views on labor and technology. It needs to stop. Yes, we need to consider the interaction between the two. We do not, however, need the help of someone whose thinking is as sloppy and self-congratulatory as Ford's. Lots of work has been done on technology's influence on labor markets. Work that uses real data. Ford is essentially making the same "technology kills jobs" argument that has been around for centuries. His argument boils down to "this time it's different" and "people (economists) who don't see things exactly as I do feel threatened by my powerful view and are to be ignored."

There is a whiff of Glenn Beck in Ford's dismissal of other views.

Now, I think that saying "it needs to stop" and then comparing me to Glen Beck is a little over the top. It seems a bit unlikely that my little blog represents an existential threat to the field of economics.

The other points, however, deserve an answer: First, am I just dredging up a tired old argument that's been around for centuries? And second, have economists in fact done extensive work on this issue---using real data---and have they arrived at a conclusion that puts all of this to rest?

It is obviously true that technology has been advancing for centuries. The fear that machines would create unemployment has indeed come up repeatedly---going back at least as far as the Luddite revolt in 1812. And, yes, it is true: I am arguing that "this time is different."

The reason I'm making that argument is that technology---or at least information technology in particular---has clearly been accelerating and will continue to do for some time to come. (* see end note)

Suppose you get in your car and drive for an hour. You start going at 5 mph and then you double your speed every ten minutes. So for the six ten-minute intervals, you would be traveling at 5, 10, 20, 40, 80, and if you and your car are up to it, 160 mph.

Now, you could say "hey, I just drove for an hour and my speed has been increasing the entire time," and that would basically be correct. But that doesn't capture the fact that you've covered an extraordinary distance in those last few minutes. And, the fact that you didn't get a speeding ticket in the first 50 minutes really might not be such a good predictor of the future.

Among economists and people who work in finance it seems to be almost reflexive to dismiss anyone who says "this time is different." I think that makes sense where we're dealing with things like human behaviour or market psychology. If you're talking about asset bubbles, for example, then it's most likely true: things will NEVER be different. But I question whether you can apply that to a technological issue. With technology things are ALWAYS different. Impossible things suddenly become possible all the time; that's the way technology works. And it seems to me that the question of whether machines will someday out-compete the average worker is primarily a technological, not an economic, question.

The second question is whether economists have really studied this issue at length---and by that I mean specifically the potential impact of accelerating technical progress on the worker-machine relationship. I could not find much evidence of such work. In honesty, I did not do a comprehensive search of the literature, so it's certainly possible I missed a lot of existing research, and I invite any interested economists to point this out in the comments.

One paper I did find, and I think it is well-regarded, is the one by David H. Autor, Frank Levy and Richard J. Murnane: "The Skill Content of Recent Technological Change: An Empirical Exploration," published in The Quarterly Journal of Economics in November 2003. (PDF here). This paper analyzed the impact of computer technology on jobs over the 38 years between 1960 and 1998.

The paper points out that computers (at least from 1960-1998) were primarily geared toward performing routine and repetitive tasks. It then concludes that computer technology is most likely to substitute for those workers who perform, well, routine and repetitive tasks.

In fairness, the paper does point out (in a footnote) that work on more advanced technologies, such as neural networks, is underway. There is no discussion, however, of the fact that computing power is advancing exponentially and of what this might imply for the future. (It does incorporate falling costs, but I could not find evidence that it gives much consideration to increasing capability. It should be clear to anyone that today's computers are BOTH cheaper and far more capable than those that existed years ago.).

Are there other papers that focus on how accelerating technology will likely alter the way that machines can be substituted for workers in the future? Perhaps, but I haven't found them.

A more general question is: Why is there not more discussion of this issue among economists? I see little or nothing in the blogosphere and even less in academic journals. Take a look at the contents of recent issues of The Quarterly Journal of Economics. I can find nothing regarding this issue, but a number of subjects that might almost be considered "freakonomics."

The thing is that I think this is an important question. If, as I have suggested, some component of the employment out there is technological unemployment, and if that will in fact worsen over time, then the implications are pretty dire. Increasing structural unemployment would clearly spawn even more cyclical unemployment as spending falls---risking a deflationary spiral.

Consider the impact on entitlements. The already disturbing projections for Medicare and Social Security must surely incorporate some assumptions regarding unemployment levels and payroll tax receipts. What if those assumptions are optimistic?

Likewise, I think economists would agree that the best way for developed countries to get their debt burdens under control is to maximize economic growth. If we got into a situation where unemployment not only remained high but actually increased over time, the impact on consumer confidence would be highly negative. Then where would GDP growth come from?

It seems to me that, from the point of view of a skeptical economist, this issue should be treated almost like the possibility of something like nuclear terrorism: Hopefully, the probability of its actual occurence is very low, but the consequences of such an occurence are so dire that it has to be given some attention.

So, again, I wonder why this issue is ignored by most economists. There are a few exceptions, of course. Greg Clark at UC Davis had his article in the Washington Post. And Robin Hason at GMU wrote a paper on the subject of machine intelligence. I don't agree with Hanson's conclusions, but clearly he understands the implications of exponential progress.

Why not more interest in this subject? Perhaps: (A) Conclusive research has really been done, and I've missed it. or (B) Economists think this level of technology is science fiction and just dismiss it. or (C) Maybe economists just accept what they learn in grad school and genuinely don't feel there's any need to do any research into this area. Maybe something like this is so far out of the mainstream as to be a "career killer" (sort of like cold fusion research).

Another issue may be the seemingly complete dominance of econometrics within the economics profession. Anything that strays from being based on rigorous analysis of hard data is likely to be regarded as speculative fluff, and that probably makes it very difficult to do work in this area. The problem is that the available data is often years or even decades old.

If any real economists drop by, please do leave your thoughts in the comments.

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* Just a brief note on the acceleration I'm talking about (which is generally expressed as "Moore's Law"). There is some debate about how long this can continue. However, I don't think we have to worry that Moore's Law is in imminent danger of falling apart because if it were, that would be reflected in Intel's market valuation, since their whole product line would quickly get commoditized.

Here's what I wrote in The Lights in the Tunnel (Free PDF -- looks great on your iPhone) regarding the future of Moore's Law:

How confident can we be that Moore’s Law will continue to be sustainable in the coming years and decades? Evidence suggests that it is likely to hold true for the foreseeable future. At some point, current technologies will run into a fundamental limit as the transistors on computer chips are reduced in size until they approach the size of individual molecules or atoms. However, by that time, completely new technologies may be available. As this book was being written, Stanford University announced that scientists there had managed to encode the letters “S” and “U” within the interference patterns of quantum electron waves. In other words, they were able to encode digital information within particles smaller than atoms. Advances such as this may well form the foundation of future information technologies in the area of quantum computing; this will take computer engineering into the realm of individual atoms and even subatomic particles.

Even if such breakthroughs don’t arrive in time, and integrated circuit fabrication technology does eventually hit a physical limit, it seems very likely that the focus would simply shift from building faster individual processors to instead linking large numbers of inexpensive, commoditized processors together in parallel architectures. As we’ll see in the next section, this is already happening to a significant degree, but if Moore’s Law eventually runs out of steam, parallel processing may well become the primary focus for building more capable computers.

Even if the historical doubling pace of Moore’s Law does someday prove to be unsustainable, there is no reason to believe that progress would halt or even become linear in nature. If the pace fell off so that doubling took four years (or even longer) rather than the current two years, that would still be an exponential progression that would bring about staggering future gains in computing power.

Causes of Unemployment

Lately, there has been a fair amount of buzz in the economics blogosphere about the issue that I've been discussing extensively here: Structural Unemployment.

Several notable economists have weighed in. Paul Krugman touches on it here. Brad DeLong says this. Mark Thoma has a post in a forum focusing on structural unemployment at The Economist.

If you read through these posts, however, you won't see a lot of discussion about the case I've been making here, which is that advancing technology is the primary culprit. I've been arguing that as machines and software become more capable, they are beginning to match the capabilities of the average worker. In other words, as technology advances, a larger and larger fraction of the population will essentially become unemployable. While I think advancing information technology is the primary force driving this, globalization is certainly also playing a major role. (But keep in mind that aspects of globalization such as service offshoring---moving a job electronically to a low wage country---are also technology driven).

The economists sometimes mention technology, but in general they find other "structural" issues to focus on. One that I have seen again and again is this idea that people can't move to find work because their houses are underwater (the mortgage exceeds the equity). The emphasis given to this issue strikes me as almost silly. Are there any major population centers in the U.S. that have really low unemployment?

Even if people could sell their homes, would they really be motivated to load up the U-haul and move from a city with say 12% unemployment to one where it is only 9%? Have the economists lost sight of the fact that 9% unemployment is still basically a disaster? The few locales I've seen with unemployment significantly lower than that are rural or small cities (Bismark ND, for example)---places that are simply incapable of absorbing huge numbers of hopeful workers. Let's get real: playing musical chairs in a generally miserable environment is not going to solve the unemployment problem.

Another thing the economists focus on is the idea of a skill mismatch. Structural unemployment, they say, occurs because workers don't have the particular skills demanded by employers. While there's little doubt that there's some of this going on, again, I think this issue is given way too much emphasis. The idea that if we could simply re-train everyone, the problem would be solved is simply not credible. If you doubt that, ask any of the thousands of workers who have completed training programs, but still can't find work.

Economists ought to realize that if a skill mismatch was really the fundamental issue, then employers would be far more willing to invest in training workers. In reality, this rarely happens even among the most highly regarded employers. Suppose Google, for example, is looking for an engineer with very specific skills. What are the chances that Google would hire and then re-train one of the many unemployed 40+ year-old engineers with a background in a slightly different technical area? Well, basically zero.

If employers were really suffering because of a skill mismatch, they could easily help fix the problem. They don't because they have other, far more profitable options: they can hire offshore low wage workers, or they can invest in automation. Re-training millions of workers in the U.S. is likely to make a killing for the new for-profit schools that are quickly multiplying, but it won't solve the unemployment problem.

Why are economists so reluctant to seriously consider the implications of advancing technology? I think a lot of it has to do with pure denial. If the problem is a skill mismatch, then there's an easy conventional solution. If the problem's a lack of labor mobility, then that will eventually work itself out. But what if the problem is relentlessly advancing technology? What if we are getting close to a "tipping point" where autonomous technology can do the typical jobs that are required by the economy as well as an average worker? Well, that is basically UNTHINKABLE. It's unthinkable because there are NO conventional solutions.

In my book, The Lights in the Tunnel, I do propose a (theoretical) solution, but I would be the first to admit that any viable solution to such a problem would have to be both radical and politically untenable in today's environment. That's why I don't spend much time suggesting solutions here: what would be the point? (but please do read the book---it's free). I think the first step is to get past denial and start to at least seriously think about the problem in a rational way.

The few economists that have visited this blog and commented on my previous posts have generally barricaded themselves behind economic principles that were formulated more than a century ago (see the comments on my posts about the lump of labour fallacy and comparative advantage).

Most economists seem to be unwilling to really consider this issue---perhaps because it threatens nearly all the assumptions they hold dear. I wrote about this in my first post on this blog. We'll see how long it takes for the economists to wake up to what is really happening.

Update

I've posted a followup that addresses comments and poses some questions for economists: Econometrics and Technological Unemployment -- Some Questions

Jobless Recovery and the Jobless Future

January 2010

The official unemployment rate remains at 10%, and economists are projecting that the job market will take years to recover. Is it possible that, beyond the obvious impact of the financial crisis, there is another largely unacknowledged factor contributing significantly to the dismal unemployment situation?

I believe that there is, and I argue that case in my new book, The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future. In the past two decades, information technology has advanced dramatically and is increasingly being employed to eliminate jobs of all types. Job automation technology, together with globalization, has been the primary force behind the stagnant wages and diminished opportunities for less educated workers we've seen in recent years.

Because information technology accelerates (roughly doubling every two years), rather than increasing at a constant rate, we can expect that the coming years and decades will see even more dramatic progress. In the future, automation is no longer going to be something that primarily impacts low wage, uneducated workers. Technologies such as artificial intelligence, machine learning and software automation applications will increasingly enable computers to do jobs that require significant training and education. College graduates who take "knowledge worker" jobs will find themselves threatened not only by low-wage offshore competitors but also by machines and software algorithms that can perform sophisticated analysis and decision making.

At the same time, continuing progress in manufacturing automation and the introduction of advanced commercial robots will continue to diminish opportunities for lower skill workers. Technological progress is relentless, and machines and computers will eventually approach the point where they will match or exceed the average worker's ability to perform most routine work tasks. The result is likely to be structural unemployment that ultimately impacts the workforce at virtually all levels -- from workers without high school diplomas to those who hold graduate degrees.

Most mainstream economists dismiss this scenario. They continue to believe that the economy will restructure and create adequate numbers of jobs in the long run. Historically this has, in fact, been the case. Millions of jobs were eliminated in agriculture when mechanized farm equipment was introduced. That resulted in a migration to the manufacturing sector. Likewise, manufacturing automation and globalization has resulted in the transition to a largely service-based economy in the United States and other developed countries.
In the past, technology has typically impacted one employment sector at a time, leaving or creating other areas for workers to transition into. That's unlikely to be the case this time around. Accelerating information technology will offer a completely unprecedented level of work capability -- and it can be applied virtually everywhere. As technology providers compete and innovate, automation will certainly become more affordable and more accessible to even the smallest businesses. If a business can save money through automation, competitive pressures will leave it no choice but to do so. While there will certainly continue to be jobs that cannot be automated, the reality is that a very large percentage of the 140 million or so workers in the United States are employed in jobs that are fundamentally routine and repetitive in nature. Enormous numbers of these jobs are going to be vaporized by technology in the coming decades, and because that technology will be available across the board, there is really very little reason to believe that entirely new employment sectors capable of absorbing massive numbers of workers will be created.

The problem is not just one of unemployment. In my book, I use a thought experiment or mental simulation based on "lights in a tunnel" to illustrate the overall economic impact of relentlessly advancing job automation technology. As unemployment increases and wages fall, discretionary consumer spending and confidence will likewise plummet. The result will be a downward economic spiral that will be very difficult to arrest. Beyond some threshold, the business models of mass market industries would be threatened as there would simply be too few viable consumers to purchase their products. We would also likely see unprecedented levels of debt defaults, plunging asset values and financial system disruptions that might easily exceed what has so far occurred in the current crisis.

I believe that the impact of accelerating automation technology is likely to present an enormous economic, social and political challenge over the next ten to twenty years and beyond. Yet, the issue is simply not on the radar. In The Lights in the Tunnel, I suggest some possible reforms that might address the issue, but the reality is that the problem is potentially so disruptive that even progressive thinkers would probably find some of my ideas extreme. Conservatives will likely view my proposals as unthinkable. Nonetheless, if we are ultimately destined to progress into a world where traditional jobs are simply unavailable and where a huge percentage of the population has little in the way of marketable skills or opportunity to earn an income, there will be few if any viable solutions that would not be perceived as radical.

Martin Ford is the author of The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future

Artificial Intelligence - Economics and Job Market Impact

Robin Hanson, a professor at George Mason University (who also blogs at Overcoming Bias), is one of the few economists who has given serious thought to the potential economic implications of artificial intelligence. In Dr. Hanson’s 1998 paper, “Economic Growth Given Machine Intelligence,” he suggests several variations on a growth model which assumes that machines achieve sufficient intelligence to become complete substitutes for, rather than complements to, human labor. Dr. Hanson’s conclusions are very optimistic, and to me, quite counterintuitive. His models “suggest that wholesale use of machine intelligence could increase economic growth rates by an order of magnitude or more.” At the same time, however, he notes the obvious reality that as machines become affordable, and very likely more capable, substitutes for human workers, “wages might well fall below human subsistence levels. “

My immediate reaction to this is that economic growth at any level—let alone of an order of magnitude beyond what we are accustomed to—is fundamentally incompatible with wages that are falling dramatically for the vast majority of workers. We might, perhaps, have vigorous economic growth if the falling wages applied to only a minority of human workers, but it is very difficult for me to conceive of a way in which such growth would be compatible with wages falling across the board—or even for the bulk of workers. The reason is simple: workers are also consumers (and support other consumers). If wages fall dramatically, then consumption must likewise fall because the majority of personal consumption is supported by wage income.

Additionally, I would make the point that as artificial intelligence overwhelmed the labor market, the psychological impact on consumers would almost certainly amplify the fall in consumption. As the number of viable consumers in the market rapidly diminished, the mass market business models of most industries would be numerically undermined: there simply would not be enough willing and able buyers to support the high volume production of goods and services that characterizes most of the major industries that make up today’s economy. The result would not be extreme economic growth, but instead falling revenues and, quite probably, widespread business failures. It seems to me that the current economic situation offers a fair amount of support for my position.

In his paper, it appears to me that Dr. Hanson makes two separate assumptions to get around this basic problem of a reasonable balance between production and consumption. In his initial overview of his growth models, Dr. Hanson writes: “We assume that the product of the economy can be either consumed or used to produce more of any kind of capital (i.e., human, hardware, software, other).” I read this to mean that Hanson is assuming that private sector investment might “pick up the slack” left by diminished consumption. This strikes me an unsupportable assumption for the simple reason that business investment is not independent of consumption—or, at least, current investment is clearly a function of anticipated future consumer spending.

Businesses invest in order to better position themselves to reap the fruits of future consumption. As a business owner myself, I can really think of no other good reason for a business to make substantial investments in “human, hardware, software, or other” capital. In a world in which most workers’ jobs are being automated away and will never return, there would be very little reason to anticipate that future consumer spending would be anything but anemic. Therefore, there would be no reason for the private sector to invest. To me, it seems intuitively obvious that overall private sector investment would not increase, but instead would fall in line with plummeting consumption.

Dr. Hanson does, however, offer a second assumption that might help get around this problem:

Surviving the Economics of Artificial Intelligence: Everyone a Capitalist

Dr. Hanson suggests that his results “may be compatible with a rapidly rising per-capita income for humans, if humans retain a constant fraction of capital, perhaps including the wages of machine intelligences, either directly via ownership or indirectly via debt.” In other words, he seems to be saying that if consumers have an ownership interest in the economy of the future, then the resulting investment income will be sufficient to make up for the precipitous decline in wages. Presumably this would allow the population to continue consuming. Dr. Hanson fleshes out this view in another article on “Singularity Economics” that was published in IEEE Spectrum in June, 2008:

…human labor would no longer earn most income. Owners of real estate or of businesses that build, maintain or supply machines would see their wealth grow at a fabulous rate—about as fast as the economy grows. Interest rates would be similarly great. Any small part of this wealth would allow humans to live comfortably somewhere…

In other words, everyone (or at least most people) will have a piece of the action, and the returns on that ownership will be so fantastic that almost everyone will have a reasonable discretionary income—with which they can then go out and consume.

I’m going to leave aside the obvious problems with the distribution of wealth and income, as well as with any hope of social mobility, that this scenario implies, and instead focus on a more basic question: would asset values really increase at the extraordinary rate that Hanson suggests? Would they increase at all?

Dr. Hanson seems to be assuming that the stock market (and other productive assets) would increase dramatically in value because investors would recognize that businesses now have a fantastic new technology (intelligent machines) which will enable extraordinarily efficient production. The problem I see with this is that, according to modern financial theory, asset values are not determined by investors’ perceptions about technology. Asset values are defined by investors’ expectations for the future cash flows that will be associated with the asset in question. It seems clear to me that, in the midst of across the board job automation and plunging consumer demand, those future cash flows would be looking pretty minimal.

In order for asset values to increase, investors would have to reason that, because asset values would increase dramatically, nearly everyone would have access to an investment income which could then be used to consume—and thereby create the future cash flows which would justify the current value of the asset.

That strikes me as both circular and unlikely. Dr. Hanson seems to be assuming a perpetual asset bubble that somehow gets going even though it is not even remotely initially supported by fundamentals. In fact, the initial fundamentals would point—quite dramatically—in exactly the opposite direction.

Where would these courageous initial investors come from? During the height of the financial crisis last year, I happened to see a report on CNBC which noted that extremely wealthy people were buying gold and having it shipped directly to their estates. They wanted their gold in their homes, behind their gates and walls, buried in their underground vaults. Are those perhaps the investors that Dr. Hanson is expecting to step up to the plate and begin driving up asset values when intelligent machines arrive and destroy consumer demand?

It seems to me that Professor Hanson’s views are really quite unsupportable. Nonetheless, it is of course possible that I have made an error somewhere or I have misunderstood Dr. Hanson’s arguments. I look forward to Professor Hanson’s response to my thoughts.

Update: Dr. Hanson has responded on his blog. My response to his response is here.

Unemployment from Robotics, Artificial Intelligence and Computers - Will Robots and Machines steal our Jobs?

Could Advancing Job Automation Technology Cause Structural Unemployment?

The unemployment situation is looking increasingly dismal. Is it possible that there’s something going on that no one wants to acknowledge?

There can be little doubt that computers, robotic technologies and other forms of job automation have been getting far more capable and that as this trend continues, more workers are certain to be displaced in the relatively near future. Most economists dismiss any concern that this might lead to long-term structural unemployment. At the risk of being labeled a “neo-Luddite,” I’d like to explore this issue a little further.

I think I can make a fairly strong argument that a very large percentage of jobs are, on some level, essentially routine and repetitive in nature. In other words, the job can be broken down into a discrete set of tasks that tend to get repeated on a regular basis. It seems likely that, as both hardware and software continue to advance, a large fraction of these job types are ultimately going to be susceptible to machine or software automation.

I’m not talking about far fetched science fiction-level technology here: this is really a simple extrapolation of the expert systems and specialized algorithms that can currently land jet airplanes, trade autonomously on Wall Street, or beat nearly any human being at a game of chess. As technology progresses, I think there is little doubt that these systems will begin to match or exceed the capability of human workers in many routine job categories–and this includes a lot of workers with college degrees or other significant training. Many workers will also be increasingly threatened by the continuing trend toward self-service technologies that push tasks onto consumers.

One of the most extreme historical examples of technologically induced job losses is, of course, the mechanization of agriculture. In the late 1800s, about three quarters of workers in the U.S. were employed in agriculture. Today, the number is around 2-3%. Advancing technology irreversibly eliminated millions of jobs.

Obviously, when agriculture mechanized, we did not end up with long-term structural unemployment. Workers were absorbed by other industries, and average wages and overall prosperity increased dramatically. The historical experience with agriculture is, in fact, an excellent illustration of the so-called “Luddite fallacy.” This is the idea–and I think it is generally accepted by economists–that technological progress will never lead to massive, long-term unemployment.

The reasoning behind the Luddite fallacy goes roughly like this: As labor-saving technologies improve, some workers lose their jobs in the short run, but production also becomes more efficient. That leads to lower prices for the goods and services produced, and that, in turn, leaves consumers with more money to spend on other things. When they do so, demand increases across nearly all industries–and that means more jobs. That seems to be exactly what happened with agriculture: food prices fell as efficiency increased, and then consumers went out and spent their extra money elsewhere, driving increased employment in the manufacturing and service sectors.

The question we have to ask is whether or not that same scenario is likely to play out again. The problem is that this time we are not talking about a single industry being automated: these technologies are going to penetrate across the board. When agriculture mechanized, there were clearly other labor intensive sectors capable of absorbing the workers. There’s little evidence to suggest that’s going to be the case this time around.

It seems to me that, as automation penetrates nearly everywhere, there must come a “tipping point,” beyond which the overall economy is simply not labor intensive enough to continue absorbing workers who lose their jobs due to automation (or globalization). Beyond this point, businesses will be able to ramp up production primarily by employing machines and software–and structural unemployment then becomes inevitable.

If we reach that point, then I think we also have a serious problem with consumer demand. If automation is relentless, then the basic mechanism that gets purchasing power into the hands of consumers begins to break down. As a thought experiment, imagine a fully automated economy. Virtually no one would have a job (or an income); machines would do everything. So where would consumption come from? If we’re still considering a market (rather than a planned) economy, why would production continue if there weren’t any viable consumers to purchase the output? Long before we reached that extreme point of full automation, it seems pretty clear that mass-market business models would become unsustainable.

One of the things that concerns me the most about this scenario is the potential influence of consumer psychology. If at some point in the future consumers look out the window and see a landscape where jobs are relentlessly getting automated away, and if it appears that getting additional education or training provides little protection, there’s likely to be a significant negative impact on consumer sentiment and discretionary spending. If we someday get into a reinforcing cycle driven by fear of automation, a very dark scenario could ensue. It’s difficult to see how traditional policies like stimulus spending or tax cuts would be effective because they wouldn’t address consumers’ concerns about long-term income continuity.

Most economists will likely object to my arguments here as speculative and lacking in objective data. I think that if you look at issues like stagnating or declining wages for average workers, growing income inequality, increasing productivity, and consumption supported by debt rather than income, you can certainly find evidence that generally suggests we might be approaching that “tipping point” where structural unemployment is going to become a problem. However, it seems unlikely that an econometric analysis of past data is going offer clear support for this theory–and if it ever does, it will be very late in the game.

I wonder about the wisdom of the extreme emphasis on quantitative data analysis that seems to characterize economics. Should we really steer the ship exclusively by focusing our telescope on the wake? There might be an iceberg ahead.

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Martin Ford is the author of The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future.

Future Computer Technology

What can we expect in terms of future computer technology?

Computers have clearly been getting a lot better--faster, lighter, more portable--for a long time. In fact, they have been getting better at an accelerating rate.

In 1965, Gordon Moore, one of the founders of Intel, established what's known as "Moore's Law." It says that the number of transistors on a computer chip will roughly double every two years. Moore's Law has held true for over forty years. Many people now use Moore's Law as a general rule of thumb to express the acceleration of computer technology in general; in other words, the computational capability of computers has been approximately doubling every two years.

That is a fantastic rate of increase: an exponential or geometric progression. To get an idea of what that might mean for future computer technology, lets imagine you start with a penny (one cent) in 1975. That's the year the first real PCs (like the Apple II) began to appear.

So, in 1975 you have 1 cent. Two years later in 1977, you have 4 cents. 1979: 8 cents, and so on.

Here's how it would go:

45 cents in 1985.

$3.60 in 1992.

$82 in 2001.

and $1,300 in 2009.
So we have $1,300 after starting with only a penny, and that demonstrates the difference between a machine like the Apple II and the most advanced computers available today.

Future Computer Technology - A Look Ahead

What's more interesting is if we take a look into the future:

$10,500 in 2015.

$84,000 in 2021.

$336,000 in 2025.

$2.6 million in 2031.

So, if Moore's Law continues to hold, we are going to see a fantastic increase in the power of computer technology by 2031. It's possible that the acceleration will slow down before then because, at some point, chip fabrication technologies will hit a fundamental limit. However, there may well be new technologies like quantum or optical computing by then, or the focus may simply shift to parallel processing so that thousands of cheap processors are linked together.

Of course, there is also a problem with creating software to take advantage of this power. Historically, software has advanced much more slowly than hardware, so it's really software that is the bottleneck.

Software companies like Microsoft will have to come up with compelling applications to make use of all that power. I think there is a good chance that artificial intelligence is going to be one of the biggest uses of the computer technology of the future.

If that's the case, job automation technology is likely to leap forward dramatically, and computers will be capable of doing many of the routine jobs in the economy--even those held by people with college degrees. That is going to create some serious issues for the job market and for the economy as a whole. That's the main focus of my new book, The Lights in the Tunnel.

Best Jobs for the Future

Given the state of the current job market, at lot of people are wondering what career path will make the most sense in the future. The reality is that two primary forces are going to impact the future job market: automation technology and globalization.

Most people tend to focus on globalization as the primary threat. Recent items in the press have noted that people are specifically looking for jobs that can't be outsourced, while at the same time manufacturing jobs continue to migrate to low wage countries.

While globalization and outsourcing are getting most of the attention, the reality is that job automation probably represents a bigger long term threat to most workers than globalization. In addition, many people will be surprised to learn that the threat from job automation is not going to be limited to low skilled/low wage workers. While it is true that robots and machines may someday take over many routine jobs in supermarkets, warehouses and fast food restaurants, many people who sit at desks using computers may be impacted even sooner.

The Best Future Jobs will be Jobs that are Protected from both Automation and Globalization

The New York Times recently had a story entitled Beware, Humans. The Era of Automation Software Has Begun. Sophisticated software may soon be capable of performing many service jobs. In the future, we can expect that many of the jobs that are now being offshored will instead by handled by automation software.

As a result, choosing a career in the future is likely to be increasingly complex. For example, the assumption that getting a college degree will always lead to a better job may not hold true, because many college graduates end up taking "knowledge worker" jobs--they end up sitting at desks using computers, but they still very often perform relatively routine and repetitive tasks (especially at the entry level). These types of jobs are likely to be highly vulnerable to both offshoring and automation at some point in the relatively near future.

Technological change is going to abrupt and unpredictable, so choosing the best job for the future may be a challenge, and it may be necessary to be flexible. The Lights in the Tunnel, includes a detailed look a the trends in automation and offshoring and gives some insight into which types of jobs are likely to relatively safe, and which ones may be among the first automated.