Knowledge Networks in the Exponential Age

?Knowledge Networks in the Exponential Age

?Background

A tsunami of social change is coming, brought about and sustained by knowledge expansion (Azeem, 2021). Ideas encourage wealth to ply innovation to develop society. Until more students achieve high levels of cognitive skills, it is unlikely that advanced reasoning can take root in future everyday societal activities. The greater the knowledge, the more opportunity and income growth, allow even more opportunity to avail itself. Knowledge networks imply that everyone benefits directly or indirectly from large numbers of peers who train hard to improve thinking skills in any activity. The resulting skill base provides awareness in populations to succeed economically, engage politically, advance socially, and participate culturally.

Knowledge networks set the stage for improving problem solving capability. In advanced societies this shift in knowledge expansion allows society to stay ahead of the global learning curve. Emerging societies first need to build foundation skills to support cognitive skill development. It seems increased knowledge neither affects GDP below some thresholds nor above some ceiling effect – possibly because so few countries have reached that point yet. Nevertheless, knowledge is important because without sufficient amounts available to society, wealth creation is limited in poor economies and in advanced countries finds complacency to learn more. When group formation stagnates, then both individual and societal traits such as ambition, connectivity, and mobility cannot entertain dialectics and bubble talk.??

Chapter One asked how knowledge influences societal wealth (GDP) through skill networks. Chapter Two explained how knowledge compounds problem-solving skills through complexity. Chapter Three added the ingredients of values and attitudes to the mix. In that chapter we looked into how two-way contacts involving dialectic reasoning and bubble conversation influence human capital, R&D, and capital investment. Knowing how knowledge networks accelerate the rate of societal development across stages of economic growth, helps us too see what economies will look like in the future?

Big changes come when the transition of nations to two-way communication allows acceleration of knowledge expansion both in supply and demand for products and services. Lower-middle-income countries having majority one-way communication networking provide the knowledge foundation to create advanced networks that eventually shift the rate of GDP expansion to levels found in advanced economies.

On the other hand, as rich nations move into digital economies they expand two-way advanced thinking and emotional reasoning to keep pace with GDP growth. This process is relatively straightforward but is actually hard to accomplish without awareness and investment planning in a deliberate and purposeful policy framework (e.g., environment, finance, social welfare, business, manufacturing, transport, etc).

The benefits of two-way communication supporting deeper network exchange of dialectic and bubble dialogue are greater than one-way exchange of information. As indicated in Chapter Three, one-way information flow does not cut it when it comes to transferring knowledge. Put simply, critical thinking and complimentary values of open-minded and future orientation help explain why two-way interactions are powerful in putting resources to use. Empirical evidence suggests two-way communication expands geometrically among greater numbers of advanced thinkers as indicated by the Metcalfe Law.

Over time nations build up their cognitive infrastructure by reassembling their national mental space of rows and piles of facts, generalizations, and theories acquired by citizens. Ultimately society can incorporate all manner of knowledge and skill levels used by all manner of people in all manner of situations. This national knowledge base represents an assessment of the aggregate supply and demand for knowledge.

This supply and demand structure of knowledge combines all ways of knowing with all types of social dispositions to add value to the flow of ideas among individuals to communities. There is a point reached where cognition along with personal attitudes allow dialectic reasoning to flourish in problem solving. The process of learning evolves to where complex ideas produce self-organizing ideas that blend activity.

With dialectics in hand, individuals are exposed to new ideas from others that feed into the continuous flow of useful ideas. The concept of bubble mobility explained in Chapter Three ?demonstrates how new ideas move between like-minded people when one-way and two-way levels of knowledge application are compatible. Individual curiosity seeks out chance encounters in daily life.

Both dialectical reasoning and bubble contacts help explain how and why some individuals remain stuck in one-way network connections while others having similarly limited skills but a desire to learn desperately grasp onto complex ideas. More importantly, individuals who acquire advanced skills and attitudes are well placed to develop new ideas based on dialectic processes and bubble contact that create clusters of expertise.

With a firm grasp of non-cognitive values and beliefs influencing critical thinking, reasoning becomes more balanced, user friendly, and better monitored. It appears individuals can transcend applying advanced thinking skills to complex societal problems by raising human development to higher levels of personal meaning. One can think of this human development process as comprising sequential stages of improvement over the life cycle as humans strive for perfection. This is what is suppose to take place as greater experience and opportunity result from higher levels of GDP noted in Chapter One.

If enough citizens can transition to two-way connections sharing ideas, the effect can catapult the greater society into a higher growth path that wisely and effectively meets the needs of the nation. Once operational, smart productivity can continue indefinitely like a well-oiled machine if attended to regularly.?Development specialists need to look closely at the overall role that knowledge offers in directing a society to meet the needs of its people.?

From the Individual to the Nation

The ontogeny of cognitive and non-cognitive development refers to life stages of the individual that direct maturation. Skills move from simple to complex allowing growth to benefit from advance knowledge connecting ideas. As self-organizing skills arise, cognitive links add value to refinements in thinking found in homes, schools, hobbies, and with acquaintances. Likewise, phylogeny or the study of relationships among collections of individuals applies to the evolutionary history of society as a whole. The more that individual skills improve, the greater chances for new experiences to arise for the entire society. Societal evolution proceeds by adding to preexisting stages throughout human development.

Society can collectively replicate societal influences on human well being once the ontological stages of growth in individuals make human character stronger in facing challenges. In a sense both individuals and societies become self-organizing as each learn from the other to apply dialectical reasoning and bubble diplomacy to transform one-way to two-way networking. Societies that promote individual development in the aggregate end up reinforcing network efficiency. In this case, societies do not have to reinvent the wheel. They just have to accentuate creativity through institutions, people, ideas, places, things, and ideas that constantly innovate individual activity. It should be no surprise that homes and schools are most collaborative when they keep abreast of trends in social research.

?The Growth Transition

Put into the broader framework of development, society produces better goods and services to create societal wealth and income as human knowledge expands. The growth formula can be given by:

Y = R (N, K, A)

where Y is national income, R is knowledge that impacts labor (N), capital (K), and technology (A) in the form of human capital, physical capital, and R&D respectively (Romer,1994, Agenor, 2009). Together these inputs can coalesce into the modern curricular-digital economy by shaping public and proprietary knowledge to support environmental protection, scientific inquiry, equity, trade, work, human capital, technology, and financing. Knowledge mingling across activities also affects society through general well being, human relations, social services, work and leisure.

Pulling together labor, capital, and technology mediated by knowledge tend to create the higher GDP that sets the pattern in motion for national development including knowledge expansion. Figure 4.1 displays another example of rotating gears demonstrating how knowledge-driven complementarities spur progress when two-way communication drives each input.

All the while each nation employs its own model to generate national income, which places the country on a unique growth path. As these inputs improve in efficiency, the trajectory shifts to higher growth that GDP measures. However it may be constructed, the economic growth model is a way to think about how development proceeds especially when advanced knowledge is added to the mix.

Figure 4.1: Interaction Among Growth Inputs in Digital Economies

The concept of “steady-state” denotes the level of economic equilibrium reached at any point in time. In equilibrium, the growth rate of capital equals the growth rates of output when labor, capital, and real output all grow at the same rate. In that sense, steady-state is a snapshot of a given income level equilibrium supporting a given standard of living measured by output in goods and services. Each trajectory starts at some initial per capita income level and remains until some economic shock lifts the economy out of its current growth path. For example, countries up to $25,000 per capita GDP found in Chapter One settle into a state of income equilibrium that limits two-way interactions from increasing en masse.

Once all potential labor and capital are tapped, more growth comes from small increments of population growth but mostly from new production methods that stretch the productivity of the existing workforce and capital outlay. This new pattern increases income but also ultimately decreases again as diminishing returns set in until quality innovations are added. Countries with around $40,000 to $55,000 GDP identified in Chapter One fall into this group that provides decent standards of living to a majority of citizens but without wide scale sustainable knowledge effects.

Advanced stages come later when added population and capital accumulation are declining. In these cases the prime growth initiator is left almost entirely to technology through marketable innovations in human development and organizational streamlining. This advanced stage of development requires careful attention be paid to increasing stocks and flow of knowledge research that provide the fuel for innovation to flow throughout economies (ILO, 2010).

Advanced economies with more smart people among the total are better able to solve the many complex problems facing society with greater confidence. These countries take advantage of two-way communication to advance public goods including environmental concerns, health, education, social enterprise, and trade.

So far few countries have fully achieved this knowledge-based growth path emanating from digital innovation. Countries above $60,000 GDP found in Chapter One fall into this group of early adapters struggling to accelerate into sustainable advanced knowledge growth trajectories.

?Group Clusters Transform Social Divisions and Occupations

As knowledge invigorates labor, capital, and innovation, growth models transform trajectories observed in Chapter One through cognitive and non-cognitive skills that support networking. In the race from one-way to two-way thinking, advanced reasoning affects productivity through technology and shifts in occupations.?In the emerging digital world, human skills compete with artificial intelligence to improve production through effective human capital, R&D, and financial investments noted by Kissinger and Schmidt (2021).

Technical innovation can lead to positive effects from things like genome sequencing, 3-D printing, quantum mechanics, astrophysics, telekinetics, and much more as innovations reconfigure the way society operates. In turn, occupations change to meet these technological changes especially on the Internet, Cloud, virtual and augmented telecoms, each comprising the elements of the coming metaverse. Big knowledge analytics and advanced cognitive skills make people highly productive without turning them into one-way interaction automatons that click, pay, and watch.

Smart critical and creative reasoning are key to economic development because they enable the majority of citizens to acquire resilience in applying problem solving to areas of special interest and importance that yield greater individual benefit. When the majority of society attains higher problem solving, knowledge can shape and accelerate socio- economic development. This is the sweet spot in nation building.

Social Mobility

Gilbert-Rolfe (2019) of the EU and EU Commission (2019) research on digital technology suggest occupations are changing job selection, work participation, inequality outcomes, and shifts in economic status across the digital divide. Within this scenario possibilities arise where the middle-class declines, jobs get polarized, financial inequalities and life chances are altered along with new types of economic relations expanding boundaries between labor, capital, and technology.

In turn, these changes increase social stratification favoring wealth advantage that encourage the already advantaged to acquire technical skills and education in both developing and advanced countries. Increasingly, computer skills provide job streaming for the Internet savvy that can increase income and status.

It appears the top 5-10 percent in any society can write their own ticket, another 35 percent are in demand in all fields, and the rest must rely on stealth to maintain position in the new social hierarchy. Social divisions become far less equitable as the top 45 percent parlay income and earnings into rent-seeing activities and stock market investments to increase wealth. In the meantime, others fall further behind because they lack the cumulative advantage of living in stable environments.

Historically, as economies develop and mature, the middle-class moves from perhaps 25% of the population participating in the formal sector in emerging societies (c.f., the Philippines) to 75% upper and middle class groups in a well-functioning industrial economies (c.f., Spain, Chile). However, economies can decline dramatically when inequality emerges in digital economies. Finally, in rising digital economies (c.f., Singapore), there can be either increased inequality to a 35-65 percent top-bottom distribution, or move toward a 50-50 balance if equality takes hold, and everyone exercises their best skills to the fullest (Figure 4.2).

Figure 4.2: Hypothetical Percentage Levels of High, Middle, and Low Social Divisions in Societies

There is need for new taxonomies and analytical tools to monitor social position and life chances across the globe. Special attention should focus on equality of opportunity based on probabilities for success by segments of the population to overcome unfair disadvantage. The digital economy may weaken boundaries across formal, non-formal, and in-formal learning as knowledge accelerates, which can be good if talent and motivation are allowed to move freely. At the same time, knowledge can either increase or decrease mobility depending on how well knowledge gets distributed across the population.

Occupational Mobility

Growth models create new occupational structures affected by technical progress.?The new occupational structures (Danbi et.al., 2021) are lighter on structure and formal organization leading to collaborative team projects. Societal demographics also affect growth process of nations as rising household income signals better times ahead for offspring. Cognitive skills along with attitudes and behaviors alter work relationships in manufacturing by deploying more robotics, and algorithms with fewer manual workers resulting in more computers and less brawn.

Occupations move from traditional industrial economy groupings of skilled trades and factory workers to a digital classification of entrepreneur/gig employment. These changes can either improve or harm equity and fairness depending on how well individuals relate to technology. Technology is the main driver of change that allows two-way communication to thrive (even between people and machines) while one-way talk declines.?Work characteristics required in the digital society include: connectedness, sharing, personalization, directness, and tracking as jobs in the economy fall into a set of new categories. Past traditional jobs ranging from professionals and managers, supervisors, technicians, clerical-sales, skilled trades, day laborers get re-invented.

The new reality involves social mobility in advanced economies with half the population working in office or self-employed based on skill connections in the corporate-business establishments. The remaining 50% found in increasingly marginalized jobs or unemployable. All the while, emerging society occupational structures remain mired in routine work and care giving, which is labor intensive, and will survive for another 20 years given ample labor and overly expensive robotics.

Then again, occupational structures re-organize to process more knowledge in digital societies. Agility in reasoning makes for better employers, employees, and the self-employed as working conditions change on the warehouse floor and assembly line; collaboration ensues in the office; technical advances increase R&D in the laboratory; and sharing chores in the home reduces inequities. In the realm of technology, advances accelerate as more innovators collaborate in solving problems when many sharp minds address all sorts of societal problems.

Figure 4.3 suggests five core-occupational choices people increasingly face in the modern economy. When youth think about their future, they are confronted with set of choices revolving around career, family, independence, and adventure, of which some are less formal settings. In choice-making decisions both hard and soft skills dictate entry into two-way interpersonal relationships that create successful choices.

Cognitive skills combine information and concepts into problem solving methods while soft skills of curiosity, open-mindedness, and collaborative decision-making are crucial to making good choices. Ultimately, each group of youths face different probabilities of success as with offspring of professional parents versus those from single parent inner-city families.

Figure 4.3: Potential Core Job Choices Linked to Occupations

?

Net Effects of Knowledge Expansion

Dialectic and non-cognitive bubble networking, one-way and two-way clustering, networking science with high quantity-quality social contacts all feature in knowledge expansion. This increase in advanced knowledge among the population accelerates sharing and the flow in problem solving that exponentially increases societal development. The 80/20 rule enumerated by Richard Koch that found 20 percent provide 80 percent of effort impacting exponential growth is similar to the formula in Chapter One. This ratio implies that two-way clustering drives societal expansion when advanced problem solvers play a deciding role over and above the many one-way connections found at elementary and intermediate levels.

The question remains as to whether digital technology ultimately deepens SES chasms or provides new opportunities for the many. Clearly, the evolution of workplaces expand boundaries when flexibility in work from home and zoom conferencing add to collaboration. The majority of youth stand to benefit from more opportunities in life-changing experiences brought about by accelerating knowledge patterns that lead to sustainable growth.

Over time these pattern thresholds between emerging and lower middle-income groups transform into middle income and industrial economies. Still later industrial societies transform into digital economies with rising economic trajectories. What might that future world of two-way network thinking look like as products and services advance in occupational complexity with a focus on technology, finance, and human development that accelerate change?

?

The Future of Knowledge Expansion

Looking ahead, emerging and lower middle countries will transform themselves into more stable living conditions once technological change improves resource consumption committed to preventing environmental degradation by encouraging the circular economy. The World and the bridge by Hubbard (2021) highlights the need to undertake investment (bridges) rather than put up barriers (walls) to innovation when planning the future.

Likewise, industrial nations move toward self-organizing digital economies, when the common good supports multiplier and spillover effects espoused by Kevin Kelly. This author stresses the purchasing services over goods in the new economy where applied ideas are more important than physical objects. Networking inverts the traditional system by allowing open networks to compete with proprietary knowledge.

According to Kelly, the more opportunity taken, the more opportunity arises as open networks of common knowledge changes production and consumption. As the majority of individuals and nations gravitate to advanced levels of self-organizing thought, they all end up on the same steady-state path even though some may vie for modest supremacy.?

Looking further ahead, it remains to be seen how AI or machine learning will compete and conflict with human development as the rate of intellectual vigor increases. The knowledge that reinforces labor, capital, and technology in the above Y = R(N,K,A) equation may come from humans or machines. Two-way interactions in humans accelerate knowledge expansion especially as more of the population master two-way reasoning in dialectics and bubble consultancy.

Nevertheless, machine learning is advancing as well. As more facts and information are fed into computers, AI builds up its knowledge base useful for creating algorithms. More pictures of dogs help the computer to comprehend the concept of dog. Add attributes of dog behavior, and dog profiles even tell more about dogs. The same applies to people. Since computers absorb more information faster than humans, they discern pattern recognition and discard unnecessary inference when combining ideas quickly.?Speed is at the crux of human versus machine learning. Knowledge expansion is a prime research goal affecting the 21st century and it starts today.

Prospects for countries to advance given their current states of knowledge networks affecting development. Most advanced nations face shrinking demographics, labor forces, population momentum, innovation, too much or too little conformity or idealism or ideology, risk aversion, or risk taking. These factors occur across-the-board in China, Central Europe, EU, Japan, Korea and the US. Middle-income prospects for Indonesia, Turkey, and South Africa face similar problems on a smaller scale.

When countries employ advanced knowledge to build R&D, human capital, and capital investment, they can turn comparative disadvantage to advantage. Middle-class countries like Algeria, Bangladesh, Brazil, Bulgaria, Egypt, Indonesia, Kazakhstan, Malaysia, Mexico, Philippines, Poland, Slovenia, South Africa, Turkey, and Vietnam; all have potential up-sides in the coming years if they proceed with rapid expansion of knowledge (c.f., Table 1).

As noted, the major ingredients of growth are educated labor, capital expenditure, technological innovation, and wide-scale deep knowledge analytics mentioned earlier. Each region of the world possesses these resources to some extent, which can be used to predict future progress. North America has deep capital and technology pockets but lacks sufficient home-grown high-level educated labor, which requires importing high level human capital. It also does not invest enough in productivity-enhancing activities. The EU has deep capital and innovation pockets, but lacks sufficient educated labor due to demographic decline in key innovative?sectors.

North Asia is a third key region and it possesses relatively deep pockets of capital and large numbers of educated labor but lacks experience. It currently is strengthening local high-power innovation that requires deep thinking but this takes time, experimentation, and constant feedback. The remaining areas of the world in Latin America; Africa; Middle-east, Central Asia, and South Asia; and South-east Asia still lack local capital, highly educated and experienced labor, innovative R&D, and deep thinking triggered by knowledge expansion.

The world map portrayed in Figure 4.4 is a blank slate, which the reader can pencil in potential network links across key territories. What geographic region, population, and resource base will hook up with others to form human capital, R&D, and capital expenditure supply and demand chains for an integrated future digital world economy? Time will tell but surely reliance on knowledge will play a defining role in how wealth and power take shape. Beginning with the Library in Alexandria in ancient times, promotion and storage of knowledge is growing exponentially while humans who have difficulty catching up will likely lack the necessary skills to acquire and interpret knowledge (Loxley, 2016).

Figure 4.4: World Map with Key Digital Technology Platforms

?If the world cannot solve the many social problems facing world development, the nexus between humans and machines will accelerate at detriment to the many disadvantaged. The many one-way connections will be swamped by advanced communication technology. When countries can no longer continue to add resources through more of the same, they must learn to expand using the same resources but more wisely by adding greater quality knowledge to R&D, human capital specialization, and Fintech. The race between creating more dialectic reasoning, bubble dialogue, with machine learning will heat up, and require many individuals to enter the world of two-way reasoning. If this does not happen, human development will fall behind machine learning, and algorithms will prevail.

Two-way interactions require individuals to be familiar with knowledge depositories such as Wikipedia, Public Library, Google, Bing, You Tube, Amazon books, TikTok, various on-line book and magazine publishers, and blog sites. Access to knowledge distribution and flow involve knowledge networking connections formulated in Chapter One. That index implied systems with advanced thinkers generate greater possibilities through network links as suggested by Metcalfe’s Law and Gowel’s power in a link. The digital divide becomes detrimental when group differences in access and usage arise between rich and poor, young and old, curious and disinterested, active and passive users, as well as those change-oriented versus the status quo.?

As ideas come to rule the world, society cannot afford to fall behind the global learning curve. The future tech world will meld into an online multiverse 3-D virtual world inhabited by algorithms, avatars, and real people affecting society including: older web services like e-mail, real time 3-D computer graphics, person-to-person social interactions, support for users creating their own virtual items, links to outside systems to profit from virtual goods, and augmented reality headsets for games, cinemas, avatars, etc, as virtual and augmented techniques merge. The multiverse will no longer be two dimensional and text-heavy with limitations for those with little connectivity. The multiverse becomes the global brain on which, like little ants and bees, we add to the sum total of all that there is.

Clearly, those born around the year 2050 will either passively submit to or actively employ knowledge to improve themselves.?They will be digital and not analog, have finger dexterity, employ brain-power learning, listen to influencers, apply gadgets, live as avatars in virtual space, and find new ways to acquire and distribute wealth, religion, culture, and everything else.

?

A Look into the Future of Knowledge Unchained

What will the multiverse incorporate as digital technologies progress in innovating AI, machine learning, quantum computing and how must knowledge expansion of humans rise to meet the demands of a knowledge society??New technologies will affect all activities in manufacturing, transport, travel and leisure, schooling, work, health, shopping, information- communication, and cultural understanding. Youth in particular will have to adapt, and seniors, too, will have a challenging time to stay informed.

Consequently, the average national knowledge base will need to keep up with technical innovations applied digitally to the metaverse both in hardware and software in the cloud or in individual software apps all designed to provide access to the virtual world. The coming metaverse will expand from the current e-mail, social media, news and entertainment streaming, business and finance talking heads, science research centers and think tanks, print and digital publishing, and gaming apps. All these streaming processes will be linked totally to mobile apps built into humans.

Even more enticing will be the metaverse of augmented reality in the virtual world of avatars that live imaginative life styles that allow individuals to recreate themselves and live in a virtual world of their choosing. These places may be more desirable to “hang out” rather than in reality. Given the above scenarios which are already coming to fruition among some youth and entrepreneurs already, one can ask how can knowledge expansion support this new reality to meet the needs of individuals?

The metaverse is coming into view but it is mostly the preserve of those well-connected networks of knowledge, technology, and financial resources.?As technology progresses, so does the digital world of augmented virtual reality. People with ambition and skills for offer can build their own alternative universe of success and then collect digital payments as influencers and entrepreneurs. Along side the more crowded actual reality where assets and opportunity are in short supply, the virtual world allows individuals to prosper. The virtual world offers experience to develop skills that can be applied in the real world.

For those less able (one-way interactions) but highly emotive personalities can enter the metaverse where others build for them fantasy worlds that make believe anything they want for their self-satisfaction. However, this new virtual reality may not hold up in the real world and these followers may choose to remain living in this fantasy full time.?The metaverse is especially relevant for the creative younger generation of advanced thinkers who will inherit the virtual world. ?

Figure 4.5: Network, Web, and Metaverse Progression

How can knowledge expansion guarantee opportunity to participate in this new future world. Unless everyone has the opportunity to fully participate, social wellbeing will be lost to many. In a laissez-faire world, survival into the future will depend on knowledge acquisition gained through networking and bubble diplomacy. When knowledge proceeds at an accelerating rate, human development must maintain its position relative to the digitalization of machines. If knowledge expansion falters, AI will gain the upper hand. While a long-range consideration, this struggle between human knowledge and ignorance is of great importance in the digital world of influencers influencing the gullible.

Future technology and elite groups will dominate this process given their cumulative advantage. Two-way interactions especially among the tech savvy generation will use the Internet to actively join in an immersive metaverse experiences such as in entertainment, sports, and other opportunities.?Yet regardless of whoever controls the “airwaves,” knowledge expansion can be aided by modern digital platforms like Tik Tok, Amazon, Google, and Meta.?Each of these networks appeal to various levels of reasoning be it informing about “what” or “how” or “why.” Networking will circulate idea, dialectics will preside over logic, bubble diplomacy will limit ideas in the marketplace, and science fiction will allow an off-ramp for others. The above will create through algorithms virtual idealized worlds which exist inside the real world, and bump up against one another to compete for attention and superiority.

Conclusion

Advanced stages of individual human development and cognitive reasoning will develop over time and lead to greater experiences and opportunities for world populations that allow societal development to thrive. Increased opportunities create valuable experiences that add to human awareness. These experiences require high income from rising GDP to become commonplace. The relationship found in Chapter One showed rising GDP accelerates the flow of opportunities that create experience.

Two-way clusters transform human development stages of Piaget, Malsow, and Erikson through network clusters. The take away is simply that increased opportunities create valuable individual experiences that alter the rise of knowledge. These experiences require rising knowledge and GDP to expand together to alter learning opportunities for everyone.

Entering the exponential age of knowledge expansion pulls together all the pieces of evidence in the preceding pages. It seems current trends will continue. High levels of advanced learning will enable knowledge networks to inspire quantity and quality connectivity; higher value connections; greater density of advanced thinking groups; and the potential for mentors to pass information through dialectic debate, and bubble connections.

The distribution of knowledge across sophisticated individuals will accelerate knowledge networks as suggested by the Metcalfe Law and lead to more groups of advanced thinkers.?Once the process starts, stages of development rely on knowledge to support the economy. Even more, growth in GDP across all stages of development?proxy resources that can build local capacity needed to expand progress for the benefit of all.

The message in Chapter One argued that rising GDP accelerates the flow of experience that gives opportunity the license to aspire. This historical evolution for both individuals and groups suggest ontogeny of individual human activity recapitulates phylogeny of the collective society given the overall expanding self-development process at work in the twenty-first century. As with many other social improvements in sports, cuisine, stock market investing, science exploration, and more; the initial knowledge networking accelerates change to self-direct people and societies to do better.

Every country has its own comparative advantage and liability. Countries choosing to accelerate networking into two-way development patterns still have to face shrinking demographics, labor force, and population momentum. Advanced nations must learn to expand from within using existing resources but with greater expertise in the form of quality R&D, human capital, and financial investment. On the other hand, lower GDP countries can continue to exogenously expand adding resources including greater quality in people, credit, and off-the-shelf technology.

Implications resulting from the relationship between wealth and knowledge across stages of development suggest that knowledge expansion aids economic growth. Yet rising GDP more strongly expands the rate of knowledge than the other way around. First, more research is needed using these data sets to explore the relationship to see how results hold up. Averaging data over two decades make data more reliable.

Second, comparisons should focus on locating thresholds for stages of development when calculating points of GDP where knowledge expansion is greatest. Finally, the research should be used to track network effects of knowledge expansion on measures of societal development including occupational mobility, geographic mobility, marriage hypergamy, R&D technology, and income level.

This is the message of the book. Knowledge expansion serves as the basis for how advanced economies increase breadth and depth of knowledge through dialectics and bubble talk which speed the flow of knowledge to keep pace with machine learning in the global market. Ultimately, societies must keep in mind that knowledge is an entity onto itself that can be used by humans and machines alike in dialectic fashion to form “bubble-induced” global networks.

Knowledge, not humans, is the center of attention. Snow Crash, is a novel by Neal Stephenson (1992) who foresees a digital future that can shape society in very powerful ways that may not be healthy. Snow Crash refers to static noise on analog television sets when a transmission ends at the close of day, which can be mesmerizing, but according to some may hide sub-limitable messages within the scatter. The story is about a virus that wipes individual brains clean leaving them passive recipients trapped in the virtual world.

The virtual world of knowledge networking is coming fast. Currently, there are many problems facing humanity. If humans cannot mobilize intellectual and emotional resource skills to solve these issues, world development will stagnate. To ensure knowledge expansion raises global progress, greater two-way quality human connections are needed. Otherwise machine learning will supersede human ingenuity.

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