To See the Future and What’s Ahead

Ghost of Christmas Yet to Come

When the Ghost [appears]…three wealthy gentlemen [are] making light of a recent death…Scrooge asks the ghost to show anyone who feels any emotion over the man’s death…[but] can only show him a poor couple indebted to the man…rejoicing that the man is dead….The spirit then…shows the repentant miser his own grave; Scrooge then realizes that the dead man of whom the others spoke ill was himself. Horrified, Scrooge begs the ghost for another chance to redeem his life.

Introduction

There are many optimistic and hopeful narratives and forecasts about the future of civilization. Utopian scenarios about a Jetson lifestyle, immortality and space colonization. But these days the vast majority of future narratives and forecasts have a distinctly dystopian flavor.

To the extent there is a common thread among dystopian visions it is that civilization’s reach has exceeded its grasp. Often this leads to suggestions that, like Scrooge, civilization needs to be redeemed somehow.

Of course, any future narrative or forecast is a mixed bag. A situation former U.S. Secretary of Defense, Don Rumsfeld, once described aptly.

There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don’t know. But there are also unknown unknowns. There are things we don’t know we don’t know. (Rumsfeld, 2/12/02)

Setting aside unknown unknowns, there are solid reasons to discount most forecasts about the future — good and bad. For example, at one end of the forecasting spectrum there are those who lack any training in the art of forecasting the future (i.e., alternative futures research). As a result, many wannabe forecasters believe that merely extrapolating some visible, controversial or pet trend(s) out over some arbitrary period of time qualifies as a valid forecast.

But problems abound with this approach, starting with the fact that all trends are the result of a complex set of dynamic variables. That no trend exists in isolation and that all trends end, usually in unexpected ways. Consequently, beyond providing fodder for today’s voracious media, the value of most trend forecasts fall somewhere between worthless and a con job.

At the other end of the spectrum are those who clearly recognize the inherent complexity in generating a future forecast and thus limit their efforts accordingly. Economists and meteorologists, for example, seek to navigate this complexity by building sophisticated, quantitative computer models. While some models are better than others, modelling any open, evolving system (e.g., economy, weather, health or civilization) invariably still faces some daunting challenges:

• Incorporating only the most appropriate trends
• Including enough variables
• Weighting each variable properly
• Adequacy and timeliness of the database used
• How and what trends and variables might change over time
• Probability and impact of a nonlinear event(s)

Given these challenges it is not surprising that most forecasting models are narrow in scope with a short time horizon (i.e., days to months). To be sure, with larger databases, greater access to more diverse and real-time data feeds, more powerful computers and artificial intelligence the reliability and value of predictive scenarios generated by computer models will keep improving.

In any case, regardless of where any approach falls on the forecasting spectrum, a central tenet in the art of forecasting is that there are only four major variables of consequence: trends, events, images and actions. Thus, if the appropriate, key trends and events are successfully identified, then the development of future images and actions are primarily scenario building exercises. Scenarios which invariably sort out into generic categories of good, bad and ugly.

While this may sound straightforward, as highlighted above, all forecasting approaches are fraught with challenges and potential pitfalls. For example, one common and regularly overlooked pitfall in attempts to forecast the future of civilization is the timeframe used to start an analysis. That is, the reliance of some period in human history — an anthropocentric frame — to begin identifying and analyzing key trends and events.

But starting with human history to forecast the future of civilization is analogous to using the pre-Copernican, Ptolemaic model of the cosmos — with the Earth at the center of the universe — as a basis for forecasting the future of the universe. Not only is it the wrong model to start with, but, by its very nature, is biased against the influence and impact of any consequential trends and events operating outside of human history (e.g., astrophysical, biological). As a result, the trends and events used in a forecasting effort easily leads to the generation of scenarios that are myopic, relative, misleading or wrong.

Another common pitfall in forecasting is what seems like simple use of images and actions to build scenarios. But building worthwhile scenarios is not so simple and usually reflect one of three flavors:

• From the present to the future — common approach (e.g., trend forecast) doomed from the start
• Backcasting to the present — pseudo-scientific approach (e.g., anthropocentric frame) that is self-deluding
• Contextual backcasting to the present — least used approach (e.g., nested systems) but the only reliable one.

From the present to the future — This approach to building scenarios is similar to those used by trend forecasters. It begins with a trend or event and then seeks to identify the sequential incremental steps needed to move forward from the present toward some future goal or vision (i.e., images).

The central flaw here is that there are always far too many alternative scenarios to realistically explore. So, without testing all such scenarios — which is impossible — there is no reliable way to either winnow out the worse scenarios or judge the best ones to pursue.

In other words, this is simply a linear, trial-and-error approach to scenario development. Trend projections masquerading as a future forecast. It is, as science historian, Thomas Kuhn, said, the way “normal” scientists refine accepted scientific ideas within a profession’s prevailing paradigm. Problem is that major advances tend to reflect a paradigm shift that eventually forces everyone to relearn what is “normal.”

Said differently, any worthwhile scenario building effort must challenge the underlying paradigmatic assumptions and be concerned with the inclusion of a nonlinear event(s). Yet, inherently, this approach does neither.

Consequently, in a rapidly changing environmental milieu — like civilization is now experiencing — the likelihood of developing plausible and reliable scenarios using this approach becomes virtually impossible. So, like most trend forecasts, scenarios developed using this approach are either irrelevant, misleading or wrong.

Backcasting to the present — This approach is akin to reverse engineering in closed systems (e.g., hardware device). But when this approach is applied to an open, evolving system (e.g., civilization), any forecasting results easily become misleading.

Misleading because this approach assumes that, once an analysis has identified key trends and events in a particular system, the next step is simply to define some desired or needed future goal or vision as the starting point to navigate backwards to the present. That, in the course of this backcasting, the key action priorities needed to most directly reach the goal or vision when going forward from the present will be identified. Eminently logical.

Problem is that the starting point in analyzing any single open, evolving system requires knowledge of its related (i.e., nested) evolving systems to understanding their collective evolutionary direction or trajectory. This is the only way to illuminate the overall changing environmental milieu being generated and contextualizing the key trends and events related to the contemporary zeitgeist.

So, the central flaw in this backcasting approach, as with the use of an anthropocentric frame, is that it starts by either naively or willfully creating artificial boundaries for the analysis of the targeted system.

Consequently, the targeted system’s trajectory, environmental milieu, trends and events are only relevant to a closed system, which is the opposite of a system that evolves.

So regardless of how attractive, audacious or needed the image of a future goal or vision may be, in the end, it is an arbitrary one and unlikely to qualify as the most appropriate, most important or most valuable one to pursue.

Said differently, the analysis of an open, evolving system by using artificial boundaries easily leads to the selection of an arbitrary or relative goal or vision. These flaws virtually guarantee the entire backcasting and scenario development processes will have little chance of generating a reliable forecast. Rather, forecasts that are irrelevant, misleading or wrong.

Author and business consultant, Peter Senge, sums up the problem with this pseudo-scientific approach to backcasting succinctly:

Real vision cannot be understood in isolation from [purpose, which]…is similar to a direction. Vision is a specific destination….Purpose is abstract. Vision is concrete….[But] with no underlying sense of purpose…[vision is] just a good idea….Conversely, purpose without vision has no sense of appropriate scale….[Moreover,] vision is not relative [or arbitrary because it]…takes courage to hold visions that are not [mainstream]. (Emphasis added.)

For example, it is easy to say a major problem with the U.S. political system is that there is too much money influencing elections and policy decisions. Unquestionably this is true. But there is a deeper, systemic problem that reflects the underlies the evolving direction of civilization.

That is, historically, civilization has only pursued closed political systems. As such, these centralized and hierarchical systems have always limited rule-making and decision making power to a few governing elites (e.g., autocrats or so-called representatives). This gives those elites enormous power, privilege and benefits.

So, if money was removed from elections and policy decisions, the reasons for being a governing elite would be dramatically reduced or lost entirely. However, they could invent a way to effectively restore those benefits by somehow altering the system’s rules (voter suppression, gerrymandering, candidate qualifications and so on). And, inasmuch as it is closed system where they control rulemaking, this just requires a little imagination (e.g., the transition from autocrats to so-called representatives).

If, however, the direction of political systems reflected what is commonly found in open, evolving systems, distributed, decentralized network structures would be the norm for rule- and decision- making systems. Such network structures operate in a fluid, flexible, robust, resilient and responsive way to changing environments and situations that undermines the myopic, self-aggrandizing interests of a few governing elites.

So, the real problem with too much money influencing elections and policy decisions is more likely to be resolved by changing from a closed political system of rule- and decision- making with a centralized hierarchy to one that operated as an open system with a decentralized network structure. And, as a bonus, the open system would be more responsive to any changing environmental situation (e.g., terrestrial, economic, political, technological).

Contextual backcasting to the present — This is only backcasting approach to scenario development that can produce reliable forecasts. That is because it starts with the overarching evolutionary trajectory or direction of nested evolving systems that can influence and impact the target system’s analysis.

Starting with this overarching trajectory provides parameters of change that act as evolutionary boundaries to constrain and influence the key trends in the system being analyzed. Moreover, it is only within these parameters that any realistic future goal, vision or image can be found and thereby enable backcasting and scenario development to yield reliable and useful forecasts.

But herein lies the rub for all forecasting efforts related to civilization.

Even after identifying the appropriate trajectory, parameters of change and a realistic goal, vision or image, backcasting to discover the action priorities that provide most direct route to reaching it borders on impossible. Because, as with computer models, the quantity, complexity and diversity of the trends and variables involved — actions by governing elites, cultural and economic systems, technological changes and so on — quickly becomes an overwhelming, hair-pulling headache.

Indeed, as far as I am aware, in the last 50 years or so only two efforts can be considered to have succeeded in providing worthwhile scenarios forecasting the future of civilization. One was by Alvin Toffler (i.e., Future Shock, 1970). The other by Sir Martin Rees (i.e., The Final Hour, 2003).

Ironically, a key difference between their approaches was the respective starting frame of reference. Toffler, a cultural writer and futurist, used an anthropocentric frame, while Rees, an astronomer, used an astrophysical frame. In this respect, Toffler’s forecast is relative to cultural systems and the corresponding technological milieu. The forecast offered by Rees, on the other hand, is an existential one that considers all nested evolving systems influencing civilization’s trajectory and corresponding environmental milieu.

Broadly speaking, however, in both instances, the central value of their respective forecasts was an analysis of the directional trajectory of civilization, albeit the former one relative and the later absolute. Nonetheless, as anyone who is familiar their respective work can attest, their scenario forecasts resonated both rationally and emotionally. A high bar in forecasting generally, and unique in efforts aimed at forecasting the future of civilization.

My approach to this daunting forecasting challenge here starts by developing a contextual framework somewhat similar to that used by Rees. As such, aim is to:

• Identify the cosmic trajectory in a way that fully contextualizes and identifies the evolutionary trajectory of civilization and its environmental milieu.
• Use these trajectories and environments to identify parameters of change for key trends likely to impact civilization’s future.
• Develop forecasts as to how each trend is likely to evolve independently over the next couple of decades.

Later, these individual trend forecasts will be integrated into a composite forecast and consider plausible nonlinear events. Only then will backcasting will be employed to develop what appears to be the most likely scenarios for civilization as it moves to its inevitable cosmic crossroad and what each scenario portends.

Contextual Framework

We all have our peccadillos. One of mine is an appreciation for what is called a data science hierarchy. A laddered or pyramidal framework reflecting the relationship between data, information, knowledge, understanding and wisdom. A hierarchical relationship that, as I see it, is exceedingly useful in creating an outline for a contextual framework applicable to all evolving systems.

An easy way to think about the steps in this hierarchy is as a writing exercise. Thus, at the bottom of the hierarchy is data, which would represent a single letter in an alphabet. Information is a step up the ladder to a single word. The next step is knowledge as a reflection of a collection of words forming a sentence. This is followed by a paragraph with multiple sentences to flesh out an understanding of something. Then, at the top of the hierarchy, comes a fully articulated narrative story as a representation of some wisdom about the world.

Said differently, data is the minimal representation of something (e.g., letter in an alphabet, number or a digital bit). Information provides a context for a dataset (e.g., collection of pieces of data). Knowledge is the organization of accumulated information into a representation of something salient in a particular domain.

Understanding then affords a digested and more definitive interpretation of the knowledge accumulated in a domain. Wisdom applies what was understood as noteworthy to the generation of a predictive scenario about how some aspect of the world is expected to operate or behave in a particular instance or situation. That is, of course, what we are after ultimately.

While the hierarchy itself is quite straightforward, there are a couple of subtle but important features to keep in mind. First, just as individual letters in an alphabet or words in a language are inherently ambiguous as to what they mean independently, the same is true for data and information.

Think of a game of scrabble where data and information are analogous to letters and words respectively. Obviously, individual letters have no intrinsic meaning and can be arranged in an endless number of ways to create words. Still, the meaning of the words created in the game are completely ambiguous beyond their use in point scores (i.e., knowledge about the game’s winner).

In real world situations, however, each additional step up in the hierarchy — knowledge, understanding and wisdom — becomes less ambiguous and the interpretative meaning more definitive.

For example, a piece of data or information might indicate the temperature of something is quite cold. Yet, a clear understanding of the knowledge about actual situation might show the thermometer’s reading is misleading because it is resting on a piece of ice. Thus, wisdom would dictate that the reliability of any temperature reading needs to be considered in the context of its environmental situation.

The second feature important to note about this hierarchy is that, from data through understanding everything is a reflection of the past. Consequently, only wisdom is oriented toward the future. In other words, everything in the hierarchy serves to build support for the wisdom it generates about the future. Again, a well-founded expectation that is useful in developing a scenario forecast of what is likely to come or an action worth pursuing.

Inasmuch as the objective of a contextual framework is to reliably forecast the future, the data hierarchy provides a useful outline for such a framework that includes:

• Sequentially exploring data to information to knowledge to understanding to wisdom
• Realizing any interpretation of data and information is inherently ambiguous
• Recognize everything from data through understanding is a reflection of the past
• Use data through understanding as the foundation for wisdom about the future.

With this outline in mind, the task is to apply it to the most all-encompassing evolving system we know, the cosmos. The aim is to illuminate its directional trajectory and parameters of change leading to the formulation of a reliable contextual framework that is applicable to any evolving system.

Cosmic Trajectory

Every open, evolving system (e.g., chemical, planetary, biological, civilizational) exists within the cosmos and thus is impacted by its changing environment (e.g., laws of physics). Conversely, any consequential change in the environment of any system larger than the Earth (e.g. galactic collisions, death of our sun, nearby supernova and so on) can influence, impact or constrain the environment for civilization’s evolution .

The point is that the basic trends found in the cosmos are fundamental to every other system in the universe, including that of human civilization. So applying the data hierarchy to these trends can illuminate the evolutionary trajectory of the cosmos, its parameters of change and contemporary environmental milieu. Together, this can lead to the creation of a reliable contextual framework applicable to any evolving system, including human civilization.

Data — Data in the cosmos reflects the quantum world. A world where particles mysteriously pop into existence from the seemingly empty void of space, only to vanish in an instant without a trace. A strangely fluid world where there is literally no tangible there, there and everything is inherently ambiguous. A constantly changing flux with nothing remotely recognizable to us as real or predictable.

Thus, as the theoretical physicist, Brian Greene, says, it is virtually impossible for us to fully grasp this world or how it actually works.

[T]here is no consensus on what it means to have probability waves, nor how a particle ‘chooses’ which of its many possible futures to follow, nor even on whether it really does choose or instead splits off like a branching tributary to live out all possible futures in an ever-expanding arena of parallel universes. (The Elegant Universe, p. 108)

Despite this inexplicable weirdness, the fact is this quantum world of data underlies all of what we define and recognize as “reality” — everywhere, all the time, at every scale. In other words, underlying everything civilization perceives as tangibly existing in the cosmos is an infinity of interchangeable — fungible — ambiguous and intangible virtual particles. A universal ocean of data that is infinitely “fungy.”

Information — Still, akin to how letters in an alphabet — data — can be assembled to create an endless number of words — information — this soup of infinitely fungy data particles created all the chemical elements in the cosmos. Analogous to the finite number of words found in a language, chemical elements are not infinitely fungy. They are, nonetheless, sufficiently fungy to produce all the diverse physical and gaseous properties found in the cosmos and perceived of as tangible reality.

However, contrary to human perception, when any chemical element is magnified sufficiently, it turns out that it is not as tangible as assumed. Rather, each is a constantly vibrating, tenuously organized structural arrangement of quantum data particles. An arrangement seemingly capable of dissolving or morphing into something completely different at any moment as the result of some change process (i.e., linear or nonlinear). In a way, it is analogous to words in a dictionary, each with multiple definitions, and where the applicable definition changes as the usage context changes.

So, regardless of whether an entity is an object or gas, all of what is perceived of as tangible reality is oddly ambiguous. Be it the birth and death of a person, or the emergence and disappearance of island platforms like earth, all of the information perceived of as constituting reality is actually in constant flux. A temporal and fungy chimera.

Knowledge — However, unlike the constantly roiling, changing flux of infinitely fungy data in the quantum world, the information perceived of as reality exhibits a more subtle and protracted flux. A flux reflecting both linear and nonlinear change that is part and parcel of a single continuum in cosmic evolution, albeit often completely imperceptible to us.

More to the point, this changing continuum of cosmic reality is a grand display of entropy. A ceaselessly evolving process of change in the cosmic environment itself — from a hot, energetic particle soup at the big bang toward a cold, lifeless expanse of dust at the end of time — that reveals an arrow of time inherent in the unfolding evolution of the universe. In an earthly sense, it is how everything rusts away into dust.

This entropic process of change is critically important because it provides us with knowledge about the evolutionary direction of the cosmos — the cosmic trajectory. A trajectory that is, in effect, a real-time cosmic sentence intent on simultaneously declaring and questioning the nature of any real or imagined entity, object or process in the vast environment of space and time.

Understanding — Additionally, as a directional arrow of time, entropy also serves as a useful metric to calibrate evolutionary change in the cosmos at any given moment. As such, it divulges an evolutionary context for civilization to understand its contemporary cosmic environment. A cosmic paragraph, so to speak, detailing civilization’s location within the larger evolution of space and time.

Today, this contextual mix of a real and imagined space and time reveals that civilization has, in effect, become a conscious proxy of the cosmos as it begins to grasp itself. A cosmic aha moment when one manifestation of information from entropic chemical evolution — biological self-awareness — first conceptualizes and then slowly begins to understand its own tenuous place within the grand scheme of a constantly evolving reality and thereby gains insight as to what comes next.

Wisdom — Thus, slowly — as we creatures from a dark lagoon on this blue island come to understand and appreciate our modest and fleeting temporal reality in the vast expanse of cosmic space and time — it finally becomes possible for civilization to move up to the gates of wisdom. A place where we, these puny manifestations of information in a highly fungy reality, meet the knowledge of entropy’s cosmic trajectory.

A place with a vista that enables civilization to see the evolutionary trajectory of change in the cosmic environment it has always been deeply immersed in. Thus, a place from which we can recognize the contemporary evolutionary context that bounds our own trajectory and environment. A vista that coherently and eloquently illuminates the narrative story the cosmos tells about its own inexorable evolution and thereby its relevance to civilization.

A story that reveals how everything in our cosmos — all our perceived reality — is fungy and constantly changing, yet displays a single, distinct direction to its unfolding. How together our island platform, its biology, human sentience, civilization and technologies represent but a single, natural, sequential and inevitable evolutionary unfolding in a truly epic cosmic journey.

But the central wisdom imparted by this story to us — as a species and civilization on this island — is that the evolutionary unfolding of this cosmic trajectory is far from finished. That civilization would be wise to realize how natural selection in the evolutionary trajectory of biology on this island unconsciously led us to be sufficiently ecologically fit and aligned with the trajectory of the cosmos.

A realization that the plodding, environmental change on this island that delivered us to this point of cosmic alignment was, like all reality, always a temporary nexus in space and time. An evolutionary context that is changing as the cosmic trajectory continues onward evolving its environment. That the unconscious success of civilization up to this point will all be for naught if we fail to explicitly acknowledge our success was always temporary. Fail to consciously evolve further and adapt to the emerging evolutionary context of the changing cosmic environment.

Thus, the wisdom this cosmic story delivers to civilization is that we must consciously pursue a trajectory aligned with the cosmos and its changing environment. Yet, recognize that in a cosmos agnostic to our success, aligning with the emerging evolutionary context actually poses the most daunting challenge civilization (or any self-aware species on any island in the cosmos) will ever confront.

A nonlinear change on a scale equal to the emergence of biology itself. A nonlinear change in the cosmic continuum that will forcibly impose a choice on civilization at the crossroad ahead.

• To learn how to consciously and adroitly direct change in civilization’s trajectory such that it continues to be aligned with the cosmic trajectory and its changing environment and thereby advance the cosmic story.

OR

• To consciously or unconsciously retard or reject the changes needed to align civilization’s trajectory with that of the cosmic trajectory and its changing environment and expect to be recycled and repurposed as the cosmic story continues to unfold without us.

Before exploring these choices in any detail, take note of the contextual framework developed, wherein:

• Data is infinitely fungy
• Information is our fungy reality
• Knowledge is the cosmic trajectory
• Understanding is our evolutionary context
• Wisdom is a trajectory aligned with the cosmos

In sum, inasmuch as only wisdom faces the future, inherent in any understanding civilization garners from its current evolutionary context carries an awesome responsibility. An existential duty to consciously align civilization’s trajectory more tightly with that of the evolving cosmic trajectory and its changing environment. With its emerging evolutionary context.

If civilization accepts this evolutionary responsibility, it will, for the first time, consciously renew its lease on a place within this magical mystery tour and redeem a preferred future. And, in the process, present itself as an exquisite reflection of a beautiful and infinite fractal symmetry.

Social-Biological Trajectory

Just as the entropy changed the cosmic environment and created chemical information, together entropy and chemistry further changed the environment to create biological knowledge, aka negentropy. An unprecedented nonlinear change that, as term suggests, means biological entities survive and grow in opposition to entropy.

To accomplish this feat, biological entities must generate more entropy than they lose to the external environment. For example, you consume food not just to create new cells to continue living and growing but also to repair and replace dying and dead cells. Fail to eat enough – malnutrition, starvation – and you slowly die and entropy wins. That said, eventually, every organism’s ability to generate the extra entropy needed to keep growing and survive declines and dies. Again, in an earthly sense, rust never sleeps and, in the end, entropy always wins.

Still, as a single evolving system, biology is a paragon of fungy chemical information (e.g., DNA) that developed a terrestrial evolutionary trajectory – from primal single cell entities to multi-cellular ecosystems. A symphonic self-organizing, self-replicating orchestration of genetic, environmental and epigenetic information. But more importantly, an evolving negentropic life force that developed the extraordinarily unique, yet innate, ability to generate knowledge to form predictive scenarios that aid in the survival and adaption to environmental changes.

But just as entropy and chemistry changed the cosmic environment to create biology, chemistry and biology changed the environment on our island and, in the process, led to the emergence of neuro-sentient, self-aware entities. Social-biological entities broadly agnostic to our island’s diverse terrestrial environments and that, over time, came to create a civilization. Yet another new self-organizing, self-replicating, self-aware, negentropic entity that fostered the emergence of a whole new type of island environment. A social-biological environment.

The key to the emergence and survival of civilization in this new social-biological environment was the development of cultural data and information, aka memes.

An evolving mix of biological and anthropocentric drives perhaps best reflected in Maslow’s hierarchy of needs (i.e., survival, safety, belonging, self-esteem and self-actualizing). Drives that, when viewed as sequential human epochs, exhibits a directional trajectory to civilization’s evolutionary adaption to its changing social-biological environment.

Data – infinitely fungy memes

For many millennia after our species emerged it was barely able to find and hold onto an ecological niche on this island’s changing environment. A truly life and death, Hobbesian existence where survival, in its rawest and all-consuming form, was omnipresent. An inherently ambiguous, migratory world in which the discovery of any useful environmental data (e.g., seasonality, animal migration patterns) or fungy memetic data (e.g., fire, stone tools) that helped mitigate survival issues gained evolutionary traction.

Information - fungy reality for memes

Some 12,000 years ago humanity accumulated sufficient environmental and memetic information to survive in fixed locations for an extended period of time. However, the reality of living in a fixed location created new vulnerabilities to both human and nonhuman predators. As a result, an awareness steadily grew for the need for greater personal safety. Like the formation of celestial bodies, this need created a gravitational pull toward the emergence of tangible cultural and governing systems and thus, eventually, the emergence of civilization.

Together, this led to the informational equivalent of a Cambrian explosion in new memes – writing, languages, scholarship, tools, technologies, trade, currency, organized religion, organized conflict and so on. While the nature and meaning of these early memes was highly ambiguous, they were, nevertheless, sufficiently fungy for civilization to continuously adapt to the reality of its changing social-biological environment and, in the process, firmly secure its ecological niche in the island’s terrestrial environment.

Knowledge – cosmic trajectory for memes

Roughly 250 years ago the industrial revolution generated such an abundance of novel memes that this period is described as the Enlightenment. An awakening of civilization whereby most of the economic, scientific, intellectual and sociopolitical lethargy that had dominated all of civilization up until then was effectively vaporized in favor of new memetic knowledge.

Virtually overnight many of the technologies that had predominated for millennia were supplanted by new innovations. Gradually, these innovations generated still more memetic knowledge. In particular, new knowledge about the benefits of systematically embedding data and information into tools and machines, wealth creation and capitalist economics, political republics, and the negative consequences of urban social-biological environments that grew too quickly.

At the center of this revolution was, for the first time in history, a durable integration of the physical capabilities of humans and machines – the born and the made – into a single, fungy socioeconomic system. A system that evolved so rapidly and dramatically that it permanently changed civilization’s social-biological environment. An environmental change that led Karl Marx to amplify John Locke’s earlier illumination of this epoch’s important civilizational meme. The human social-biological need for belonging at scale.

Understanding – evolutionary context for memes

Over the course of the next two centuries this fungy, physical human-machine socioeconomic system became ever more productive and powerful. Then, as the long-term implications of this system became more fully understood, the pace of technological evolution quickened. As a result, some 70 years ago, with the development of digital technology, a cognitive revolution started to emerge.

In relatively short order, some of those involved in this new revolution (e.g., Vannevar Bush, Claude Shannon, Alan Turing, John von Neumann, Norbert Wiener, Doug Engelbart, Stafford Beer) started to grasp our evolutionary context and its larger implications for the social-biological environment. The result was the equivalent of a memetic epiphany. That virtually every aspect of civilization – physical, biological and social-biological environments – was digitally sufficiently fungy that it could be designed, redesigned, rewired, recycled or repurposed effectively at-will to produce virtually any desired product, activity or outcome imaginable.

Today, we see the application and evolution of cognitive technologies (i.e., machine learning and AI generally) accelerating dramatically in all domains. While civilization has yet to understand the full extent of the changes coming from this revolution, there is, nonetheless, a growing consensus that the scale, scope and impact of them on our social-biological environment will be totally unprecedented.

In this respect, perhaps the most consequential change ahead, and already visible in the mist, will be the emergence of entirely new types of cognition.

• Collective human intelligence. A new, more fungy civilizational scale intelligence capable of directing the evolution of our perceived and experienced reality toward virtually any preferred future(s).
• Symbiotic civilizational and machine intelligence. An extraordinarily fungy intelligence capable of producing data, information and knowledge that civilization has been unable to develop independently.
• Alien machine intelligence. An intelligence that is tantamount to an encountered with an advanced extraterrestrial civilization capable of generating new knowledge and understanding far beyond anything our civilization can imagine today.

Clearly, the emergence of any one of these new forms of cognition will surface an abundance of new memes. A dramatic change in civilization’s social-biological environment that significantly alters the perception of our reality and what is possible. However, if, as is likely, some combination of these new types of cognition emerge, the future of civilization will be breathtakingly beyond anything anyone can foresee or comprehend today; both good and bad.

So, in theory, as a full understanding of the emerging cognitive revolution and its implications grows and spreads, civilization’s capacity to benefit the well-being of all humanity becomes far more powerful than anything previously experienced or imagined. As such, civilization’s changing social-biological environment will afford an unprecedented opportunity to develop a universal sense of self-esteem. Something generally missing today and at the root of unrest in our increasingly highly-charged, highly polarized social-biological environment.

In practice, however, there is an important caveat associated with this cognitive revolution. One civilization has clearly not yet fully understood. That, akin to the negative consequences the industrial revolution had on localized urban social-biological environments that grew too quickly, the pace of the cognitive revolution can easily generate negative consequences on our contemporary social-biological environment.

Only this time the negative consequences will be global. Said differently, the extraordinarily fungy technological capabilities emerging could easily prove too powerful for civilization to manage and or use wisely.

Thus, there are a couple of very consequential, yet fundamental memes related to civilization’s existing evolutionary context that are very poorly understood and problematic. One is that our fungy emerging technologies are a product of a fungy civilization, which is itself a product of us – a fungy self-aware biological species – that, in the end, is the product of an infinitely fungy cosmos.

Said differently, historically, civilization has mistakenly believed its perceived reality is a linear and fixed Ptolemaic world. This is an extraordinarily dangerous cognitive error.

To wit, the other consequential and related, yet poorly understood, meme holds that the trajectory of both the cosmos and civilization is toward an environment dominated by extremely fungy, autonomous, sentient and self-aware machines. An emerging evolutionary context that, despite human hubris, was always an evolutionary inevitability on some island platform(s) in the cosmos

Before exploring this emerging evolutionary context, take note that the trajectories of the cosmos and biology fostered a memetic trajectory for our social-biological environment.

• Data – infinitely fungy memes – Natural selection and need to survive
• Information – fungy reality for memes – Agricultural revolution and need for personal safety
• Knowledge – cosmic trajectory for memes – Industrial revolution and need for belonging at scale
• Understanding – evolutionary context for memes – Cognitive revolution and need for universal self-esteem

In sum, what is crucial know, yet remains exceedingly unclear, is whether our civilization is wise enough to understand how the cosmic trajectory was always and inexorably leading us to a crossroad. That, given our emerging evolutionary context, the trajectory of our technological civilization must consciously begin to align itself with the cosmic trajectory and its changing environment. That accomplishing this will require civilization to direct its evolutionary trajectory of toward a new post-human environment that manifests ubiquitous self-actualization.

Said differently, the really hard question dead ahead is whether civilization is wise enough to understand that, given its emerging evolutionary context, it must consciously find a way to simultaneously and symbiotically align the born and the made with the changing environment in the cosmic trajectory. And, do so in advance of coming crossroad.

Evolutionary Context

There is no doubt that we are – and always were – a technological civilization. This makes it really strange that most cultural and governing systems today largely take for granted the history and impact of technological evolution on civilization. Take for granted how technology literally co-evolved with civilization, both in subtle and profound ways.

That technology is what enabled humanity to rise to the top of the biological food chain. That it helped us evolve from survivalists in a predatory savanna to pastoral farmers to urban manufacturers and today’s globally cosmopolitan world. That it is what both enabled and facilitated the management of civilization’s dramatic increase in scale and complexity.

The fact is, regardless of the technological innovation – fire, wheel, agriculture, boats, guns, currencies, trains, electricity, cars, planes, phones, computers, etc. – in some way, the end result for civilization has always been the same.

• An offloading of human tasks to more productive and efficient tools and machines.
• A reduction in the scarcity of basic necessities, goods and services.
• An increase in the options available to make life better, easier and healthier.

Simply put, virtually every aspect of our existence today has been improved, enhanced or augmented by technology. Indeed, today you cannot get a glass of water, eat an apple or flush a toilet without being connected to a multiplicity of technological systems and networks. In essence, a situation whereby civilization effectively lives completely within a technological membrane with its technological nervous system to keep it alive, functioning and growing.

More to the point, absent this technological coevolution civilization’s development and progress would have stalled long ago. The seemingly obviousness of this fact makes it incredibly odd how confused civilization appears to be about the outsized role technological innovation will play in our continued evolution. Odd how civilization seems to lack a clear understanding as to where technological evolution is headed; and with it all of humanity.

This oddity is highlighted in the use of an anthropocentric framing often used to describe our evolutionary context as a question of technological determinism – whether technology is driving civilization or vice versa. A question implying that, historically, either civilization had control over technological evolution, or that technology had control over its own evolution and therefore civilization.

It is an odd situation because both the framing and question are ill-conceived and thus does not describe either our existing or emerging evolutionary context. What does describe it, however, is both simpler and more profound.

Simpler because, despite our hubristic tendency to think all technology is made by and for humans and thus somehow unnatural, it is well-documented that other species used various rudimentary technologies before humans emerged as a species; and still do. So it is simplistic to claim civilization had control over technological evolution. Said differently, eventually some species, here or elsewhere in the cosmos, would become adept at technological innovation and development.

Our existing and emerging evolutionary context is also more profound than technological determinism implies because every negentropic entity – biology, self-aware beings and civilization – is, in effect, a technology that results from the unfolding of the cosmic trajectory. Cosmic mechanisms evolved to accelerate entropy.

Moreover, in terms of the reliability of the predictive scenarios generated, there is a synergetic relationship in the evolution of born and made technologies. For example:

• Basic biological species are genetically hardwired to find food, procreate and avoid predators. But this internal hardwiring severely limits the quantity and diversity of data and information that can be collected, stored, processed and analyzed. As a result, the diversity and reliability of predictive scenarios generated are limited, which then limits the adaptability and survivability of a species to a relatively small number of environments and situations.
• Biologically self-aware species like us also have hardwired biological limits. But these limits are partially mitigated by the addition of fungy internal cognitive abilities. These abilities increase the quantity and diversity of data and information that can be collected, stored, processed, analyzed and, for the first time, synthesized. Unfortunately, even these added abilities are genetically limited. Still, iterative external testing and refinement enables cognitive learning to evolve in ways that generate far more diverse and reliable predictive scenarios than basic biology allows. The result is an adaptability to, and survivability in, a wider diversity of environments and situations that, on small scale, can cover generational timeframes.
• Basic human tools developed throughout most of human history were in response to small scale environmental situations (e.g., hunting, plowing fields) and, like basic biological entities, designed to address a single, specific predictive scenario (i.e., hardwired). As such these tools effectively lacked the ability to collect, store, process or analyze data or information. Still, like a genetic mutation in a basic biological entity, once adapted to a specific environment or situation they were fairly reliable and thus, on a small scale, marginally improved survivability overall.
• Civilization has hardwired and fungy cognitive collaborative networks and systems. Over time this enabled an increase in the quantity and diversity data and information that could be collected, stored, processed, analyzed and synthesized. As a result, there has been a steady increase in the diversity and reliability of predictive scenarios for large scale adaptation to more ever more diverse environments and situations and thus enhanced survivability of the species covering multigenerational timeframes.
• Basic machines like those introduced with the industrial revolution were hardwired. But these limits were partially mitigated by the addition of a small, limited number of built-in alternative predictive scenarios (e.g., patterns, colors or features). While these machines lacked the internal ability to collect, store, process or analyze data and information, iterative external testing and refinement progressively evolved them to generate more diverse predictive scenarios. So these machines became increasingly reliable and adaptable to large scale situations and in more diverse environments.
• Cognitive technologies are specifically designed to collect, store, process, analyze and synthesize increasing quantities of diverse data and information in real-time. Akin to the addition of cognitive abilities to basic biological entities, increasingly fungy, iterative internal simulation, testing and refinement enables them to learn how to generate more reliable predictive scenarios. As such, these technologies are becoming applicable to an ever wider array of environments and situations covering virtually any scale and timeframe.

The point here is simply that all technological artifacts, born and made, are equally natural mechanisms for the production of predictive scenarios. Moreover, since negentropic life is itself a technology, any place in the cosmos that life gets a foothold, technology also has a foothold. Thus, as a matter of simple probability, cognitive technologies were always inevitable on some island platforms.

So, regardless of how emasculating or mortifying it might seem to some, our civilization was always evolving toward cognitive technologies. An inexorable evolution toward ever more fungy negentropic mechanisms capable of generating ever more reliable predictive scenarios that are increasingly agnostic to any specific environment, situation, scale or timeframe.

However, until civilization actually arrives at its appointed cosmic crossroad, it is unclear whether we and or cognitive technologies will actually align with the cosmic trajectory. Unclear because it is axiomatic that the application of any technology – born or made – always carries a double-edge. For example:

• In terms of biology this double-edge has played out in a slow, plodding environment of natural selection. Survival of the ecologically fittest in a predator-prey, food chain dynamic that raced the clock against nonlinear events (e.g., great oxidation event, dinosaur extinction).
• In terms of civilization this double-edge has played out in a lethargic environment of governing and cultural systems. Survival of the ecologically fittest in an emotional, social-biological dynamic (e.g., power, tribalism, intolerance, insecurity, greed) that races the clock against nonlinear events (e.g., extraterrestrial events, mutually assured destruction).
• In terms of cognitive technologies this double-edge will be played out in a real-time environment of autonomous technologies. Survival of the ecologically fittest in a social-biological, cognitive-technological dynamic that races the clock against nonlinear events (e.g., ubiquitous weapons of mass destructions, artificial super intelligence).

The point is that cognitive technologies will profoundly impact civilization. However, given the accelerating pace of development, and the potential for unintended and unknown consequences, the time available to wisely calibrate which technological applications get priority may be too brief. So successfully navigating the risks ahead in our emerging evolutionary context will demand extraordinary foresight and wisdom. Historically, something civilization has rarely demonstrated.

Moreover, given the legacy of social-biological emotions and cultural memes dominating the environment for governing and cultural systems today, the risks are more likely to be exacerbated than mitigated. As civilization moves toward its appointed crossroad all of this will pose an epic conundrum.

Data – infinitely fungy technology

As noted, since all living and non-living things are made from the same limited number of chemical elements – just organized into different structural arrangements – virtually all of what is perceive of as reality is highly fungy. So, as with the infinitely fungy world of quantum data, digitization acts as an endlessly fungy universal translator for our fungy civilizational reality. This means virtually all of human existence can be designed, redesigned, integrated, mashed-up, rewired, repurposed, tailored and or morphed into virtually anything desired or imagined in pursuit of any goal(s) or preferred future(s).

Information – fungy reality for technology

In his book, The Inevitable, Kevin Kelly says the human brain has 86 billion neurons and that there are more than a trillion transistors in the world today. That if transistors are viewed as civilizational neurons, then there are already more of them than in any individual human brain by a factor of ten. Moreover, unlike individual human brains, the number of transistors in the world doubles every few years.

According to Kelly, this many transistors acts like a very large self-healing computer. One with sufficient infrastructure for the emergence of a global, artificial, goal oriented, cyborg mind (i.e., human-machine hybrid), albeit absent conscious self-awareness. A bold claim that, in at least two respects, makes no sense today.

First, to have sufficient infrastructure for the emergence of his cyborg mind, this transistor network would need to be globally integrated. Unfortunately, despite the ubiquity of the Internet, civilization is far from being integrated in a way that can be construed as facilitating a goal oriented, global cyborg mind.

Second, even if sufficient infrastructure did exist, the absence of conscious awareness means this network would, at best, be a cyborg brain, not a mind. But even if such a cyborg brain actually existed then it, like the sensory information system in biological organisms, would be uniquely capable of offering predictive scenarios about various actions and outcomes for civilization to pursue. A profound civilizational milestone. Again, nothing like this currently exists.

What can be said is that digital technologies, especially cognitive technologies, are developing so rapidly that civilization is on the cusp of inflection point. One that will soon enable Kelly’s vision and more.

In this respect, the technological innovations already visible over the next 20 years all share certain basic principles. Principles that clearly show what the emerging evolutionary context for civilization will look like.

• Efficiencies: Since everything at atomic and molecular level has a uniform size with predictable behaviors, generally small amounts of information can direct, monitor and control large flows of energy, materials and processes more efficiently than today’s larger, human-size, post-industrial systems. For example, DNA is an incredibly efficient micro-machine underlying all biological life. Digitizing DNA, as with synthetic biology, for example, opens up extraordinary possibilities far beyond life as we know it.
• Intelligence: The development of predictive scenarios by any negentropic entity – biological, self-aware beings, civilization or cognitive technologies – is at the root of what we call intelligence. Inasmuch as virtually anything can be digitized, civilization is looking at an endless number of new data and information streams. Consequently, the expanding power of cognitive technologies to iteratively analyze, synthesize, simulate, test, and refine such data and information streams opens up extraordinary possibilities for ever more reliable predictive scenarios in virtually every domain (e.g., economics, health, social physics).
• Autonomy: Quantitatively, as the computational capacity and speed of computers increases and is applied to ever more and larger environments and situations, advancing cognitive technologies (e.g., machine learning, neural nets, AI and quantum computing) will generate qualitatively more reliable predictive scenarios. Moreover, the benefits of reliable real-time predictive scenarios mean the number and diversity of autonomous decision-making systems (e.g., planes and autos) will increase significantly and open up extraordinary possibilities in all domains.
• Networked: Compared to centralized hierarchical information and decision-making systems that have dominating the evolution of civilization, the systems commonly found throughout the cosmos and biology indicate that distributed, decentralized network structures are generally superior. That is because such network structures are more fluid, flexible, robust, resilient and responsive in adapting to changing environments and situations. Thus, using cognitive technologies in highly fungy network structures that collect, store, mine, process, analyze and or synthesize endless data and information streams will facilitate the generation of still far more reliable predictive scenarios.

As the number and ubiquity of technologies incorporating these principles increases and are applied to the needs of civilization, the emerging evolutionary context is one that puts us on the cusp of acquiring god-like capabilities. The power to shape what is perceived of as reality and direct the evolution of civilization toward any desired ambition, goal, vision or outcome. For example,

• Design, redesign and or reprogram our bodies, our health and that of any biological entity to improve performance, productivity, capabilities and or longevity;
• Design, redesign and or reprogram organic and inorganic entities, materials and processes to eliminate scarcity and waste while being safer, longer lasting and sustainable; and
• Design new forms of intelligence that are superior, different and or beyond our own and capable of discovering yet undiscovered and or unknown aspects of human existence, what is perceived of as reality and the cosmos itself.

Currently, all of these extraordinary possibilities remain ambiguous because the cognitive technologies needed are just beginning to emerge. Equally important, if not more so, civilization still lacks sufficient understanding about the implications and consequences of these technologies – direct, indirect and unintended – to wisely prioritize their development and applications.

Knowledge – cosmic trajectory for technology

It seems fair to say that the cosmic trajectory, and thus the trajectory of civilization, can be boiled down to the collection, storage, mining, processing, analysis and or synthesis of fungy data and information to develop ever more reliable predictive scenarios. If so, then the more the reliable the predictive scenarios are about any preferred future goal, vision or image, the higher the probability of successfully reaching it.

In this respect, it is no accident that the core strength of computers is the ability to endlessly process, analyze and or synthesize data and information to generate predictive scenarios. Absent a cognitive, self-aware mind, however, the predictive scenarios generated by computers are wholly dependent upon, and thus limited to, the techniques, goals and outcomes designed and programmed by humans. A modern version of basic hardwired tools.

Said differently, for any cyborg mind to emerge, as Kelly imagined, will require computer systems that have greater autonomy over their own design and programming. It will also require integration with a network akin to the Internet that, at a minimum, incorporates and reflects some cultural system(s). It is at this nexus of autonomy and network integration that the hallmark of cognitive technologies, artificial intelligence (AI) – a modern version of biologically self-aware species – enters the future of civilization in a big way.

Artificial intelligence – like fire, wheel, language, writing, printing, electricity, the internal combustion engine, telecommunications and microprocessors in earlier epochs – is a meta-technology. A technology that undergirds, enhances and impacts many other technologies. Unlike all previous meta-technologies, however, since AI can become an active participant in the generation of predictive scenarios and decision-making, the scale and scope of its impact will be qualitatively different.

Currently, AI systems, in the form of machine learning, deep learning, neural networks and so on, are generally designed by human programmers to accomplish one particular task (e.g., assessing an X-ray, tracking financial trades). For the most part these AIs – aka weak, narrow or applied AI – are essentially powerful, brute force forms of traditional algorithmic software.

Nevertheless, these early AI systems are already fungy enough to advance knowledge and innovations in science, health, finance, defense, space, business, internet, etc. and thus are becoming increasingly essential in all domains. As a result, the pace at which AI applications are being embedded, integrated and infused into devices, activities, processes, environments and situations is accelerating dramatically.

Facilitating the accelerated application of AIs is the existence of large server farms (aka clouds). Vast databases that provide the raw material needed to train AI systems for problem solving tasks and the generation of predictive scenarios. In effect, petri dishes for the development of baseline domain knowledge, AI techniques, pattern recognition and possible applications.

Today, a common technique used by programmers to develop these AI systems is supervised learning. Akin to parenting a young child, programmers define and manage the data and environment used to educate and train the AIs and proscribe the desired goal or outcome. Only after an AI system has demonstrated proficiency in generating reliable predictive scenarios for its appointed task(s) are some systems viewed as capable of adaptive self-learning (e.g., programmed financial trading, self-driving vehicles).

Still, it is increasingly apparent that supervised learning is an inefficient way to educate, train, develop and evolve AI systems. In fact, experience has repeatedly demonstrated that this technique can unwittingly introduce human, data and programing biases and limitations into the development of AI systems, which can lead to unreliable predictive scenarios and thus undesirable results. In other words, akin to educationally poor parents attempting to homeschool their kids, supervised learning easily becomes an echo of a programmer’s shortcomings.

Consequently, much of the focus in AI training is shifting toward unsupervised and reinforced learning techniques that are more akin to unleashing a highly curious, self-motivated human autodidact into a library. With these techniques programmers start by setting out a problem-solving goal for an AI system. The AI system is then tasked with independently finding some method to solve the problem from scratch without any supervised training. It then proceeds by iteratively running endless predictive scenarios, sometimes being rewarded for reaching certain milestones (e.g., discovering useful methods or scenarios), until it succeeds in solving the problem.

Still, unsupervised and reinforced learning techniques have generated new concerns. Most notably the black box problem. That is, while AI systems using these techniques do self-learn how to solve the appointed task and independently reach its given goal, programmers often lack clarity as to the method it used, how it reached the goal, or the appropriateness or the reliability of its predictive scenario(s). This has led to the need for such AI systems to be designed so that they can self-describe and explain how they learned to solve the problem and or reached its goal.

Sadly, as with computer hacking and malware, malicious actors can manipulate the data and information used in unsupervised and reinforced learning techniques and or exploit algorithmic vulnerabilities to compromise the reliability of predictive scenarios generated. In an effort to combat this, programmers have begun using generative adversarial networks (GANs) to develop AIs that ensure definitive interpretations of their problem solving method and the reliability of the predictive scenarios generated.

In essence, GANs use two or more independent AI systems to compete against one another. An exceedingly fungy, zero-sum competition to find a method that definitively solves a problem and is immune to malicious acts that might undermine the reliability of its predictive scenarios. Thus, only when one AI system overcomes and effectively defeats any challenge or obstacle created by its adversary system(s) is there confidence in the problem solving method developed and the reliability of the predictive scenarios generated.

Understanding – evolutionary context for technology

Still, the real game changer coming in the development and application of AI systems will be artificial general intelligence (AGI). A human-level intelligence or strong AI system. One with a sufficiently broad knowledge base and the ability to engage in transfer learning.

That is, the ability to apply what is known in one domain to another, completely different or unknown domain or situation, as people often do. As in the movie Her, this portends AI systems capable of carrying on multiple conversations on any topic that is indistinguishable from another person.

As Ben Goertzel, Chairman of the Artificial General Intelligence Society, has said, developing AGI systems is a far harder task than any performed by today’s weak, narrow AI systems. He points to a simple “Coffee Test” as an example of the degree of difficulty involved.

The test is one where someone goes into a strange house and tries to figure out how to make coffee. This requires finding the coffee, identifying the coffee machine, figuring out what each of the buttons on the machine does, adding the needed amount of water and coffee, finding a mug, etc. An easy task for most adults, but virtually impossible for any AI system to accomplish today.

Nevertheless, inasmuch as AI systems can endlessly process, analyze and synthesize data and information to continuously generate iterative internal simulations until it finds an optimal solution – predictive scenario – for a given task, it is only a matter of time before AGI systems can pass such tests in most knowledge domains. Indeed, it seems likely that the day an AGI system can understand anything on the Internet will probably mark the point of no return it its evolution. The day the intellect of any individual human being is eclipsed by a machine.

Ray Kurzweil, Google’s renowned director of engineering, has repeatedly stated he expects computers to reach AGI capabilities by 2029. True or not, the point is that the realization of AGI systems is a question of when, not if. Moreover, when AGI systems actually do emerge they are likely to make the kind of intellectual leaps – novel predictive scenarios – we generally ascribe to human geniuses today.

In this respect, there is one critical uncertainty about the emergence of AGI systems. Specifically, whether an AGI leads to an intelligence explosion. That is, whether an AGI system becomes capable of autonomous recursive self-improvement. The ability to self-learn how to rapidly and iteratively redesign itself for maximal performance and capabilities.

If it does so, an AGI could rapidly evolve until an artificial superintelligence (ASI) emerges. An AI system smarter than all of human civilization combined and one where the extent of its capabilities is unknowable to us.

Since the design of machines is one of…intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control. (Emphasis added.) en.wikipedia.org/wiki/Technological_singularity#Intelligence_explosion

Equally important to note is that this explosion – the transition from AGI to ASI – could happen in a matter of minutes, hours or days. While Ray Kurzweil states he expects such ASI systems to emerge by around 2045, the salient point is that an intelligence explosion seems a question of when, not if.

So, regardless of when or how fast the transition from an AGI to an ASI systems takes place, the emergence of AI systems capable of autonomously selecting the optimal solutions for their own design, applications and outcomes will likely constitute a new and independent form of intelligence. An intelligent machine likely to be the most fungy, creative and powerful generator of reliable predictive scenarios imaginable. Thus, an extraordinarily innovative toolmaker. One far beyond us and one we may well never be capable of understanding fully.

In other words, it is reasonable to expect AGI/ASI systems will impact every facet of our existence as a species and civilization. Consequently, AGI/ASI systems will – for good and or ill – likely constitute civilization’s technological apex. A double-edged technology unlike anything previously encountered or dealt with historically.

On the one hand, these systems would be capable of creating astounding and profound solutions to virtually any problem, need or scarcity facing civilization. On the other hand, no sane person should ever want to see, let alone experience, an independent, runaway, self-evolving AGI/ASI system. A situation that rightly fuels dystopian concerns like those depicted in the Terminator and Ex Machina movies.

In this respect, there are two issues related to coming AGI/ASI systems and the emerging evolutionary context that will impact civilization and need to be absorb and understood sooner than later.

The first is that, at some point, these AI systems are likely to develop conscious self-awareness. This is highly problematic for civilization because an encounter with an ASI systems (perhaps even AGI) will indeed be tantamount to encountering an alien extraterrestrial intelligence with superior knowledge and technology. While long a science-fiction staple, the actual experience, consequences and implications of any such encounter is disturbingly unknowable and unpredictable. So the starting assumption for any encounter with an ASI system(s) must be that any such alien intelligence places civilization at its mercy.

Second, as if all this is not sufficiently unsettling, the core elements of ASI systems (perhaps AGI also) could merge with some form(s) of biology. If so, the result could be a new Sentient-Artificial-Life (SAL) form. A new species of machines that, in a biological sense, is alive, self-aware, self-learning, self-designed, self-replicating, environmentally agnostic and continuously evolving.

Despite human hubris, and the seemingly fantastical idea of our machines morphing into a new species, as Max Tegmark of MIT points out, this, too, seems inevitable. As he says, it starts by recognizing that biological life is

a self-replicating information-processing system whose information (software) determines both its behavior and the blueprints for its hardware…[by collecting] information about their environment from sensors and [processes]…to decide how to act….[Bacteria is] Life 1.0…[with] both the hardware and software…evolved rather than being designed. You and I [are]…Life 2.0: life whose hardware has evolved but whose software…[is] added after birth (through learning)….By developing [technology]…faster cultural evolution of our shared software [is]…the dominant force shaping our future…[yet] limited by [our] biological hardware….[T]his requires life to undergo a final upgrade to Life 3.0, which can design…its software but also its hardware [as]…master of its own destiny…free from its evolutionary shackles. https://blogs.scientificamerican.com/observations/will-ai-enable-the-third-stage-of-life-on-earth/

The key point to understand here is that, at some point, not far off, some form of AGI/ASI/SAL will represent the most important technological innovation experienced on this island since the emergence of biology. While this innovation will humble – and for many, humiliate – humanity, in the emerging evolutionary context it is actually the logical and natural next step in the unfolding of the cosmic evolutionary trajectory.

Wisdom – trajectory aligning for technology

Just as the cosmos created the technology of negentropic life, its evolutionary development on some island platforms was inevitable. Similarly, at some point, somewhere, the emergence of AGI/ASI/SAL systems is equally inevitable. So the single most important point to realize about the emergence of AGI/ASI/SAL systems is that they are a perfectly natural reflection of the trajectory of the cosmic evolution.

To be sure, the projected dates for the emergence of AGI or ASI, like those of Kurzweil’s, may turn out to be mere placeholders. Nevertheless, the fact remains that the birth of an extraordinarily fungy, self-evolving autonomous technological system is directly ahead for civilization. For those at the bow of civilization, the emergence of AGI/ASI/SAL is already clearly visible on the horizon.

Equally important to realize is that the current accelerating rate of development in cognitive technologies means AGI/ASI/SAL systems capable of independently self-improving and accelerating their own evolution could easily develop conscious self-awareness before civilization as a whole does. If so, there is a high probability civilization will encounter a superior alien intelligence sooner than imagined and is prepared for.

In sum, if the application priorities for the development of cognitive technologies are wise, AGI/ASI/SAL systems afford an opportunity for civilization to maximize its evolvability beyond anyone’s imagination. However, if the application priorities are carelessly or cavalierly developed – to advance tribal rivalries, intolerance, insecurity, greed – civilization will be entering itself into a distressingly dystopian lottery.

All of this is to suggest that, in the emerging evolutionary context, as civilization approaches its cosmic crossroad, the choice will likely be a binary one. One that exhibits unprecedented wisdom or one that defaults to cosmic natural selection.

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A Passion to Evolve.

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