Tag Archives: online education

The Great Disintermediation

Yesterday at Forbes, William Pentland had an interesting piece on possible disintermediation in the electricity market.

In New York and New England, the price of electricity is a function of the cost of natural gas plus the cost of the poles and wires that carry electrons from remotely-sited power plants to end users. It is not unusual for customers to spend two dollars on poles and wires for every dollar they spend on electrons.

The poles and wires that once reduced the price of electricity for end users are now doing the opposite. To make matters worse, electricity supplied through the power grid is frequently less reliable than electricity generated onsite. In other words, rather than adding value in the form of enhanced reliability, the poles and wires diminish the reliability of electricity.

If two thirds of the cost of electricity is the distribution mechanism, then, as Pentland notes, there is a palpable opportunity to switch to at-home electricity generation. Some combination of solar power, batteries, and natural gas-fired backup generators could displace the grid entirely for some customers. And if I understand my electricity economics correctly, if a significant fraction of customers go off-grid, the fixed cost of maintaining the grid will be split over fewer remaining customers, making centrally-generated electricity even more expensive. The market for such electricity could quickly unravel.

While it remains to be seen whether electricity generation will indeed become decentralized, such disintermediation would be the continuation of a decades-long social trend. It all began (plausibly) in 1984. The Macintosh was released, and desktop computing became a thing. Desktop printers disintermediated printing departments, Kinkos, and the steno pool. The Internet has disintermediated telephone companies, music labels, television networks, newspapers, and much more. Online education is unbundling university courses.

What’s even more exciting is the next generation of disintermediating technologies. Bitcoin could displace some financial institutions—to varying degrees, banks, the Federal Reserve, Western Union, and credit card companies. Mesh networks could solve the last-mile problem of Internet service delivery, which tends to be monopolized or at least concentrated. 3D printers could disintermediate supply chains. 3D chemical printers could disintermediate drug companies and the FDA.

Delivery drones like Amazon Prime Air‘s arguably disrupt package delivery services, though not entirely because FedEx and UPS will still run drone-utilizing distribution networks. More importantly, delivery drones disintermediate the real estate market for small businesses. It will no longer be important, if you run a local business, to have a storefront in a prime location. Your customers can order online and items can be delivered to them in half an hour straight from the factory or artisanal workshop. It could be the Etsyfication of the economy.

If information, electricity, money, and production all get disintermediated, what is left? If these trends continue, the future will be one in which human interaction is unmediated, and to a surprising degree, unregulable. It will be difficult to stop a willing buyer and seller from transacting. Information about the proposed transaction might not be censorable. Payment via Bitcoin or other cryptocurrencies can’t be stopped. Production and delivery of the item may be difficult or impossible to detect and intercept.

Intermediaries are often used by governments as points of control. As we shed intermediaries, it may become possible to live one’s entire life without any particular authority even knowing that one exists. I doubt that we’ll ever get that far in the process, because using non-abusive intermediaries often makes economic sense. But for the next few decades, at least, I expect the trend to continue and the world to get a lot more interesting.

The Third Industrial Revolution Has Only Just Begun

Bob Gordon released a provocative working paper (ungated) back in August that made quite a splash on the blogs. It is an extreme, more pessimistic version of Tyler Cowen’s The Great Stagnation. Gordon argues—rightly, in my opinion—that economic growth is not automatic. There is no a priori reason to believe that real per capita GDP will grow at 2 percent in the future when it has grown at a rate closer to 0 for most of human history. Maybe the current period is unique—and coming to an end.

The question is worth considering, but in the details of his analysis, there is much that Gordon gets wrong. For example, Gordon looks at growth in the “frontier” economy, the economy that is most advanced in each period. This means the UK from 1300 to 1906 and the US from 1906 to 2007 (where he stops his story to abstract from the financial crisis). When looking at a single wealthy economy, global factor-price equalization that results in lower middle-class wages seems like a bad thing. But of course, these lower wages are the result of higher wages elsewhere—they are wages for poor people who can increasingly contribute to the frontier of innovation as they get wealthier. Limiting the analysis to a frontier national economy seems inappropriate when one of the major global trends is a reduction in the discreteness of national economies.

I have a lot of other complaints—for instance, I wanted to refer Gordon to Noah Smith on global warming—but for the rest of this post, I am going to focus only on one particular issue. Gordon divides our progress over the past 250 years into not one, but three Industrial Revolutions. IR #1 was from 1750 to 1830 and gave us steam power and railroads. IR #2 ran from 1870 to 1900 and yielded electricity, internal combustion, running water, indoor toilets, communications, entertainment, chemicals, and petroleum. IR #3 started in 1960 and gave us computers, the Internet, and mobile phones.

Gordon takes the view—entirely defensible—that IR #2 is the one that is the most important, and that it took about 100 years for its “full effects to percolate through the economy.” But both in his definition and discussion, he gives short shrift to IR #3.

The computer and Internet revolution (IR #3) began around 1960 and reached its climax in the dot.com era of the late 1990s, but its main impact on productivity has withered away in the past eight years. Many of the inventions that replaced tedious and repetitive clerical labor by computers happened a long time ago, in the 1970s and 1980s. Invention since 2000 has centered on entertainment and communication devices that are smaller, smarter, and more capable, but do not fundamentally change labor productivity or the standard of living in the way that electric light, motor cars, or indoor plumbing changed it.

Later in the paper, he writes,

Attention in the past decade has focused not on labor-saving innovation, but rather on a succession of entertainment and communication devices that do the same things as we could do before, but now in smaller and more convenient packages. The iPod replaced the CD Walkman; the smartphone replaced the garden-variety “dumb” cellphone with functions that in part replaced desktop and laptop computers; and the iPad provided further competition with traditional personal computers. These innovations were enthusiastically adopted, but they provided new opportunities for consumption on the job and in leisure hours rather than a continuation of the historical tradition of replacing human labor with machines.

I can see how if you’re comparing the advancements of the past few decades to the benefits of indoor plumbing you might come away a little disappointed, and I’m not trying to play IRs 2 and 3 against each other. But I think that Gordon unfairly or unwittingly understates the magnitude of IR #3, because IR #3 has only just begun.

What is IR #3 and where is it going?

Again, Gordon defines IR #3 as the arrival of computers, the Internet, mobile phones, etc. But rather than focusing on the products, let’s focus on the processes and innovations that got us here—computation, miniaturization, packet switching, and so on. These ideas feature prominently in the products that Gordon uses to define IR #3, but they also have much wider conceivable applicability than just those products.

I think we are on the cusp of an important transition within IR #3. So far, we have used these innovations to make ever faster, smaller, and more useful computers, including mobile phones. We have created, as Gordon notes, a whole lot of dot-coms and online services. But we’re already starting to see engineers and companies dabble with new kinds of products. Rather than merely accepting, transforming, relaying, and displaying information, some new computer-based products have more of a physical—really, a kinetic—effect on the world.

The most obvious example of this new kind of kinetic computing is the autonomous car. Rather than simply gathering information and displaying it to the driver, like a GPS mapping system, we are empowering an onboard computer to make decisions about driving. These decisions have consequences, and it is difficult to program a computer to get them right—much harder than, say, inventing Facebook. But despite the difficulty of the problem, we have made a lot of progress in the last decade, and most of us can look forward to one day owning a robotic car or ordering a robotic taxi to come pick us up.

The point is that computing innovation is going to shift, and is already starting to shift, from the virtual to the physical world. The products that IR #3 has brought us so far are great fun, but because they only really display information to us, they leave a lot for us to do. The main benefit of iR #3 is going to arrive when new innovations make and do things for us.

Ambient computing

Golden Krishna wrote an excellent blog post recently entitled “The best interface is no interface.” Read the whole thing. The point of the post is that we have not yet done a good job of replacing early computer interface paradigms like WIMP—window, icon, menu, pointer—with natural, unobtrusive, adaptive paradigms. Instead we slap a display on everything and call it progress.

Read tweets on your speedometer!

Krishna provides some great examples of the alternative vision, what he calls “No UI,” which include the Auto Tab feature of Pay with Square and Nest. What these products and services have in common is that users empower them to make decisions without direct supervision. They require a little human interaction to set up, but from then on, unless something goes wrong, there is no need to do anything to use the product. The product adapts to you, it gets out of the way, and it feels natural.

We are only just now getting to the point where products like these are becoming possible. So far in IR #3, we have mainly trusted computers with information, not with decisions about the physical world. But as computing improves, we are going to automate more.

In What Technology Wants, Kevin Kelly writes about the “home motors” you could buy a century ago. The idea was that buy a single motor for interchangeable use in a sewing machine, a mixer, a fan, or an egg beater.

One hundred years later, the electric motor has seeped into ubiquity and invisibility. There is no longer one home motor in a household; there are dozens of them, and each is nearly invisible. No longer stand-alone devices, motors are now integral parts of many appliances. They actuate our gadgets, acting as the muscles for our artificial selves. They are everywhere. I made an informal census of all the embedded motors I could find in the room I am sitting in while I write:

[...]

That’s 20 home motors in one room of my home. A modern factory or office building has thousands. We don’t think about motors. We are unconscious of them, even though we depend on their work. They rarely fail, but they have changed our lives. We aren’t aware of roads and electricity either because they are ubiquitous and usually work. We don’t think of paper and cotton clothing as technology because their reliable presences are everywhere.

Once computer chips become as ubiquitous and invisible as motors, and we get competent enough at using them to empower them to make decisions for us without direct supervision, the result will be something like ambient intelligence. It’s hard to predict what people will use AmI for, but it certainly feels to me like a much bigger advance than Angry Birds and Facebook. We’re probably a decade or two away from high-quality ambient intelligence, but given its reliance on the innovations generated on IR #3, AmI should be counted as an IR #3 innovation when it arrives.

Transport efficiency

The audacious idea that economic growth was a one-time-only event has no better illustration than transport speed. Until 1830 the speed of passenger and freight traffic was limited by that of “the hoof and the sail” and increased steadily until the introduction of the Boeing 707 in 1958. Since then there has been no change in speed at all and in fact airplanes fly slower now than in 1958 because of the need to conserve fuel.

Gordon is right that travel speeds have not increased much in recent decades. If you had told me in that 1980s that by 2012 I would still never have traveled faster than sound (relative to the Earth), I would have been very disappointed. And while some interesting technologies are in the pipeline—scramjets, spaceplanes, and so on—it will be a while before these are commercialized.

But in the meantime, the efficiency of transporting people and goods could explode in the near future. Gordon is well aware of autonomous cars, so I won’t belabor the point, but it seems obvious to me that a morning commute during which I am able to productively get started on my day is almost like no commute at all. An evening commute during which I am able to relax and unwind is almost like no commute at all. If we calculate effective speed by dividing travel distance by wasted time, then technologies like autonomous vehicles and to a lesser extent in-flight Wi-Fi are starting to make up for some of the stagnation in proper transport speed.

I have already written about how revolutionary commercial drones are likely to be. Local deliveries will be made robotic quadrocopters instead of by humans, and FedEx will switch to blended-wing unmanned cargo freighters that will reduce the cost of long-range goods transport by a factor of five, making air transport competitive with (only about twice as expensive as) ocean transport. A key point about the quadrocopter revolution is that it needed the iPhone market to get started:

As Dan Shapiro notes, “A single high-quality gyro used to go for a thousand bucks.  Now, you can get 3 gyros, 3 accelerometers, and a nice CPU to manage the whole thing for under a sawbuck.”

Commercial drones face some regulatory hurdles, but assuming these can be overcome, they will be an important contribution of IR #3.

Matter compilers

Traditional printers have a kinetic effect on the world—they put ink to paper—but not really. We value them for the informational quality of the printed product, not for the physical structure of the object that comes out of the printer. 3D printing is not that different from traditional printing, but its impact is likely to be much larger. It is another element of IR #3 that is still in development.

When I got a chance to see a 3D printer in person earlier this year, I was underwhelmed. There is still very little that consumer 3D printers can produce that I would actually want. But future generations of printers will almost certainly be much more useful as they become able to print in a wider array of materials.

In particular, I am excited to see chemical printers. People will be able to make their own drugs—both medical and recreational. This may sound dangerous, and perhaps it will be. But with the adoption of quantum computing we will be able to simulate chemical reactions in advance, something that we still cannot do efficiently with classical computers. Such simulation will greatly improve the feasibility of moving quickly to human trials on new drugs, including self-experimentation. The combination of quantum simulation and chemical printing could lead to a golden age of pharmaceutical discovery.

Synthetic biology

Relatedly, synthetic biology is another area where we seem to be observing rapid progress. I am woefully ignorant about synthetic biology—I am ashamed of this and will remedy it soon—so I should probably not be making very strong claims. But it seems important to mention that few if any of the advances in this field would have been possible without computers or prior research that has made heavy use of computers. Consequently, these advances are attributable to IR #3.

Online education

Total educational spending in the United States is something like 7 percent of GDP (5.5% of GDP is public expenditure, I believe around 1.5% or so is private expenditure). And the quality of education for anybody but the best or richest students is not especially good—the US routinely posts middling scores in international comparisons for primary and secondary education. Even at the college level, where the US excels, a lot of students are being underserved, often because they need remedial help.

We are still using a medieval technology, the lecture, to educate our students. But increasingly entrepreneurs—both for- and non-profit—are looking for better ways of teaching. Many of the new crop of online educational institutions, such as Khan AcademyUdacity, and Marginal Revolution University, are completely free.

People are still experimenting with educational models (and business models), but education that leverages new technologies has several advantages over the old classroom model. For example, in what is known as “flipping the classroom,” students can watch lectures for homework, and do problem sets in class, where they can get help from teachers. The quality of teaching can be higher because everybody can be taught by the very best teachers. And separating the teaching component of school from the coaching and supervision component of school means lower costs and greater specialization, including jobs for people who are not good at teaching but who are nevertheless good at working with kids. At least until the robots can do that too.

Gordon argues that we got a one-time economic boost from educating more people, but now educational achievement has plateaued and we can no longer rely on more education as a source of economic growth. But this seems like a narrow perspective to me. The quality of education certainly has a lot of room for improvement, as does the cost. If we let computers help us teach, we can improve on both of these margins.

While it remains to be seen what the ultimately successful models of online education will be, it would be surprising to me if there is not a major change in the educational industry in the next couple decades. And when that change comes, I bet it will be due to IR #3.

A new phase of IR #3

I’ve tried to review a number of emerging technologies that are likely to transform our daily lives, how we transport people and goods, how we make stuff, our health, and our educational system. Obviously this is an incomplete list; see Wikipedia for more.

There is still a lot of oomph in IR #3. All of the technologies that I have described are in development, and all of them owe their existence to digital computing. Some of them may founder, and some different technologies may turn out to be more important. But it is a big mistake to think that the world of computing can remain separate from the rest of the world for long. Computing started out set apart because it is safer that way—if your browser crashed or your web server goes down, there are not very large external consequences.

Experience and practice in the safe virtual world are leading to a greater desire and capability to extend these technologies to the physical world. It has taken 50 years, but we are now on the cusp of these changes. The remaining question is whether we will welcome them or try to smother them with regulations and arguments over the transitional gains. The best way out of the Great Stagnation is to eagerly embrace and support the new technologies. But they may be coming whether we want them or not, and that is why I am a long-run growth optimist.

The New Economics of Online Education

Let’s stipulate up front that there is an old model of online for-profit education that has completely failed. The old model is this: take everything that used to be done in person, put it online, charge for it. There are some programs along these lines that are still kicking, and some traditional universities have online programs, but it seems clear now that the future of online education does not lie here.

A large problem with this model is incentive-compatibility. The incentives of the online provider are to enroll as many students as possible, especially since students are often subsidized, and then to let standards slip so that the students pass. If most students fail, they will be angry, and the commitment to keeping standards high is not credible. High standards are not a subgame perfect equilibrium.

The reason most universities are not for profit is that the profit motive strengthens the incentive to let standards slip, although it should be noted that standard-slippage has happened, albeit more slowly, even at non-profit universities. The great success stories in for-profit education are those that generate easily verifiable skills. For instance, if you want to learn German, you are probably better off going to Berlitz than to Harvard. When you finish at Berlitz, you know whether you got your money’s worth because you know whether you know German; this solves much of the incentive-compatibility problem. If Berlitz taught English literature (to English speakers), I don’t think it would be as successful as Harvard.

Enter Udacity. Unlike many other online education providers, Udacity has not tried to simply replicate the old in-person education experience online. Rather, they are adopting an entirely new business model. First, they have a radically different cost structure than traditional providers. Udacity does its grading by AI, so the marginal cost of another student is basically zero. It has a much higher fixed cost per course, because it needs to train the AI to grade homework and exams.

Since Udacity’s marginal cost of a student is zero, it can give away the courses for free if it can find another way to cover its fixed cost. I perked up when I read this:

All classes are currently free, and the goal is to keep it that way. When asked how it will make money, [Udacity co-founder] Sebastian [Thrun] pointed out that recruiting good technical talent is something that companies pay for. Udacity knows who the best students are and could pass them along to companies looking for new hires.

In Silicon Valley, finding talent is so difficult that recruitment bounties are often as high as 20 percent of the new hire’s first-year salary. This provides an opportunity for a new revenue structure for online education: vertical integration into job placement.

Udacity can sell its database of high-performing students to recruiters from tech firms. They can survey these students to see if they are interested in a job before they do so to ensure that the database is high quality in the interest dimension as well. This database is a very valuable asset, one that seems likely to cover Udacity’s fixed costs.

I think the Udacity model can succeed in subject areas where:

  1. Skills command a large premium in the labor market.
  2. Employers can verify skills in the medium run, so that they can decide whether to continue to pay for Udacity-educated recruits.
  3. It is possible to evaluate coursework using artificial intelligence (we’re not there for writing yet).

Udacity has started out with classes on computer programming, because that is what its founders know, but they seem eager to expand to new subject areas. I wonder if economics will be one of them.

Socially, there are some advantages to the Udacity model versus the traditional university system. Perhaps most obviously, we can avoid a lot of the student debt crisis. Since classes are free, there is no tuition expense, and since revenue is constrained by the labor market, the skills taught will need to correspond to those that are valuable. We can also save a lot of money on government subsidies for higher education; indeed, cutting off these funds now would hasten the adoption of new education business models.

Speaking generally, new contexts allow for new business models. People are often slow to recognize these new opportunities. We need to make sure as a society that we are not locking in old business models and preventing change. This means giving up control and being willing to be surprised by the outcome.