“We shape our tools. Thereafter, our tools shape us.”
— Tobias Kinnebrew, Bot & Dolly
The onrush of new technology into higher education is, to most academicians, both wonderful and terrible—not least for the reasons that Kinnebrew suggests: the new tools presage a different world and a different “us.” Now we have “Web 3.0,” according to Tim O’Reilly at a conference last month. O’Reilly is a technology publisher and commentator and the origin of the phrase, “Web 2.0.” What is this new Internet? And what does it portend for higher education?
Most likely this: more of the same, only more so. In previous posts, I have argued that new technology will accelerate the pace of change of higher education, that such change will entail a displacement of instructors and institutions whose material can be easily digitized, and that the emergent champions will be those who excel at digital delivery of knowledge, and those who excel at the delivery of superior in-person learning experiences—to be stuck in the middle will be very dangerous. Acceleration. Displacement. Polarization. My hunch is that “Web 3.0” will advance all of that.
The New New Thing
To refresh your memory, “Web 1.0” gave connectivity of the written word, such as email and blogs. It entailed narrow-band connectivity available through dial-up services such as AOL. Then came “Web 2.0,” which gave connectivity of video, music, and which required more bandwidth and the communication technology to process immense volumes of data. The Internet took on a two-way publishing model in which Internet users contribute content, rather than a one-way system akin to book publishing, in which Web site owners post and publish content directly for a separate audience to read—YouTube is the canonical example.
“Web 2.0” made possible asynchronous education such as Khan Academy and the “flipped classroom” now so popular in K-12 education circles. It also exploded digital instruction into higher education: MOOCs, hybrid program designs (that mixed digital and person-to-person (P2P) instruction), Skype-based learning teams, learning management systems such as Canvas, Cloud-based storage of records and materials, digitized books and case studies, and PowerPoint mashups of video, text, voice, animation, etc. What made all this possible was the growth of bandwidth, and the incredible decline in the cost of computer processing power and of storage of information.
“Web 3.0” is the “Internet of Things” (IoT), which recognizes that Internet connectivity extends well beyond desktop-to-desktop toward a host of different possible things: tablets, smartphones, smart watches, personal activity monitors (e.g. Fitbits), robots in manufacturing plants, and glasses (e.g., Google Glass). Sensors are growing in ubiquity and connecting to form intelligent systems based in the Internet. Tablet computers are widely distributed across military units in Iraq and Afghanistan. A new-model jet engine by General Electric contains over 100 sensors and generates over a terabyte of data per flight; these data are uploaded via the Internet to promote predictive maintenance (i.e., rather than maintenance that is purely reactive to breakdowns). Application software enables the individual person or the large enterprise to customize the engagement with the Internet. The torrent of data that descends on the service providers has riveted decision-makers on “big data” and the need for sophisticated analytics to enable even better provision of service in the future. What made all this possible is the near-zero cost of information storage, the spread of sensors that record the experience of humans, organizations, and things; the invention of hardware devices that achieve the greater distribution information generated by sensors; the development of apps that permit greater customization; and generally, the diminishing cost of innovation. The cost of experimentation with hardware and software is so low that design and development of new software and devices is being pushed out of large enterprises and into the garages, basements, “Fab Labs,” “hackathons,” and “Maker DIY.”
These themes about “Web 3.0” and IoT were explored last month in the Solid Conference, produced by O’Reilly Media. ((Disclosure: my son, Jonathan, was co-chair of the conference.)) The premise of the conference was that “Physical things—machines, devices, components—are about to experience a profound transformation. The Internet fundamentally changed how software is developed and deployed, and now hardware is on the brink of a similar disruption. Consumers, already carrying smart phones and driving cars that park themselves, have come to demand more from their objects than ever before. They expect their belongings to “know” them, to interact with them, and to adapt to their needs. Industry is realizing that smart networked machines can bring them the efficiencies and new capabilities to do more, faster, and cheaper…Hardware and software are fusing into a single fluid entity….this collision of software and hardware is fueling the creation of a software-enhanced, networked, physical world.” The “Things” form a more intelligent system rather than just a connection of objects. Hardware is starting to resemble software in its capacity to be edited, to adapt to changing needs; and software is starting to resemble hardware (e.g. smartphones don’t have buttons, they have icons on a touch screen). The result is increasingly intelligent information technology systems that are growing in their ubiquity, customizability, and sensing capacity:
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Networked automation. Prompted by sensors, machines communicate with machines from the consumer’s point of purchase back to the assembly plant, back to the component fabricators, back to the suppliers of raw materials. RFID and GPS systems allow computers to track the movement of supplies from distant locations to sufficient precision that it gives new meaning to “just in time” management. Within manufacturing plants, processes are increasingly automated: machines monitor workflow, inventory levels, quality, and maintenance. Beth Comstock of General Electric calls this the “selfless machine: a machine will sense other machines and what the changing environment requires that the machine should do. No machine is an island.” And machines remove workers from dangerous settings: Rio Tinto described the use of mining vehicles controlled by drivers in the safety of a distant facility. These examples may seem unsurprising and prosaic, since mechanization has been a steady theme for decades. But what is notable today is the extent to which machines and information systems substitute for human interaction and to which humans expect their machines to anticipate their expectations. Reducing human intervention has proved to be a boon to users of taxicabs—just ask clients of Uber—or to people trying to transfer money—just ask clients of Bitcoin.
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Synthesis of virtual and physical. Google, a software company, bought seven robotics manufacturers last year. In 2008, the number of devices connected to the Internet surpassed the number of people on earth. One of the most provocative examples of the melting boundary between software and the physical world comes from Autodesk, the software company. Carl Bass, the CEO, explained that DNA, or genetic code, is simply a physical manifestation of software. Extending the company’s capabilities in software development, Autodesk has the ability to “print” physical DNA. Bass said, “the age of synthetic biologic manufacturing is right in front of us.” Is Autodesk in software or hardware or biotech?
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Knowingness. Systems that can recognize a person’s individual identity can adapt to that person’s preferences. Inventors demonstrated systems that adjust household lighting, heating and ventilation. Similarly, systems can aggregate across many individuals to frame insights about mass behavior—inventors demonstrated a system that can distill exabytes of purchasing behavior from iTunes to graphically display the presence of jazz enthusiasts by district in a metropolitan area.
The Limit to Things.
How far will the “Web 3.0” go in displacing the work of humans? It is limited by its ability to produce transformational experiences, to generate high standards of craft, and to create ideas.
Experiences. At the end of the Solid conference, I took a hike. Literally. Backroads.com is one of the best active vacation tour guides on the planet and took me and six others on an exploration of some mountainous terrain along the Amalfi coast in Italy. Heart-pounding trail-climbs and descents. Spectacular vistas. The scent of wild garlic, rosemary, and fennel; the feel of wild orchids between the fingertips; the taste of homemade pasta, mozzarella, and cappuccino. What’s more, the experience was shared with the likes of a physician, two research chemists, a corporate manager, and two homemakers. We corrected one-another’s broken Italian, shared jokes, collaborated on load-bearing, map-reading, and direction-finding, compared perceptions about the surroundings, and challenged assumptions on virtually all subjects—it felt like a walking graduate seminar. I was transformed by the experience: new sensations and their synthesis into something quite impactful.
High Standards of Craft. Can “Web 3.0” define its own standards of excellence? Can it judge true excellence, as opposed to just “good enough” compared to some peers? A highlight of the Solid conference was a presentation by Richard Isaacs, who carries the title of “Organ Builder” at C.B. Fisk, a leading manufacturer of pipe organs. Each of these instruments is one-of-a-kind, a work of art. Isaacs asked, “What has changed in organ-building over the past 150 years?” Relatively little. A tracker organ connects keys to pipes by mechanical means which produces an extraordinary ability of the musician to “feel” the very complex instrument at work, in turn which enables highly sophisticated performance. Fisk’s instruments embody extraordinary craftsmanship.
Ideation. The new book, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, by Eric Brynjolfsson and Andrew McAfee of MIT, forecasts the increasing automation of “routine” tasks: “this leads to job polarization: a collapse in demand for middle-income jobs, while non-routine cognitive jobs (such as financial analysis) and non-routine manual jobs (like hairdressing) have held up relatively well.” (p. 139). The authors emphasize that the cognitive work that will fare particularly well in the increasingly machine-dominated environment will be the non-routine cognitive jobs:
We’ve never seen a truly creative machine, or an entrepreneurial one, or an innovative one. We’ve seen software that could create lines of English text that rhymed, but none that could write a true poem…Programs that can write clean prose are amazing achievements, but we’ve not yet seen one that can figure out what to write about next. We’ve also never seen software that could create good software; so far, attempts at this have been abject failures. These activities have one thing in common: ideation, or coming up with new ideas or concepts. To be more precise, we should probably say good new ideas or concepts…Ideation in its many forms is an area today where humans have a comparative advantage over machines. Scientists come up with the hypotheses. Journalists sniff out a good story. Chefs add a new dish to the menu. Engineers on a factory floor figure out why a machine is no longer working properly. Steve Jobs and his colleagues at Apple figure out what kind of tablet computer we actually want. …Ideation, creativity, and innovation are often described as ‘thinking outside the box,’ and this characterization indicates another large and reasonably sustainable advantage of human over digital labor. Computers and robots remain lousy at doing anything outside the frame of their programming. (pages 191-2)
These limiting factors define that “high ground” to which traditional educational institutions will need to climb. Ironically, this ground has always been the domain of higher education; but as the mandate of higher education broadened after World War II, this ground was overgrown by other mandates that are now being seized by digitization. Such other mandates include vocational preparation, compensating for a worsening K-12 educational system in America, and “edutainment.”
Conclusion
As Tobias Kinnebrew said, “We shape our tools. Thereafter, our tools shape us.” That is the dominant message for higher education from “Web 3.0.” Here are some speculative implications for how the tools will shape educators:
- One way becomes two way. The digital services will not be tied only to computers, but will be delivered through a variety of devices, such a mobile phones, eyeglasses, and earbuds. The Internet of Things will permit educators to engage digitally with students in ways that may feel more intimate and attentive to the learning experience. For instance, this will yield greater opportunity to monitor the reaction of students to their lessons and their progress. Software intelligence is rising above the level of a single instructor, department, or institution. Think of the extensive knowledge that Amazon, Apple, or Netflix accumulates about its customers. Without doubt, networks and markets are accumulating that kind of information about our students. Data accumulation will morph into service offerings to students that are ubiquitous and are increasingly customized to their needs.
- Automation and Ideation. Digital delivery will serve tools and objective information (such as names, dates, and formulas). If IBM’s Watson computer can learn to beat the world’s reigning Jeopardy champion (i.e., a challenge based on ambiguous questions depending on encyclopedic knowledge of trivia), it may be possible to digitize some aspects of mentoring students. Still, I doubt the ability of machines to recognize subtle variations in human emotion and to empathize appropriately. Above all, P2P (person-to-person) instruction best serves to prepare students for ideation and critical thinking—delivering on this is not a stretch for most colleges and universities worth their name. Big data is very interesting. Big wisdom is even more interesting.
- Innovation at the fringe rather than the center. Incumbency may not be an advantage. So much of innovation today is occurring on the periphery of the industries rather than by the major players. In previous posts, I have argued that the high cost of digital instruction, and the inevitably rising quality expectations would redound to the advantage of deep-pocketed leaders in the field. But the rise of disruptive new players can eliminate the middlemen and edge out the incumbents (think of Uber versus the big city taxi monopolies, Bitcoin versus banks, or Autodesk versus big pharma).
- Governance and accountability Much of Brynjolfsson and McAfee’s argument says that we should get better at working with smart machines. Probably so. But let’s not teach students to cede accountability or moral responsibility for the consequences of their collaboration with machines. At issue here is, who shall be the master? A related fact is that today, every school is a software enterprise. Design and delivery of the learning experience for students will increasingly entail a software interface in addition to a human face. If, as the foregoing points suggest, that interface will be an integral part of the curriculum, should not the faculty govern it?