Note: This text is adapted from the original Spanish-language text that I wrote for the first Chapter 1 in Invisible Learning (a book co-written with Cristóbal Cobo). An updated and expanded version of this text will also appear in the next volume, Knowmad Society, due for release later in 2012, and is being shared early to ignite discussion for the upcoming On the Horizon special issue on “Borderless Society.” (The call for papers is still open.)
This working paper presents a framework for conceptualizing changes in society, driven by the forces of globalization, transformations of knowledge society, and accelerating change. The framework is centered on three social paradigms, which Moravec (2008c) labels “Society 1.0,” “Society 2.0,” and “Society 3.0” — expressed as Industrial Society, Knowledge Society, and Knowmad Society. Society 1.0 reflects the norms and practices of pre-industrial to industrial civilization. Society 2.0 refers to the radical social transformations that we are experiencing today, largely due to technological change. The 3.0 or Knowmad Society points to a state of society that is in our near future, where accelerating technological change is projected to have huge transformative consequences. This text considers the human capital development consequences and necessary transformations in education to meet the needs of a rapidly transforming society, and looks into some of the challenges facing Knowmad Society in an era of accelerating change.
The paradoxical co-existence of “Education 1.0” in “Society 3.0”
Society 1.0 refers to the agricultural to industrial-based society that was largely present through the 18th century through the end of the 20th century. In the early portion of this period, economic activity was centered on family-based enterprises. Children learned at home, and children worked at home. Kids and adults were engaged cross-generationally. Not only were children valuable contributors to the economy at all levels, but adults and kids learned from each other. This paradigm facilitated “learning by doing,” which was formally adopted by organizations such as 4-H, which embraced the principle that if you teach youth ideas and skills, they would, in turn, teach their parents (4-H, 2010).
The rise of the industrial economy saw growth in wage and salary-based enterprises. Kids began to work at low-level, and often dangerous jobs, until they were segregated from the workplace to maintain their welfare. Thus also began the industrialization of education, where, separated from the primary production economy, children were placed into an institutional mechanism where kids learned skills from adults (and not vice-versa), and eventually emerged from the system as “educated,” young adults, immediately employable for the industrial economy.
In Society 1.0, we interpreted data – leading to the information age. By and large, our relationships were hierarchical. That is, was easy to tell how we related with each other. Companies had reporting structures that were easy to decipher. And, we had siloed jobs and roles within organizations and communities. Moreover, we did everything we could to avoid chaos and ambiguity.Leading toward the end of the 20th century, this model worked fine. It was easy to understand. It was easily operationalized. And, it benefitted from an education system that produced workers for the industrial-modeled economy.
By the end of the 20th century, the industrialization of education and proliferation of meritocratic academic structures in the 1.0 paradigm all but eliminated the recognition of “learning by doing.” Moreover, this evolved norm generally provided socioeconomic advantages for those that successfully navigated the industrialized meritocracy (better jobs, better pay) than those who avoided it or did not survive the system .
The appearance of Society 2.0 is associated with the emergence of the knowledge society that materialized in the 20th century (see esp. Drucker, 1969, 1985). Information needed to be interpreted, necessitating the creation of knowledge workers. However, as Polyani (1968) explains, the nature of knowledge, itself, is personal and is composed of tacit and explicit components. They combine in the creation of personally-constructed meanings that defy the absolute objectivity of Society 1.0’s industrial information model. Moreover, as social animals, humans engage in social networking activities and share their personal knowledge across ever complex systems. This growing ecosystem of personally-constructed meanings and values facilitated the creation of the field of knowledge management in the latter half of the 20th century, which attempted to manage the new elements of chaos and ambiguity related to personal knowledge that were inputted into organizational systems.
Advances in information and communications technologies (ICTs) facilitated the broadened production of socially-constructed meanings. Many of these advancements are made possible through the convergence of the Internet (which has become the symbol for all things networking – personal and technological) and globalization, opening potentials for globally-aware and globally-present social networks. Tools that harness ICTs are being used not only to share ideas, but also to create new interpretations. A few scholars (see, for example, Mahiri, 2004) recognize this a “cut-and-paste” culture. One potent example of this cultural shift is hip-hop, which remixes and reuses sounds, lyrics, and imagery to create new meanings that are as much unique and individual to the hip-hop artist as the creator and the original source works. Other examples include the products of “Web 2.0” tools (see esp. Cobo Romaní & Pardo Kuklinski, 2007, for a detailed list and discussion) that allow individuals to harness new social networks to remix and share ideas and media (e.g., blogs, wikis, and YouTube).
The mass availability of these tools also allows everyday people to participate in an expanded array of vocations and citizen engagement. For example, tools such as blogs, Twitter and YouTube allow for the formation of citizen journalists, who are able to directly compete with mainstream media at a miniscule fraction of the cost that mainstream media needs to develop and deliver content . The technologies also allow for the formation of citizen scientists. By donating computing processing time, non-scientifically trained individuals can search for signs of extraterrestrial intelligence (SETI@Home project), search for a cure for cancer (Folding@Home), and examine stellar particles retrieved from space (Stardust@Home). Likewise, the Audubon Society has long relied on its social network of professional and amateur birdwatchers to generate a statistically accurate estimate of birds within a given area. Furthermore, technologies allow for the greater democratization of markets, creating citizen capitalists that invest in a global market for ideas, talent, products, and other capital.
Social-orient ICTs carry constraints and limitations that forces individuals to transform how they think and act. For example, Twitter and mobile telephone short message services limit message sizes to 140 characters or less, forcing content producers to deliver clear, concise messages in limited space.
These transformations are leading to new questions for social and educational theorists that are still being debated – and research suggests that these changes are impacting the fundamental organization of the human brain (see esp. Small & Vorgan, 2008). Some key questions arising are: Does Society 2.0 dumb people down, or are we creating a new, hyper-connected, social super-intelligence? If technologically-savvy youth are composing their thoughts in 140 characters or less, are we facing a loss of literacy? In a world of Twitter, do we have any capacity for full-length novels? In a world with YouTube, can we sit through feature length films? Is technological change, paired with globalization, leading to a loss of our cultural heritages? And, finally, what is needed from education to remain relevant in a cut-and-paste society where information flows freely?
“The future is already here – it’s just not evenly distributed.” – William Gibson (interviewed in Gladstone, 1999)
For most of us, Society 3.0 is in the future – possibly in the distant future. But, for a few people leading the change toward this proto-paradigm, it is very real. Three drivers are leading us to the formation of Society 3.0, which describes a world that is somewhere between “just around the corner” and “just beyond the horizon” of today’s state-of-the-art:
- Accelerating technological and social change;
- Continuing globalization and horizontalization of knowledge and relationships; and,
- Innovation society fueled by knowmads.
Kurzweil (1999) postulates a theory he labels the Law of Accelerating Returns to describe the evolutionary process that leads to accelerating technological and social change:
As order exponentially increases, time exponentially speeds up (that is, the time interval between salient events grows shorter as time passes). (Kurzweil, 1999, p. 30)
Figure 1. Accelerating Technological Change
[Note. The J-curve of accelerating change illustrates the exponential development and exponentially reduced costs of technologies. One example is evident in the evolution of microprocessors, which follow Moore’s (1965) Law of doubling the number of transistors on integrated circuits every two years, while also reducing the costs of associated processing speed, memory capacities, etc. The inflection point on the graph is the approximate location of the Technological Singularity, at which point change occurs so rapidly that the human mind cannot imagine what will happen next. One way of thinking of the magnitude of accelerating change is that if Moore’s Law is followed for the next 600 years, a single microprocessor would have the computational equivalency of the known Universe (Krauss & Starkman, 2004).]
In other words, change is occurring rapidly, and the pace of change is increasing. Kurzweil’s idea is founded on the proposal that as technologies evolve, the technologies improve, costs decrease; and, in turn, the process of technological evolution advances and speeds itself up, creating a J-curve of exponential, accelerating change (see Figure 1, above). As technologies evolve, so will society (Morgan, 1877). This acceleration of change, however, is also expected to impact human imagination and foresight. Vinge (1993) terms the theoretical limit of human foresight and imagination (illustrated as the inflection point on the above graphic) as the Technological Singularity. As the rate of technological advancement increases, it will become more difficult for a human observer to predict or understand future technological advancements.
Given the rate of exponential advancement illustrated by Kurzweil (2005), the rate of technological advancements in the future may seem nearly simultaneous. At this point, Vinge and Kurzweil hypothesize society will reach a point labeled the Technological Singularity. Kurzweil further believes the Singularity will emerge as the complex, seemingly chaotic outcome of converging technologies (esp. nanotechnology, robots, computing, and the human integration of these technologies).
As previously noted, technological change facilitates social change. Near future technological advancements are therefore expected to ignite periods of social transformation that defies human imagination today.
The impacts of accelerating technological and social changes on education are enormous. Today’s stakeholders in our youths’ future must prepare them for futures that none of us can even dream are possible.
Continuing globalization is leading to a horizontalized diffusion of knowledge in domains that were previously siloed, creating heterarchical relationships, and providing new opportunities for knowledge to be applied contextually in innovative contexts. In learning contexts, this means that we are becoming not only co-learners, but also co-teachers as we co-constructively produce new knowledge and its applications.
Table 1 summarizes key differences between the three social paradigms that we explore in this book. In the shift from Society 1.0 to Society 3.0, basic relationships transform from linear, mechanistic and deterministic order to a new order that is highly non-linear, synergetic and design-oriented. The effects of accelerating change suggest that causality, itself, may seem to express anticausal characteristics, due to the near instantaneousness of events experienced by a society in a period of continuous, accelerating change. Therefore, how reality is contextualized (and contextually responded to) becomes much more important to citizens in Society 3.0 than it was in previous paradigms.
Table 1: Societies 1.0 through 3.0 across various domains
Knowmads in Society 3.0
A knowmad is what Moravec (2008a) terms a nomadic knowledge and innovation worker – that is, a creative, imaginative, and innovative person who can work with almost anybody, anytime, and anywhere. Moreover, knowmads are valued for the personal knowledge that they possess, and this knowledge gives them a competitive advantage. Industrial society is giving way to knowledge and innovation work. Whereas the industrialization of Society 1.0 required people to settle in one place to perform a very specific role or function, the jobs associated with knowledge and information workers have become much less specific in regard to task and place. Moreover, technologies allow for these new paradigm workers to work either at a specific place, virtually, or any blended combination. Knowmads can instantly reconfigure and recontextualize their work environments, and greater mobility is creating new opportunities. Consider, for example, coffee shops. These environments have become the workplace of choice for many knowmads. What happens when the investment banker sitting next to the architect have a conversation? What new ideas, products, and services might be created?
The remixing of places and social relationships is also impacting education. Students in Knowmad Society should learn, work, play, and share in almost any configuration. But there is little evidence to support any claim that education is moving to the 3.0 paradigm.
- Are not restricted to a specific age.
- Build their personal knowledge through explicit information gathering and tacit experiences, and leverage their personal knowledge to produce new ideas.
- Are able to contextually apply their ideas and expertise in various social and organizational configurations.
- Are highly motivated to collaborate, and are natural networkers, navigating new organizations, cultures, and societies.
- Purposively use new technologies to help them solve problems and transcend geographical limitations.
- Are open to sharing what they know, and invite the open access to information, knowledge and expertise from others.
- Can unlearn as quickly as they learn, adopting new ideas and practices as necessary.
- Thrive in non-hierarchical networks and organizations.
- Develop habits of mind and practice to learn continuously.
- Are not afraid of failure.
(Note: List inspired by Cobo, 2008)
When we compare the list of skills required of knowmads to the outcomes of mainstream education, we wonder: What are we educating for? Are we educating to create factory workers and bureaucrats? Or, are we educating to create innovators, capable of leveraging their imagination and creativity?
Invisible learning a new expressions of human capital development in Knowmad Society
Knowmad Society necessitates the transformation from industrial paradigm, “banking” pedagogies (see esp. Freire, 1968) that transmit “just in case” information and knowledge (i.e., memorization of the world’s capitals) toward modes that utilize the invisible spaces to develop personally- and socially- meaningful, actionable knowledge. There is growing recognition that people with unique, key knowledge and skills (i.e., knowmads) are critical for the success of modern organizations. Godin (2010) argues successful people in today’s organizations serve as “linchpins.” From an interview with Goden by Hyatt (2010), Godin states:
The linchpin insists on making a difference, on leading, on connecting with others and doing something I call art. The linchpin is the indispensable one, the one the company can’t live without. This is about humanity, not compliance.
In their book, The Element, Robinson & Aronica (2009) interview many people who have experienced success in their careers, and identified that the people they spoke with found their “element” – that is, their success was largely due to the fact that they did something they enjoyed in addition to being good at it. This runs contrary to the “just in case” industrial model of education, and suggests that if we enable more people to pursue their passions and support them, they can achieve success.
In the 3.0 proto-paradigm, the inherent chaos and ambiguity related to tremendous technological and social changes call for a resurgence of “learning by doing.” In a sense, we are creating the future as we go along. As co-learners and co-teachers, we are co-responsible for helping each other find our own elements along our pathways of personal, knowmadic development.
How do we measure learning in the invisible spaces?
The cult of educational measurement
A key concern for policymakers and other stakeholders in education is, what is being learned? In an education system focused on industrial production, this is an important quality control issue.
The linearity of the industrial paradigm thrives on mechanical processes. For example, groups of learners are expected to read books progressively, chapter-by-chapter, and recite the information and “facts” they acquired linearly through memorization. In this paradigm, the use of summative evaluation (i.e., tests) is de rigueur.
Throughout the world, we have adopted this culture of industrial learning and evaluation en masse, and created a cult of educational measurement to support it. In the United States, this is manifested through the testing requirements of the No Child Left Behind Act. In Spain, the cult is evident in the filtering processes that lead to the Prueba de Acceso. In the United Kingdom, it is expressed within the National Curriculum (Education Reform Act of 1988). And so on.
With policies with names like “No Child Left Behind,” it is hard to disagree: is the alternative to leave children behind? The unfortunate reality, however, is that in these industrial policies we tend to leave many children behind. These industrial-modeled, testing-centric regimes produce exactly the wrong products for the 21st Century, but is appropriate for what the world needed between the 19th century through 1950. As Robinson (2001) and others have argued, these fractured memorization models oppose the creative, synthetic thinking required for work in the new economy and effective citizenship.
Leapfrogging beyond the cult of educational measurement
Focus on how to learn, not what to learn.
In the Invisible Learning proto-paradigm, rote, “just in case” memorization is replaced with learning that is intended to be personally meaningful for all participants in the learning experience. Moreover, the application of knowledge toward innovative problem solving takes primacy over the regurgitation of previous knowledge or “facts.” In essence, as discussed in the previous chapter, students very much become knowledge brokers (Meyer, 2010).
Moreover, the Invisible Learning paradigm enables students to act on their knowledge, applying what they know to solve problems –including problems that have not been solved before. This contextual, purposive application of personal knowledge to create innovative solutions negates the value of non-innovation-producing standardized testing.
The “learning by doing” aspect of Invisible Learning that focuses on how to learn rather than what to learn suggests that measurement or evaluation needs to be outcomes-based in the same way that we evaluate innovations:
- What happened?
- Did something new happen? Something unexpected?
- Was there a positive benefit?
- What can others learn from the experience?
Although there is a large body of literature supporting the need for formative assessments in education (see, for example, Armstrong, 1985; Marzano, 2003; Stiggins, 2008; Stiggins, Arter, Chappuis, & Chappuis, 2007), as well as a rich educational literature theory base that suggests we need to move toward learner-centered learning (perhaps the most vocal being Dewey, 1915; Freire, 2000), summative evaluations still persist in formal learning environments that present little value to the learner. Strategies to bring the informal into the formal are already present and widely adopted in business, industry, and, ironically, within some teacher education programs.
For example, Pekka Ihanainen (2010) explains that Finnish vocational teacher education, for example, is built on a dialogical professional development model. Knowledge and expertise areas of the teachers in training are identified and compared with their occupational competency requirements and goals. Following this assessment, career development trajectories and educational pathways are developed. The system is not designed to determine only how teachers in training meet state requirements, but also relates to their individual interests and professional development goals.
Finally, releasing ourselves from the cult of measurement requires faith and confidence that we are always learning. As we will discuss in the following chapters, as human beings, we are always engaged in learning– it is one of our most natural activities.
Implementing Invisible Learning: Making the invisible visible
The difficulties in mainstreaming Invisible Learning in Western education are daunting. Formal systems are deeply entrenched. Governments believe in the formal approach (it looks good on paper and within state and national budgets). Entire industries (i.e., textbooks, educational measurement) are built around it. And, the scale of the industrialization of education leaves many people wondering if it’s worth fighting against.
The system is further reinforced, by design, to change at a glacial pace. While markets can transform and reinvent themselves virtually overnight, governments cannot. They are designed to be slow and deliberative. As a result, they tend to lag significantly and react to change more often than they proactively design orpreact to beneficial changes.
Paradoxically, despite being key components of systems most responsible for developing human capital and human development futures, education is designed to change even slower. Educational institutions and systems report to governments, respond to governmental policies, and align their programs to satisfy requirements and funding formulae established by legislative bodies. Moreover, these criteria, including establishing what to teach, depends on who sits on what committee at any given time. By relying on personalities, political gamesmanship, and feedback-looped special interests from the formal educational industrial complex, many question if the system has perhaps become too large, too slow, and unfocused.
The problem is, the emerging pressures of Society 3.0 require educational transformation today. Schools need to develop students that can design future jobs, industries and knowledge fields that we have not dreamed of. Schools need to operate as futurists, not laggards.
Is educational reform worth fighting for?
Rather, it’s time to start anew. As Sir Ken Robinson eloquently states, we need a revolution, not reform (TED, 2010).
Revolutions are difficult to ignite. An entire genre of literature that Carmen Tschofen terms “change manifestos” has emerged in education that is rich in calls for change, but falls flat on actually creating the change it calls for (Moravec, 2010). The system, perhaps, has too much inertia. As Harkins and Moravec (2006) suggest in their “Leapfrog University” memo series to the University of Minnesota, perhaps a parallel approach is necessary.
Rather than fighting the system, students, parents, communities, and other life-long learners can invest in establishing parallel, new schools and/or networks of learning, discovering, innovating, and sharing. And some communities are already leading the way with innovative initiatives. For example:
- Shibuya University Network (Japan): “Yasuaki Sakyo, president of Shibuya University, believes that education should be lifelong. At Shibuya, courses are free and open to all; classes take place in shops, cafes and outside; and anyone can be a teacher” (CNN, 2007). In essence, the entire community and its environment have become the co-learners, co-teachers, and classroom.
- The Bank of Common Knowledge (Banco Común de Conocimientos, Spain) “is a pilot experience dedicated to the research of social mechanisms for the collective production of contents, mutual education, and citizen participation. It is a laboratory platform where we explore new ways of enhancing the distribution channels for practical and informal knowledge, as well as how to share it” (Bank of Common Knowledge, n.d.).
- TED.com (Technology, Entertainment, Design, USA) challenges lecture-based education by creating “a clearinghouse that offers free knowledge and inspiration from the world’s most inspired thinkers, and also a community of curious souls to engage with ideas and each other” (TED, n.d.).
Redefining human capital development
To move forward in making Invisible Learning visible, we need to engage in conversations on what futures we want to create. We need to clarify our visions of the future. In China, India, and throughout much of the developing world, the vision is simple: Catch up to the West through planned development. But, in the United States, Europe, and much of the rest of the Western world, concrete visions of where we want to be in the future are absent. We assert that we either do not know where we want to be in the future or we lack the foresight to imagine ourselves in a future that is very different from today.
The consequence is that we are not making investments into our human capital development systems that will enable us to meet needs set by future challenges. We need to prepare our youth and other members of society for a future and workforce needs that we cannot imagine. Moreover, given the potential for today’s youth to be engaged productively in a “post-Singularity” era, it is important to assist them in the development of skills and habits of mind (i.e., the Leapfrog Institutes’ liberal skills outlined in the “Leapfrog” memo series archived at Education Futures). that will foster life-long learning and the innovative applications of their knowledge.
This lack of vision –and acting on it– impacts not only education, but also other areas of our socioeconomic wellbeing. Bob Herbert (2010) recently wrote for the New York Times on the United States’ new unfound willingness to invest in ideas that could increase potentials for future growth and prosperity:
The United States is not just losing its capacity to do great things. It’s losing its soul. It’s speeding down an increasingly rubble-strewn path to a region where being second rate is good enough. (Herbert, 2010)
As organizations, communities, and nations, we need to set visions for the futures we will co-create, and act upon them. Throughout the remainder of this volume, we explore some of the methods individuals, teams, and organizations may employ to help develop these visions of the future.
Using technology purposively
When engaged in conversations about invisible learning or other innovations in education, there is a tendency for people to gravitate their thoughts toward technology as if it can serve as a “silver bullet” to slay the allegorical werewolf of the persistence of the Education 1.0 model. Innovation in education does not mean “technology.” Douglas Adams (1999) elaborated on the challenges of defining the purpose of the Internet:
Another problem with the net is that it’s still ‘technology’, and ‘technology’, as the computer scientist Bran Ferren memorably defined it, is ‘stuff that doesn’t work yet.’ We no longer think of chairs as technology, we just think of them as chairs. But there was a time when we hadn’t worked out how many legs chairs should have, how tall they should be, and they would often ‘crash’ when we tried to use them. Before long, computers will be as trivial and plentiful as chairs (and a couple of decades or so after that, as sheets of paper or grains of sand) and we will cease to be aware of the things. In fact I’m sure we will look back on this last decade and wonder how we could ever have mistaken what we were doing with them for ‘productivity.’ (Adams, 1999)
Moreover, we use the term “technology” to describe new tools that we do not understand. In other words, the purposive uses of “technology” are not well defined. As a result, in educational contexts, we often take the best technologies and squander the opportunities they afford us. Roger Schank (in Molist, 2010) puts it bluntly:
It’s the same garbage, but placed differently. Schools select new technologies and ruin them. For example, when television came, every school put one in each classroom, but used it to do exactly the same things as before. The same with computers today. Oh, yes, we have e-larning! What does it mean? Then they give the same terrible course, but online, using computers in a stupid way.(Molist, 2010)
Conversely, the Invisible Learning approach to technology is purposive, pragmatic and centered at improving the human experience at its core. Specifically, this means that it is:
- Well-defined: The purpose and applications of particular technologies need to be specified. Bringing in technologies for the sake of using technologies will likely lead to their misuse, underuse, and/or the creation of unintended outcomes.
- Focused on developing mindware: The focus of technologies should not be on hardware or software, but on how they enhance our mindware – that is, they focus is placed on how technologies can support our imaginations, creativity, and help us innovate.
- Social: The use of technologies is often a social experience and their social applications should be addressed. This includes the leverage of social media tools for learning such as Facebook, Twitter, etc., which are commonly blocked from formal education settings.
- Experimental: Embraces the concept of “learning by doing,” and allows for trial and error which can lead to successes and the occasional failure – but does not create failures.
- Continuously evolving: As an area for “beta testing” new ideas and approaches to problems, it is continuously in a state of remixing and transformation. As society evolves continuously, so must our learning and sharing.
Who gets to leapfrog to Knowmad Society?
Lastly, a problem facing Invisible Learning is one of equity and equality. Is it appropriate for a select group of “invisible learners” to leapfrog ahead of peers who may be trapped within the paradigm of “education 1.0?” If 1% of the population benefits from Invisible Learning, what should we do about the other 99%? Should they not have the right to leapfrog ahead, too?
We believe so. But, we also recognize the incredible inertia mainstream Education 1.0 possesses. Given rates of accelerating technological, social and economic change, we cannot wait. The revolution in learning and human capital development needs to begin now. This may mean starting out small, working parallel with entrenched systems, but it also means we need to lead by example.
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