Via a reader:
It's not there yet, but Google is adding a gaggle of World Heritage Sites to the Street View feature, and Sterkfontein will be among them. An interesting detail:
Where access by car is not possible, Google uses its custom-made 'trike' – a three-wheeled bike mounted with a camera – to take the images. It will soon be used to collect imagery of the Sterkfontein Caves in SA.
Now, if they will just take us into the Silberberg Grotto...
For obscure reasons, I'm installing Windows 7 on one of my MacBooks. The installation has gone pretty smoothly. But the first thing I wanted to do was install Safari -- not because I'm a zealot or anything, but that's what I use on every other computer, and I don't see any sense using a different browser on this one.
So how does Microsoft welcome me back into the fold? Internet Explorer won't load apple.com, or any pages from apple.com. No problem loading any other website -- heck, I've got Firefox downloading now. Nope, just Apple, which loads fine right at this moment on the MacBook I'm typing this on.
Meanwhile, on the TV comes the new "Switchers" commercial, where the PC goes into a time warp of endless promises of stability from the past.
And where the heck is my bash prompt?
UPDATE (2009-11-10): A reader writes to remind me of Cygwin, which installs bash and other Unix utilities on Windows. Oh, it works like a charm. Backslashes have their place, but the file structure is not it.
John Timmer gives a great summary of the new paper in Science covering the Complete Genomics sequencing method.
A surprising (to me, at least) fact:
But, because each of these nanoballs was so small, it's possible to do massive amounts of sequencing in parallel, simply by washing different solutions across the surface they were stuck to. The authors were able to get anywhere from 45- to 87-fold coverage of the genome—meaning that, on average, each base in the genome had been sequenced 45 or 87 times, respectively. That's just an average, of course, as chance will ensure that some sequences are under- or overrepresented. Still, given an algorithm designed to work with these specific results and the reference human genome sequence, Complete Genomics was able to get excellent coverage of the genome.
Oh, yeah -- the lede from the paper:
Validation of one genome data set demonstrates a sequence accuracy of about 1 false variant per 100 kilobases. The high-accuracy, affordable cost of $4,400 for sequencing consumables and scalability of this platform enable complete human genome sequencing for the detection of rare variants in large-scale genetic studies.
Most people know that hunter-gatherer men hunt meat. Fewer people know the major secondary target for male foraging in many hunter-gatherer societies: honey. The resource is so highly valued that some men spend as much effort foraging for honey as they do hunting.
Chimpanzees also forage for honey. The use of tools to dig for, bash into, and dip honey out of bee nests or hives has long been known from many chimpanzee field sites. For example, Craig Stanford and colleagues (2000) described how chimpanzees in Bwindi-Impenetrable National Park, Uganda, use small sticks to forage for honey from the small nests of stingless bees, while they use much bigger sticks to get honey out of honeybee nests.
Two papers from this year have illustrated a new appreciation for the complexity of chimpanzee toolkits used for honey raiding. Crickette Sanz and David Morgan (2009) describe honey gathering by chimpanzees at the Goualougo, Congo field site, while Christophe Boesch and colleagues (2009) describe the technology used by chimpanzees at Loango, Gabon. Both are relatively new field sites, in which researchers have arrived recently or are still habituating the chimpanzees to their presence. Thus, the variations in chimpanzee behaviors at these sites are still being recognized and just starting to be reported.
Loango National Park is a relatively new field site. As the researchers there continue to habituate the chimpanzees, they have been gathering a series of observations on behaviors that occur differently in Loango compared to other field sites. According to Boesch et al. (2009:2), chimpanzees at the Loango field site do not crack nuts despite a local abundance of them. But far from being simpler in their material culture than other chimpanzees that do crack nuts, the Loango chimps make up for their lack of nutcracking with a complex package of tools for honey extraction:
Gathering honey from underground hives, similar to underground termite fishing in Goualougo, is special in the sense that chimpanzees cannot see where the resource is hidden and use the first tool, the perforator, as an exploratory tool to “feel” where the resource is located underground. In both cases, external indirect signs of food sources are visible (e.g., large termite mounds or small fragile Melipone-made tubes), but the nest itself is not visible and its exact location cannot be inferred. Therefore, chimpanzees have to investigate the soil in order to locate food that can be, in the case of Melipone underground nests, as much as 1 m deep and 70 cm lateral to the visible tube. Locating the underground chamber can take a human between 20 to 40 minutes (Boesch, pers. obs.). The successful locating of honey is apparent from honey sticking to the ends of perforators. To extract honey, a tunnel needs to be dug sideways so as to reach the underground chamber and prevent soil from getting mixed with the honey once the membrane of the chamber is broken (in general, the intact upper membrane of the chamber in the emptied hole can be felt). We think that such tunnels are dug with the help of perforators to loosen the soil. These tunnels are sometimes barely large enough to let a human arm through, and therefore indicate that chimpanzees know exactly where they are aiming. This cannot be done by simply following the bee tube, as it is much too fragile to resist the tool-assisted digging process. Thus, an elaborate understanding of unseen nest structure, combined with a clear appreciation that tools permit the location of unseen resources, and a precise three-dimensional sense of geometry for reaching the honey chamber from the correct angle, is demonstrated by the chimpanzees when extracting underground honey. It has been proposed that an elaborate understanding of causal relationships between external objects is required for flexible tool use to evolve (Boesch and Boesch-Achermann, 2000), and the fact that such exploratory tools are only seen in chimpanzees and humans supports this proposition (Boesch et al. 2009).
I liked the authors' description of how they defined tool types and categorized objects on the basis of signs of use. WIth quite a simple technology, this differentiation appears nevertheless to be of a similar extent to the stone toolkits used by early Homo. What is different is the complexity of manufacture of (some of) the elements of the toolkit.
That topic of basic manufacturing method versus within-toolkit differentiation is addressed by a new study by Thibaud Gruber and colleagues (2009):
Here, we present the results of a field experiment [20] and [21] that compared the performance of chimpanzees (P. t. schweinfurthii) from two Ugandan communities, Kanyawara and Sonso, on an identical task in the physical domain—extracting honey from holes drilled into horizontal logs. Kanyawara chimpanzees, who occasionally use sticks to acquire honey [4], spontaneously manufactured sticks to extract the experimentally provided honey. In contrast, Sonso chimpanzees, who possess a considerable leaf technology but no food-related stick use [4] and [22], relied on their fingers, but some also produced leaf sponges to access the honey. Our results indicate that, when genetic and environmental factors are controlled, wild chimpanzees rely on their cultural knowledge to solve a novel task.
The finer points of tool use lie atop a technological substrate. For one group of chimpanzees, this substrate may be sticks, for another stones (in nutcracking), for another leaves. Social learning may tend to associate some raw materials with manipulatory processes -- a chaïne operatoire, at a very simple level. The complexity of the honey-extraction kits appears to show that, at least for highly valued purposes, chimpanzees can bring together distinct elements into a single technological solution. It's nothing that a three-year-old human can't do, but it's another point in favor of Wynn and McGrew's "Ape's view of the Oldowan" argument.
Boesch C, Head J, Robbins MM. 2009. Complex tool sets for honey extraction among chimpanzees in Loango National Park, Gabon. J Hum Evol 56:560-569. doi:10.1016/j.jhevol.2009.04.001
Gruber T, Muller MN, Strimling P, Wrangham R, Zuberbühler K. 2009. Wild chimpanzees rely on cultural knowledge to solve an experimental honey acquisition task. Curr Biol (in press) doi:10.1016/j.cub.2009.08.060
Sanz CM, Morgan DB. 2009. Flexible and persistent tool-using strategies in honey-gathering by wild chimpanzees. Int J Primatol 30:411-427. doi:10.1007/s10764-009-9350-5
Stanford CB, Gambaneza C, Nkurunungi JB, Goldsmith ML. 2000. Chimpanzees in Bwindi-Impenetrable National Park, Uganda, Use different tools to obtain different types of honey. Primates 41:337-341.
The coming trend in e-books: video.
The most obvious way technology has changed the literary world is with electronic books. Over the past year devices like Amazon’s Kindle and Sony’s Reader have gained in popularity. But the digital editions displayed on these devices remain largely faithful to the traditional idea of a book by using words — and occasional pictures — to tell a story or explain a subject.
The new hybrids add much more. In one of the Simon & Schuster vooks, a fitness and diet title, readers can click on videos that show them how to perform the exercises. A beauty book contains videos that demonstrate how to make homemade skin-care potions.
"Vooks" sounds like there's vampire involvement.
The linked article is about novels, where short videos seem to be included mainly for the imagination-deprived. Textbooks on the other hand seem more promising. How many 1-minute demonstrations, or five-minute interviews would go in a typical textbook chapter? I can imagine casts floating around the page like a "Harry Potter" newspaper.
IBM and Google want students to ditch their laptops and pick up some big iron:
For the most part, university students have used rather modest computing systems to support their studies. They are learning to collect and manipulate information on personal computers or what are known as clusters, where computer servers are cabled together to form a larger computer. But even these machines fail to churn through enough data to really challenge and train a young mind meant to ponder the mega-scale problems of tomorrow.
“If they imprint on these small systems, that becomes their frame of reference and what they’re always thinking about,” said Jim Spohrer, a director at I.B.M.’s Almaden Research Center.
I love that analogy -- like they're cute little baby ducks learning that their computers are mama.
Meanwhile, this is all about teaching students how to deal with data-mining software. They believe that the future of science is in being able to use these immense datasets, from sources like genomics and high-throughput astronomy.
“It sounds like science fiction, but soon enough, you’ll hand a machine a strand of hair, and a DNA sequence will come out the other side,” said Jimmy Lin, an associate professor at the University of Maryland, during a technology conference held here last week.
The big question is whether the person on the other side of that machine will have the wherewithal to do something interesting with an almost limitless supply of genetic information.
There's some truth to this. On the other hand, I don't see how this explosion of data is going to create a raft of new jobs for scientists. Sure, IBM and Google want to recruit the best, in their position who wouldn't? Maybe we'll need fewer clinicians and techs to prep samples for data analysis, and that will shift some jobs to data analysis. But what they're talking about here are software development jobs to support science, not the science itself.
Yes, geneticists will need to deal with larger datasets, but that means that more instances of small data features will empower them to test certain hypotheses that would have been untestable before. The scientist's job is to think of those hypotheses, work out the logic by which data may refute them, and root the inquiry in existing theory.
There's a practical aspect to this, where working with large datasets helps to train students to think about data and theory. But the tools we're using now to access datasets will be different in four years, and ten years down the line -- the times when today's beginning students will be entering graduate school, or finishing Ph.D.'s Those little ducklings are going to need to swim on their own.
IBM joins the next-gen sequencing race:
The I.B.M. approach is based on what the company describes as a “DNA transistor,” which it hopes will be capable of reading individual nucleotides in a single strand of DNA as it is pulled through an atomic-size hole known as a nanopore. A complete system would consist of two fluid reservoirs separated by a silicon membrane containing an array of up to a million nanopores, making it possible to sequence vast quantities of DNA at once.
I read Chris Anderson's book because it was, well, "Free". The book's thesis is simple: Sometimes people profit by giving things away.
I have been, for several years now, making scientific knowledge available for no cost to any readers who care to come by my site. In academic circles, this practice is ordinarily considered to be insane. Therefore, whenever I come across anything explaining why blogging isn't such a stupid idea, I put it right into my files. That's for Luddites on future promotion committees.
How do I review the book without making points like a Slashdot comment thread?
Somewhere in the book, Anderson wrote his plan for making money from Free: Get businesses to pay for the Chris Anderson "Free" seminar. The short business profiles and catchy anecdotes in the book were pretty well crafted as advertisements for the seminar. But beneath the chrome, there are some interesting -- sometimes wacky -- ideas about the nature of human economic interactions.
Anderson describes the $10,000 wager between economist Julian Simon and Paul Ehrlich. Simon believed that commodity prices would not rise over the long term, betting that the "substitution effect" would spur people to find new technological solutions to replace expensive raw materials, thus lowering the commodity prices. Ehrlich believed that resource shortages were inevitable as population and economic pressures grew. In 1990, Simon collected on the bet, as the five commodity metals chosen by the two had all fallen, many substantially.
Others have cast this story as a parable about bad predictions, or the inherent fallacy of future pessimism. Anderson gives the story a sociobiological spin:
Humans are wired to understand scarcity better than abundance. Just as we've evolved to overreact to threats and danger, one of our survival tactics is to focus on the risk that supplies are going to run out. Abundance, from an evolutionary perspective, resolves itself, while scarcity needs to be fought over. The result is that despite Simon's victory, the world seemed to assume that Ehrlich, on some level, was still right.
As [Wired's Ed] Regis noted, "Simon complained that, for some reason he could never comprehend, people were inclined to believe the very worst about anything and everything; they were immune to contrary evidence just as if they'd been medically vaccinated against the force of fact." Ehrlich's gloomy predictions continued (and continue) to have influence. Meanwhile Simon's own observations seem to be of interest only to commodities traders (49-50).
If we really want to explain the phenomenon of "Free", we need to turn to psychology and sociology. At several points in the book, Anderson does connect to these fields -- mentioning the "Dunbar number" in the context of MySpace "friends", Lewis Hyde's work The Gift in the context of non-monetary economies, and Abraham Maslow's "Theory of human motivations" in the context of why bloggers write for free. But Anderson's goal is not to explain, but to popularize. So his use of academic sources is, well, eclectic. The "Dunbar number" is mostly an anthropological urban myth. There's a very deep literature on the gift in ethnology. Sure, there's no market for Mauss seminars on Anderson's lecture circuit, but there are some entertaining classic stories about confusion, gifts, and cross-cultural contacts.
Anderson's theme simplifies this complexity of social interactions into a binary:
There is a reason why economics is defined as the science of "choice under scarcity": In abundance you don't have to make choices, which means that you don't have to think about it at all (50).
There's an anthropological claim -- that humans are "wired" as a "survival tactic" to perceive scarcity. It makes a good story. But is it true?
Human lives are long. Sure, there are some essential resources so abundant that we don't need to think about them -- air, for example. But most resources vary over time or space. People have always needed to consider whether to stay or move, whether to hunt today or wait until tomorrow, to gather more firewood or risk the cold. It's the ant and the grasshopper.
We might imagine a version of the Ehrlich-Simon bet during the Pleistocene. Imagine humans occupying a few abundant habitats with plenty of food. As the population grows, they put pressure on these habitats. What happens? On the Ehrlich side, resource scarcity might trigger a demographic crisis, with hunger, warfare, and a population crash. On the Simon side, people might expand their behavioral niche, moving into less favorable habitat with more complex cultural adaptations.
Humans are tricky creatures, and our potential for increasing complexity depends on the level of complexity we've already reached. Only some parts of a complex system may be amenable to measurement. Anderson points out this problem from the standpoint of business information technology:
When your phone company tells you that your voice mail box is full, that's artificial scarcity -- it costs less than a nickel to store one hundred voice messages, and the average iPod could store thirty thousand of them (voice messages are recorded at lower quality than music, so they take less space). By forcing subscribers to take the time to delete voice mails, the phone companies are saving a little money in storage costs by spending a lot of consumer time. They managed the scarcity they could measure (storage) but neglected to manage the much larger scarcity of their customers' goodwill. No wonder phone companies are second only to cable TV companies in the "most hated" rankings (191).
Reading this made me think of behavioral science in the role of the stupid phone company. Natural selection optimizes fitness, that much is algorithmic. But how does this optimization process affect any given behavioral trait? That depends how the trait is connected to fitness, how heritable it is, and whether anything else correlated with the trait exerts its own independent negative effect on fitness. It's a mess, and we generally can't figure it out. So, we measure what we can. The fallacy is that what we can measure may have little connection to the important output -- for the phone company, profit per customer; for the biologist fitness.
Today with an embarrassment of abundance of food and goods, people still agonize over choices. From one point of view, this is just a waste of time -- why argue over arbitrary markers of status, when the essential resources are super-abundant?
But from a social point of view, seeking out limited information may be in our nature. This leads me to question whether Anderson is right about the value of information itself. Does it really trend toward free?
Humans evolved to be users (and broadcasters) of social information, but in the past our communication was limited by many of the same constraints that other animals face. Animal communication is not free -- it comes with direct and indirect costs. The direct costs are energetic and developmental -- animals have to build and maintain the organs of communication, and supply the power to run them. The indirect costs are the perils of advertising: an animal that reveals itself runs a greater risk of predation. Worse, the peril of honest advertising is that potential mates may see what a loser you really are.
The Internet might have enabled more complex systems of information presentation, but for the most part, people use it for old-fashioned reading. At its best, it has enabled a social transformation, empowering millions of people to use very simple means of information transfer -- from short-form blogs to messaging in World of Warcraft.
That's "messaging", not "massaging".
If the cost of information appears to be trending downward, it may be that's because the production of information is increasing with a lot higher slope than the production of money that might purchase it. Consider genomics: What would you be willing to pay for your genome today? Whatever your answer, you can expect that you would be willing to pay even less 10 years from now, unless the health value of that information radically increases.
[T]he more products are made of ideas, rather than stuff, the faster they can get cheap. This is the root of the abundance that leads to Free in the digital world, which we today shorthand as Moore's Law.
However, this is not limited to digital products. Any industry where information becomes the main ingredient will tend to follow this compound learning curve and accelerate in performance while it drops in price. Take medicine, which is shifting from "we don't know why it woks, it just does" (there's a reason it's called drug "discovery") to a process that starts with the first principles of molecular biology ("now we know why it works"). The underlying science is information, while observed efficacy is just anecdote. Once you understand the basics, you can create an abundance of better drugs, faster.
DNA sequencing is falling in price by 50 percent every 1.9 years, and soon our individual genetic makeup will be another information industry. More and more medical and diagnostic services will be provided by software (which get cheaper, to the point of being free) as opposed to doctors (who get more expensive) (84).
Once upon a time, the only diagnostic service was a doctor. Doctors offloaded some of their diagnostic effort as lab tests became more and more important. Nowadays, one of the major reasons for the increase in health care costs is the routine ordering of expensive tests. Doctors order these tests because they reduce risk -- risk of bad outcomes, and risk of malpractice suits. Risk is money.
The least satisfactory chapter for me was about science fiction and abundance. Anderson argues throughout the book that humans are "wired" for scarcity; that we just don't understand abundance. In chapter 15, he turns to fictional worlds -- from E. M. Forster to Cory Doctorow -- in which some machine (or other invention) had created endless abundance. Invariably, these works describe how society degenerates when freed from scarcity -- freed from "striving", people are robbed of purpose.
Anderson misses a darker connection. The people who worried about the degeneration of human moral purpose in the face of abundance also worried about our genetic degeneration. The eugenics movement was born in the same post-industrial society as science fiction, and for the same reason. Later in the book Anderson references the similarity:
[R]eplace "free" with "steam" and you can imagine the Victorian concern about flabby muscles and minds (229).
I wonder whether there is something inherently dystopian about a society where genetic information is too cheap to meter. In a world where risk is money, and very small risks are increasingly quantifiable, it is not hard to imagine an inexorable process toward removing freedom and imposing control. Certainly that has been the theme of many science fiction works.
But rather than end on that depressing note, I'll point instead to a happy consequence of free information exchange: the creativity expressed in online communities:
RuneScape, yet another Web-based world of orcs and elves, counts more than 1 million subscribers (out of more than 6 million users) paying $5 a month, creating a $60 million annual business. As a point of reference, that's about the same size as the subscriber user base and annual revenues of the Wall Street Journal's subscription-based Web site, which is the biggest paid site of all the world's newspapers. It's also larger than the New York Times's paid online subscriber base was before the paper dropped the model in favor of Free in 2008. It appears that people would rather pay to cast pretend spells than to read Pulitzer Prize-winning news. (I'll leave whether that's a good thing or a bad thing to others.) (150).
People are using their power to make new things -- sometimes frivolous, fictitious things, but things that make them happy. It's possible that genetic information can serve this purpose, too -- a point I'll return to on a different topic tomorrow.
The paper about the flax fibers found by Eliso Kvavadze and colleagues in Dzudzuana Cave, Republic of Georgia, is a one-pager. The good kind of one-pager -- the kind where you can understand the whole thing. If I didn't hate the misuse of supporting online material so much, I think I might wish that every paper were required to have a one-page synopsis like this. The press accounts about the paper would have been better if they'd just quoted the whole thing!
I find this paper very exciting. Here, in one very clear set of observations, we get a glimpse of a whole human activity pattern. Before this, we knew only hints about fiber processing, later in time and from only one site. Nowadays, most people don't think much about the technology in their T-shirts and jeans. If you're not a fiber artist or knitter, you may not have a concept of just how much work went into clothing and other fiber objects before the Industrial Revolution.
Here, in these little clay samples, is a clear picture of hours upon hours of work. You don't get a variety of color dyes, systematic flax gathering and twisted threads without a sustained tradition. This was technology that contributed directly to survival -- keeping people warm, and helping them fit into their families, clans or tribes. Calories saved by clothing, mats, or padding were calories that did not have to be hunted or gathered. Few technologies could contribute so directly to social status as the kind and quality of clothing. We aren't seeing the beginning of that technology at Dzudzuana, we're seeing it already in a highly developed state.
Flax fibers by themselves would not be newsworthy. Humans gathered plant materials long before 30,000 years ago. Several caves show good evidence of many species of gathered grasses and forbs. We assume that these people, including Neandertals, were using plants as bedding or floor covering materials.
What makes the Dzuzuana fibers different is the evidence that they were incorporated into textiles:
A few of the fibers are colored and appear to have been dyed. A wide range of natural pigments was available to the Upper Paleolithic occupants of the cave, including roots and other plant parts (5). The color range includes yellow, red, blue, violet, black, brown, green, and khaki.
It's like Old Navy! More:
All 27 clay samples from unit D produced fibers of flax (N = 488) (table S2); some were spun (N = 13) and dyed (N = 58), the colors are mostly black-to-gray and turquoise. One of the threads is twisted. The complete fibers are long (>200-m) and composed of segments of smaller lengths. Individual fibers are linear with thin and translucent walls. Several ends of both complete and disbanded fibers were cut across (Fig. 1, 1 to 7).
On the whole, it's very convincing evidence of fabrics. Michael Balter's accompanying news piece was able to dig up some doubters about the extent of dyeing, and maybe a more careful study of the chemical pigments will be possible.
The paper also includes a hint about other fiber processing at the site:
The combination of flax fibers, some tur hair, and microremains of skin beetles (fig. S2) and moth can be interpreted as an evidence for processing of fur, skin, and cloth. This conclusion is supported by the presence of spores of the Chaetomium fungus (fig. S2), usually growing on clothes and other textiles and unfortunately destroying them (6).
How early does it go? Is this a novel invention with the Upper Paleolithic, as has often been suggested of string, nets, and other fiber creations? Were fabrics utilized outside the northern latitudes earlier in time?
Possibly, the fungal evidence might be found at even earlier sites, maybe even by using metagenomic techniques. It's reasonable to think that Neandertals and other early people made extensive use of skin and hair. Woven or knotted fabric is different, but possibly there is a continuum between natural animal fibers and plant fibers that connects them.
Balter M. 2009. Clothes make the (hu)man. Science 325:1329. doi:10.1126/science.325_1329a
Kvavadze E, Bar-Yosef O, Belfer-Cohen A, Boaretto E, Jakeli N, Matskevich Z, Meshviliani T. 2009. 30,000-year-old wild flax fibers. Science 325:1359. doi:10.1126/science.1175404
Yesterday's post on MIT OpenCourseware touched on some of the difficulties of independent study using online tools. Three barriers stand in the way -- one practical, two structural.
On the practical side, it's hard to get help without paying for it. If you understand the materials well, you ought to learn as easily from them as any undergraduate taking the class on campus. But if you hit a snag, you might be stuck a long time trying to work through it yourself. That's what professors, teaching assistants and tutors are for: getting you around the snag, so that you can keep progressing.
On the structural side, colleges use every means at their disposal to defend their role as credentialing institutions. Getting a degree -- a certification -- means paying somebody. And one tool in their arsenal is copyright -- they may give you their lectures and notes for free, but they can't distribute the textbooks, graphics, or images that have been drawn from other sources. Sad but true -- I show photos of fossils and sites routinely in my classes, as well as graphics from published articles. Those don't go into free online content -- hence again, personal is better.
Kevin Carey writes in Washington Monthly, "College for $99 a Month", focusing on a new player in the transfer-credit business, StraighterLine. It's one of several outfits trying to make a business out of online education. The article's title draws attention to the unique pricing scheme -- for 99 dollars a month, you can take as many courses as you want. It's like Netflix for college classes:
In recent years, Americans have grown accustomed to living amid the smoking wreckage of various once-proud industries—automakers bankrupt, brand-name Wall Street banks in ruins, newspapers dying by the dozen. It’s tempting in such circumstances to take comfort in the seeming permanency of our colleges and universities, in the notion that our world-beating higher education system will reliably produce research and knowledge workers for decades to come. But this is an illusion. Colleges are caught in the same kind of debt-fueled price spiral that just blew up the real estate market. They’re also in the information business in a time when technology is driving down the cost of selling information to record, destabilizing lows.
The company (and others) makes a business out of low-cost information by offering low-cost services. The parent company, Smarthinking, offers 24-hour tutoring by Internet whiteboard along with purely online tutorials developed in partnership with universities and textbook publishers. Some universities have outsourced their on-campus tutoring to the company, I suppose trading better service for work-study dollars.
Carey's article covers some of the challenges facing StraighterLine -- I was interested in the part describing how Fort Hays State University (in Western Kansas) had evaluated some of the company's courses as transfer credits, only to invoke the ire of the North Central accreditation board and professors. It illustrates the guild system that protects the universities' credentialing market, for the time being.
The underlying issue for colleges is that upper-level specialized courses are money-losers. They take up a large fraction of expensive faculty teaching time, but they have low enrollments -- making them better for students. Colleges cover these costs in part by offering big lecture classes to underclassmen. If students could take 10 of these classes in four months with StraighterLine, they'd spend $400, compared to the many thousands that the same credits would run on campus.
Bob Cringely's current column ("Burn baby, burn") touches on the same problem:
Education, which — along with health care — seems to exist in an alternate economic universe, ought to be subject to the same economic realities as anything else. We should have a marketplace for insight. Take a variety of experts (both professors and lay specialists) and make them available over the Internet by video conference. Each expert charges by the minute with those charges adjusting over time until a real market value is reached. The whole setup would run like iTunes and sessions would be recorded for later review.
Remember, all lectures are also available online for free. What costs is the personal touch.
Say a particularly good professor wants to make $200,000 per year by working no more than 20 hours per week or about 1000 hours per year. That gives them a billing rate of $200 per hour.
That's an interesting business model -- make every professor into a paid consultant. Many already make substantial income in that way, particularly those verging into industry-dominated fields like engineering and medicine. But it's hard to see many English or history professors making $200 per billable hour. Cringely points out that the deal would substantially improve the deal for students:
Now look back at your university career. How much one-on-one time did you actually get with the professors who really influenced your life? I did the calculation and came up with about two hours per week, max. Imagine a four-year undergraduate career running 30 weeks per year — 120 total weeks of school — times two hours of insight per week for a total of 240 hours. At $200 per hour the cost comes to $48,000 or $12,000 per year.
That’s a huge savings compared to the $200,000+ an MIT-level education would cost today.
The difference in cost is facilities and administration. Some of those facilities are necessary for an MIT-level education -- lab work can't all be virtual.
But, there are a lot of ways to involve undergraduates in research, and $200 an hour for direct tutoring in research methods plus subsidizing publication in the university-run open access journal -- that might well be a better (and more practical) advanced education than a faculty-led seminar. It's like music lessons, except for science.
Or students could pool their money to have the professor attend their seminar weekly -- get enough people together who want a Milton seminar, and then hire the Milton scholar. Or two, on alternate weeks. Take what was once passive and make it active.
Well, there are some perspectives on the future of education. Who knows how they'll turn out?
