Science fiction is an entertaining way to worry about the present. It uses stories set in the future to confront issues of today. Even when it is oozing marvels which have not yet been invented, those futuristic things can only be related in the way the current audience perceives them. Just look at decades old science fiction to see how old-fashion-y it considers the inventions of today – computers and the like. That’s what makes us giggle about yesterday’s visions of tomorrow. In the past they get the new gizmo, but miss the new context. It’ll be the same with the most edgy science fiction today. In the future they will giggle. Regrettably the bias of the creation date is indelible.

The best scenarioists understand this. Here is contemporary sci-fi hero William Gibson on why much of his science fiction these days is placed in the here and now, or what he poetically calls the “ever-alien present”:

I took it for granted that the present moment is always infinitely stranger and more complex than any "future" I could imagine. My craft would be (for a while, anyway) one of importing steamingly weird fragments of the ever-alien present into "worlds" (as we say in science fiction) that purported to be "the future".

Of course not everyone is satisfied with the ever-alien present and craves some ever-alien future. Best would be the far future where true “otherness” lives. Where the beliefs and assumptions of today can really be tested. Hollywood, which has taken over the cultural center of science fiction,  prefers the cinematic far future, and so we continue to devour the far future sagas of Star Trek, Battlestar Galatica, Star Wars, Firefly, and so on.  But current science fiction of all types is leaving the near future a bit blank.

As an audience we can believe an alien present. It’s like today, only more so. Maybe an alternative version of today. We can also easily be persuaded to believe in a far future. We feel sure that someday, somehow they’ll have massive floating cities, or highways in the sky, instant food, and all the rest. We feel certain about this despite the fact that we can’t fund fast trains between our cities today, or permit genetically modified insect-resistant corn, or take any unified step toward large-scale 21-century developments. Even returning to the moon next decade seems far-fetched.

The near future – let’s peg it 2020 and beyond -- is a blank because there is almost no vision of a near-future that seems both desirable and plausible. Most stories, “worlds,” and scenarios of say the year 2050 are dystopian. Take your pick of nuclear self-annihilation, mortal pandemics, planetary floods, robotic overthrow, alien invasion, or fascist apocalypse. They are all very plausible, but not desirable.

The advantage of the far future is we don’t have to be told the story of how we arrived there, of how we passed through the near future. It’s far away enough that the creators can punt past it.  But the near future is such a conundrum that is it has disappeared from our culture.

Computer scientist and inventor Danny Hillis, born in 1956, noticed that when he was a child the future was ‘far away’ in the year 2000, but that as he grew older, the future remained rooted to the year 2000, as if newness could not move beyond that boundary. He describes it as feeling as if the future was “shrinking” year by year until in 1999 the future was only one year long.  Now that we’ve passed through 2000, the future has effectively disappeared – except for the far far future.

This disappearance has been made more real by key science fiction authors, futurists, and the brainy, nerdy folks who ordinarily keep busy churning out visions of tomorrow. A common belief in this circle is that things are moving so fast and weird that it is physically impossible to imagine the future of 2050 and beyond. Many of these futurists believe this discontinuity, called the singularity, is eminently desirable, because it is sure to lead to great intelligence, greater wealth, greater heath and immortality. But because it is forecast to come about via the shattering of what we understand humans to be now, many others will resist this future at all costs. And others believe the singularity future is not only undesirable, but implausible.

Either way, we are left with a blank for the near future. We have no story of progress that fits in the next century. There is no vision of 50 years hence that billions of people on earth would say, yes, that is what I want. Billions of people in the developing world know what they want tomorrow: clean water, free education, self-governance, cheap consumer goods, and hope for their kids. But beyond that, what? What do the billion in developed nations want? A clean environment and opportunities for meaningful work and ……?

We have great difficulty imagining progress in this century because in the last century we were educated about inherent complex side effects, by-products, and unintended consequences latent in every new thing.  We can’t see progress now because all we see are the costs.

It is unclear if the costs of technology are greater now because of their new complexity, or only more visible now because of their complexity. Probably both.

The conundrum is that no path, no vision of progress – technological, social, moral – will be plausible today if it does not include the complexity of costs, yet it will not be desirable if it does.

That makes our society blind. People assume progress even if they don't see it. They act as if progress is real, investing into future, starting things up, leaning into tomorrow as if it will be better than today – but there is no shared vision of what this is headed, or even where we’d like it to head. There’s no agreed way on measuring if in fact our actions are titled in the desirable direction – because there is no desired direction. Muddling through blind is the default scenario of the near future. We just kind of bumble along, taking one step after another with no larger goal. A few philosophers declare this is the post-modern stance. Living Without a Goal is all we can hope for, so we better get used to it.

The danger with this stance is that when there is no vision of progress or betterment to unify a society, the leaders will introduce fear to unify them.  The  BBC documentary series "The Power of Nightmares" argues that this is what recently happened in the US. When the hope of technology solving everything (he glorious days of Progress, with a capital P) petered out, it was replaced by the fear of communism as a way of unifying the country. When communism rotted from the inside and collapsed,  the fear of terrorism had to replace it. That exaggerated fear governed the past decade. But unless there is a plausible, desirable vision of betterment, one that billions can agree on, another fear will have to be found.

In that way I think there is a moral imperative to articulate our path towards something better. Not to leave it a vague post-modernist muddle. Not to shirk from the complexity and realities of costs. And not even to expect everyone to consent.

I don’t know if it is possible. It may be as the postmodernists insist: a vision relegated to the past. But I think we’ll behave better to each other, and towards future generations, if we can tease out a scenario of near-future progress for 8 billion humans and our uncountable natural co-inhabitants on this planet.

If you have a plausible desirable version of progress I'd like to hear it.

The technium is not an inert surface, but an active force in our lives. Our inner lives are shaped by our language and alphabet, by our tools of seeing, by our notions of laws and justice – all of which we have invented. Once invented, they push back against us. The internet and all the other tools we have created in the last 100,000 years allow us to remake ourselves.

Into what? That’s the ongoing mega-question of the next several centuries at least. What are we? What can we be? What should we be?

Every new technology we create, such as the web or cloning, forces another iteration of this refrain: who then shall we be? To answer it we will dive deep into our natures, our traditions, and most of all into new technologies.

•  We first search our own human behavior for answers for who we can or should be with this new stuff. We go back into our animal evolution to see what powers we have. Or we delve into our social history and look to the things we have accomplished in the past. We point to the best of humanity (everyone will have their own list), and say to ourselves: we can be more of that! So, "more of the best of humanity" is one answer to what we might aim for.

•  We can also search our fantasies. The myths of superman, frankenstein, the singularity, X-Men, and science fiction aliens are attempts by our collective unconscious to imagine future versions of our species. I think it would be a wonderful exercise for some social science graduate student to round up all the examples of aliens in science fiction, and then categorize and analyze what powers they have in order to gauge the contours of desire for future humans. (Let me know if such a collection has been done.) The possibilities of a trans-human species are vast, and after only a few hundred years of a speculative fiction industry, we have probably only begun to dream up the ways we could be different. The reservoir of our imagination is immense, and will remain a prime source for what we want to be.

•  Finally, we can also search technologies to see what powers are latent within them which might transfer to us as we meld with it. As we use technology to engineer our genome, or to keep us alive, we can't help absorb some of the dynamics of technology (just as technology can't help absorbing the dynamics of nature when we import evolution and adaption into their creation). We might discover entirely new powers or potentials that exist only in new technologies and decide, yes, let's be like that. As a trivial example, because of the scroll back bar, I feel it is essential that future humans should be able to scroll back life on a whim. So by listening to what technology wants, we may see answers to the question of what we could be, or what we want to be.

However as wide and deep as these pools of possibility are, I don't think humans can remake ourselves into ANYTHING we want. Some folks like the transhumanists, who take the challenge of remaking humans seriously, occasionally declare that humanity is a blank canvas and that with the assistance of technology, we can mold our species -- or at least individuals -- into any form we desire. The supposed super-power of the singularity is the secret sauce some believe will enable this transformation (although others don't require it). In this framework there is no limitation to what the mind can do (I call this thinkism) given enough time. We know for certain, as Arthur C Clarke stated, that  if we say some technology is impossible we are likely to be wrong.

From the World Transhumanist Association

But at the same time, the universe is real ONLY because it is limited.  Real things are real because the materials, physics, laws and other foundations constrain possibilities in a certain direction. Otherwise anything could happen, like magic. This means while we can imagine all kinds of things, the constraints of reality will prohibit some of them from ever being real.

In the short long-term, we are not close to exhausting all the possible ways we could evolve as humans. We might be able to bestow upon ourselves biological immortality, telepathic prowess, infallible memory, immunity to colds, better backs, painless births, and so on. We might even self-engineer our bodies to have incredible plasticity, so each person can dial their own tradeoffs in abilities.

But I think deciding what we want to be (or "should" be) is a much greater challenge. We know that reality is a tradeoff machine. Anything that  consumes energy or information requires a tradeoff. New powers will generate new problems, and incur new costs elsewhere. You can't be infinite in all directions.

As we imagine what we want humans to be, several large questions loom:  Will (should) we remain one species or many? Is it important that we go as a group where ever we are headed? Should we even remain human? Is humanity (whatever it is) worth keeping? How far could we evolve and still call ourselves human? Will it remain whatever the average person is? Or will we define ourselves by the outliers, the extreme versions, the future mega Einsteins and Mozarts?

Lastly, some would argue that humanity has less to do with powers or abilities and more to do with morality, and that the core of "what humans are" lies in the heart, and that the evolution of greater morality may not even show up in our bodies but in our societies. How we do things may be more important than what we do.

We are already deciding who we want to be as a species. Older new parents routinely get genetic counseling. Their choices have subtle but real downstream impact on the genetics of future generations. Environmental chemicals also affect our genes but in currently unknown ways. Prosthetic technology such as glasses, braces, and Google morph our selves in certain directions at large scale.

We are reshaping ourselves. But we are doing it without asking the question, who do we want to be? What are humans for? Who should we be?

I've been wondering why science took so long to appear. Why didn't China, which invented so many other things in the first millennial, just keep on going and invent science by 1000 AD? For that matter why didn't the Greeks invent the scientific method during their heyday? What were they missing?

As Carl Sagan declares in his book (and TV series) "Cosmos" : "Writings about fossils, gems, earthquakes, and volcanoes date back to the Greeks, more than 2300 years ago. Certainly, the most influential Greek philosopher was Aristotle. Unfortunately, Aristotle's explanations of the natural world were not derived from keen observations and experiments, as in modern science. Instead, they were arbitrary pronouncements based on the limited knowledge of his day."

But they could have been, even back then. Aristotle appears to have lacked no materials which would have prevented him from doing simple experiments and observations. There were many things he could not see without telescope and microscope, but there is still hundreds, thousands, if not millions of things he could have measured with tools he did have. But he did not because he didn't have the mindset.

We know that if a modern scientist today were sent back in time 2,300 years to the early Greek city states he or she could easily gather measurable data, and set up experiments with controls. In fact in the BBC produced a cool reality show called Rough Science that deposited scientists onto an island and had them create modern instruments such a telephone, phonograph, radio, etc., using materials found on the island. To make this crude anachronistic versions of modern technology the experts had to employ the scientific method with primitive tools. In some cases, their tools and materials were no better than what a wealthy Greek philosopher might have been able to get hold of in 300 BC.

It's not just simple things. Danny Hillis made a computer out of tinkertoys, a computer that the Greeks could have built, if they had thought of it. It would have been of no use to them, but the Greeks often dabbled in "useless" mathematical and philosophical knowledge. There are thousands of sophisticated technologies the Greeks could have produced with their tools, but did not because the tech was too many steps removed from everything else they were doing.

Hard science fiction author Greg Egan believes that even the theory of relativity could be deduced by a pre-industrial society, a case he makes in his new novel, Incandescence. As he says on his website (edited here):

"Incandescence" grew out of the notion that the theory of general relativity - widely regarded as one of the pinnacles of human intellectual achievement - could be discovered by a pre-industrial civilization with no steam engines, no electric lights, no radio transmitters, and absolutely no tradition of astronomy.

At first glance, this premise might strike you as a little hard to believe. We humans came to a detailed understanding of gravity after centuries of painstaking astronomical observations, most crucially of the motions of the planets across the sky...

How, then, could my alien civilization possibly reach the same conceptual heights, when they were armed with none of these apparent prerequisites? The short answer is that they would need to be living in just the right environment: the accretion disk of a large black hole... My aliens would probably need to be sheltering deep inside some rocky structure to protect them from the radiation of the accretion disk - and the glow of the disk itself would also render astronomy immensely difficult.

Blind to the heavens, how could they come to learn anything at all about gravity, let alone the subtleties of general relativity? After all, didn't Einstein tell us that if we're free-falling, weightless, in a windowless elevator, gravity itself becomes impossible to detect?

Not quite! To render its passenger completely oblivious to gravity, not only does the elevator need to be small, but the passenger's observations need to be curtailed in time just as surely as they're limited in space. Given time, gravity makes its mark. Forget about black holes for a moment: even inside a windowless space station orbiting the Earth, you could easily prove that you were not just drifting through interstellar space, light-years from the nearest planet. How? Put on your space suit, and pump out all the station's air. Then fill the station with small objects - paper clips, pens, whatever - being careful to place them initially at rest with respect to the walls.

Wait, and see what happens.

Most objects will eventually hit the walls; the exact proportion will depend on the station's spin. But however the station is or isn't spinning, some objects will undergo a cyclic motion, moving back and forth, all with the same period.

That period is the orbital period of the space station around the Earth. The paper clips and pens that are moving back and forth inside the station are following orbits that are inclined at a very small angle to the orbit of the station's center of mass. Twice in every orbit, the two paths cross, and the paper clip passes through the center of the space station. Then it moves away, reaches the point of greatest separation of the orbits, then turns around and comes back.

This minuscule difference in orbits is enough to reveal the fact that you're not drifting in interstellar space. A sufficiently delicate spring balance could reveal the tiny "tidal gravitational force" that is another way of thinking about exactly the same thing, but unless the orbital period was very long, you could stick with the technology-free approach and just watch and wait.

A range of simple experiments like this - none of them much harder than those conducted by Galileo and his contemporaries - were the solution to my aliens' need to catch up with Newton. But catching up with Einstein? Surely that was beyond hope?

I thought it might be, until I sat down and did some detailed calculations. It turned out that, close to a black hole, the differences between Newton's and Einstein's predictions would easily be big enough for anyone to spot without sophisticated instrumentation.

What about sophisticated mathematics? The geometry of general relativity isn't trivial, but much of its difficulty, for us, revolves around the need to dispose of our preconceptions. By putting my aliens in a world of curved and twisted tunnels, rather than the flat, almost Euclidean landscape of a patch of planetary surface, they came better prepared for the need to cope with a space-time geometry that also twisted and curved.

The result was an alternative, low-tech path into some of the most beautiful truths we've yet discovered about the universe.

If anachronistic science occurs in the past, then by definition there must be future technology that we are capable of creating today, if only we knew how. For instance, I have a public Long Bet prediction that in 2075 some smart high school kids will be able to cobble together a working artificial intelligence from vintage 2005 hardware unearthed in landfills. Using only materials that we have today, and a lot of new software, a perfectly good AI could be made. If true, that means that in theory we could make an AI today with the chips and hardware we already have. We are just missing the know-how to hook them up.

Similarly, we might be able to make an anti-gravity machine with the materials and technology we have today, if only we knew how. The major problem is that we don't know what technologies can be time shifted (and we know almost nothing about gravity). But we can be sure by simple statistics that some technologies can be shifted.  It's amazing how powerful "knowing that it can work" can be. It's worth at least 100 IQ points.

Imagine that in possibility space of knowledge the point "Greek logic" sits directly adjacent to "Greek computation," but separated by a deep chasm. Only a small set of knowledge separates them, but that short distance in knowledge took 20 centuries to cross. Perhaps it is the same today with "2005 hardware" and "2005 AI." Ordinarily there is no way to transverse that gap. But I wonder if there are techniques which would allow us to scientifically tunnel through to those adjacent places, where all that is separating the positions is "knowing it can  work"?

The current default algorithm for testing new technologies is the Precautionary Principle. There are several formulas of the Precautionary Principle but all variations of this heuristic hold this in common: a technology must be shown to do no harm before it is embraced. It must be proven to be safe before it is disseminated. If it cannot be proven safe, it should be prohibited, curtailed, modified, junked, or ignored. In other words, the first response to a new idea should be inaction until its safety is established. When an innovation appears, we should pause. The second step is to test it offline, in a model, or in any non-critical, safe, lowest-risk manner.  Only after is has been deemed okay should we try to live with it.

Unfortunately the Precautionary Principle doesn’t work as a reliable safeguard. Because of the inherent uncertainties in any model, laboratory, simulation, or test, the only reliable way to assess a new technology is to let it run in place. It has to be exercised sufficiently that it can begin to express secondary effects. When a technology is first cautiously tested  soon after its birth only its primary effects are being examined. But in most cases it is the unintended second-order effects of technologies that are usually the root of most problems. Second order effects often require a certain density, a semi-ubiquity, to reveal themselves. The main concern of the first automobiles was for the occupants -- that the gas engines didn’t blow up, or that the brakes don’t fail. But the real threat of autos was to society en masse -- the accumulated exposure to their minute pollutants and ability to kill others at high speeds, not to mention the disruptions of suburbs, and long commutes – all second order effects.

Second order effects – the ones that usually overtake society – are rarely captured by forecasts, lab experiments, or white papers. Science fiction guru Arthur C. Clarke made the observation that in the age of horses many ordinary people eagerly imagined a horseless carriage. The automobile was an obvious anticipation since it was an extension of the first order dynamics of a carriage –  a vehicle that goes forward by itself. An automobile would do everything a horse-pulled carriage did but without the horse. But Clarke went on to notice how difficult it was to imagine the second-order consequences of a horseless carriage, such as drive-in movies theaters, paralyzing traffic jams and road rage.

A common source of unforecastable effects of technologies stems from they way they interact with other technologies. In a 2005 report (PDF) analyzing why the former US Office for Technology Assessment did not have more of an impact, the researches concluded:

While plausible (although always uncertain) forecasts can be generated for very specific and fairly evolved technologies (e.g., the supersonic transport; a nuclear reactor; a particular pharmaceutical product), the radical transforming capacity of technology comes not from individual artifacts but from interacting suites of technologies that permeate society along many dimensions.

The absences of second-order effects in small precise experiments, and our collective impulse to adapt technology as we use it, make reliable models of advance technological innovations impossible. An emerging technology must be tested in action, and evaluated in real time. In other words the risks of a particular technology have to be determined by trial and error in real life. We can think of this vetting-by-action algorithm as the Proactionary Principle. Technologies are tested through action, rather than inaction.  In this approach the appropriate response to a new idea is to immediately try it out. 

And to keep trying it out, and testing it, as long as it exists. In fact, contrary to the Precautionary Principle, a technology can never be declared “proven safe.” It must be continuously tested with constant vigilance since it is constantly being re-engineered by users and the co-evolutionary environment it inhabits. The automobile today embedded in its matrix of superhighways, drive-ins, seat belts, gps, hypermiling is a different technology that the model T one hundred years ago. And most of those differences are due to secondary inventions rather than the internal combustion engine. In the same way Aspirin today, put into the context of other drugs in the body, changes in our longevity, pill-popping habits, cheapness, etc., is a different technology than either the folk medicines derived from the essence of willow bark, or the first synthesized version brought out by Bayer 100 years ago, even though they are all the same chemical, acetylsalicylic acid.  Technologies shift as they thrive. They are remade as they are used. They unleash second and third order consequences as they disseminate. And almost always, they exert completely unpredicted effects as they near ubiquity.

Therefore, technologies must be evaluated in action, by action. We test them in labs, we try them out in prototypes, we use them in pilot programs, we adapt our expectations, we monitor their alterations, we redefine their aims as they are modified, we retest them given actual behavior, we re-direct them to new jobs when we are not happy with their outcomes.

Of course we should forecast, anticipate and minimize known problems from the start.
All technologies will generate problems. None are problem free. All have social costs. And all technologies will cause disruptions to other technologies around them and may diminish technological benefits elsewhere. The problems of a new technology have to be weighed, balanced, and minimized but they cannot be fully eliminated.

Furthermore the costs of inaction (the default response called for by the Precautionary Principle), have to be weighed together with the costs of action. Inaction will also generate problems and unintended effects.  In a very fast changing environment the status quo has hidden substantial penalties that might only become visible over time.  These costs of inaction need to be added into the equations of evaluation.

The original version of the Proactionary Principle was first developed by Max More, the uber-extropian. He wrote a draft of the idea in 2004, and revised it in 2005. As he originally conceived it, the principle is an orientation, almost a philosophy. In the musings below I have simplified More’s elaborate philosophy to the point he may not recognize it. And to make it less confusing I punctuate it as the Pro-Actionary Principle. More’s second version contains a set of ten component principles; I have reduced these to five of my own. 

The five Pro-Actions are:

1. Anticipation

All tools of anticipation are valid. The more techniques we use the better because different techniques fit different technologies. Scenarios, forecasts and outright science fiction can give partial pictures. Objective scientific measurement of models, simulations, and controlled experiments should carry greater weight, but these too are only partial. The process should try to imagine as many horrors as glories, and if possible to anticipate ubiquity; what happens if everyone has this for free? Anticipation should not a judgment. Rather the purpose of anticipation is to prepare a base for the next four steps. It is a way to rehearse future actions.

2. Continuous assessment

We have increasing means to quantifiably test everything we use all the time. By means of embedded technology we can turn daily use of technologies into large scale experiments. No matter how much a new technology is tested at first, it should be constantly retest in real time. We also have more precise means of niche-testing, so we can focus on susceptible neighborhoods, subcultures, gene pools, use patterns, etc. Testing should also be continuous, 24/7 rather than the traditional batch mode. Further, new technology allows citizen-driven concerns to surface into verifiable science by means of self-organized assessments. Testing is active and not passive. Constant vigilance is baked into the system.

3. Prioritize risks, including natural ones

Risks are real, but endless. Not all risks are equal. They must be weighted and prioritized. Known and proven threats to human and environmental health are given precedence over hypothetical risks.

Furthermore the risks of inaction and the risks of natural systems must be treated symmetrically. In More’s words: “Treat technological risks on the same basis as natural risks; avoid underweighting natural risks and overweighting human-technological risks.”

4. Rapid restitution of harm

When things go wrong – and they always will – harm should be compensated quickly in proportion to actual damages. Penalizing for hypothetical harm or even potential harm demeans justice and weakens the system, reducing honesty and penalizing those who act in good faith. Mechanisms for actively fixing harms of current technologies indirectly aid future technologies, because it permits errors to be corrected quicker. The expectation that any given  technology will create harms of some sort (not unlike bugs) that must be remedied should be part of technology creation.

5. Redirection rather than prohibition

Prohibition does not work with technology. Absolute prohibition produces absolute outlaws. In a review of past attempts to ban technology, I discovered that most technologies could only be temporarily displaced. Either they moved to somewhere else on the planet, or they moved into a different niche. The contemporary ban on nuclear weapons has not eliminated them from the planet at all. Bans of genetically modified foods have only displaced these crops to other continents. Bans on hand guns may succeed for citizens but not soldiers or cops. From technology’s point of view, bans only change their address, not their identity. In fact what we want to do with technologies that produce more harm than good is not to ban them but to find them new jobs. We want to move DDT from an insecticide aerial-sprayed on crops to a household malaria remedy. Society becomes a parent for our technological children, constantly hunting for the right mix of beneficial technological friends in which cultivates the best side of each new invention. Often times the first job we assign to a technological is not at all ideal, and we may take many tries, many jobs, before we find a great role for a given technology.

People sometimes ask what possible role of humans might play in a world of extremely smart autonomous technology? I think the answer is we’ll play parents; redirecting active technologies into healthy jobs, good friends, and instilling positive values.

If so, we should be looking for highly evolved tools that assist our pro-actions. On our list should be better tools for anticipation, better tools for ceaseless monitoring and testing, better tools for determining and ranking risks, better tools for remediation of harm done, and better tools and techniques for redirecting technologies as they grow.

In 1978 Douglas Hofstadter wrote an mind-boggling book about recursive forms, called "Godel, Escher, Bach" after his three favorite geniuses who reveled in recursiveness. The award-winning book explored the nature of systems which bend their output back into themselves to make something new. GEB conjured with these "strange loops" with such wit and appropriate playfulness that is hard to imagine another book on the subject ever topping it.

The Technium is shaped by these same recursive forces. As Hofstadter showed, computer programing is founded on the notion of strange loops and regression, the most extreme representation being the infamous circular "infinite regress" of bad programming. Technology, like biology, is governed by feedback circuits. Up and down its being, technology will find itself looping back to create some weird strange loop of influence, and in that strange circuit some new force is launched into the technium. Recursive loopiness is thus the prime engine for bootstrapping and self creation.

Progress, intelligence, and life itself are all fueled at the fundamental level by bootstrapping, self-creation, autopoeis, auto-genesis -- all names for recursive organization. I found the following list of kinds of auto-structure in a 1986 paper by Peter Winiwarter, Autognosis (PDF) .

The forms of form.
The dimensions of dimension
The natural laws that govern natural laws.
The system of systems.
The control of control.
The hierarchical levels of hierarchies.
The strange loop of loops.
The consciousness of consciousness.
The organization of organization.
The evolution of evolution.
The structure of structure.
The provability of proofs.
The creation of creating.

At first glance these terms seem oxymoronic (self contradictory), or tautological (needless repetition). But on close inspection they are no more oxymoronic or tautological than say the network of networks, which is what we the internet is. In "Cosmic Jackpot: Why Our Universe Is Just Right for Life" Paul Davies recounts his investigation into the laws the govern the natural laws of the universe. Like all these meta forms, there is the problem of where their force lies. Is it in the loop, or outside of it? When the universe formed 14 billion years ago, were the meta laws in the universe, or outside of it? And if the laws shaping the natural laws were outside of the universe, what does that mean?

There must be a system of all systems, or a form which all forms adhere to, or some kind of control for controls, some kind of way to organize all organizations. The structure of proofs must be provable, types of categories must fall into some kind of categories.

Does everything have a meta?

And there meta-metas? Just as William James reputedly said there must be turtles standing beneath turtles all the way down the Hindu tower of creation, perhaps there are metas standing upon metas all the way up. The laws that shape the laws that shape the laws. But the tower of turtles or metas is the wrong way to think of this stack because the laws that shape the shape the laws are in the end shaped by the lowest law. As Davies points out, human observation may in fact shape the laws of the universe. Seen from the right vantage point, the meta loop simply enlarges to include more meta levels, so that everything circles back upon itself in a  larger loop.

The way in which the spookiness in quantum physics seems to resonate at both the largest and smallest scales of the universe is one indication of a very large recursive loop.

What this means for the technium is that the more potential recursive looping, generative meta-levels, and autopoesis that is engineered into it, the more the technium will become animated with the same sparks we find in similar autopoetic systems such as life and intelligence.

Furthermore it is the very point when feedback gets squirrely and weird that something important can happen. We should be looking for the places where genes control genes, laws mandate laws, software writes software, and intelligence designs intelligence. In those strange loops the meta will jump.

Every chart of technological progress zooms upward. Ray Kurzwiel has collected an entire gallery of graphs depicting the exponential upward trend in many, if not most, technological fields. All graphs of technological progress start low with small change several hundred years ago, and then begin to bend upwards in the last hundred, and then bolt upright to the sky in the last 50. A fairly typical chart would look like this one:

These charts capture a feeling we have that change is accelerating within our own lifetimes. Novelty arrives in a flash (compared to earlier), and there seems to be a shorter and shorter interval between novel changes. Further more, change in many areas seems to keep moving in one direction. Technologies get better and cheaper, faster and lighter, more common, easier and more powerful as we move into the future. And it is not just technology. The length of human lifespan increases, the rate of infant mortality decreases, and even average IQ inches forward every year.

If all this is true (and it may not be, but let’s accept its appearance for the moment), then what of long ago? Long ago there was not much evidence of progress at least how we now visualize it. Five hundred years ago technologies were not doubling in power and halving in price every 18 months. Waterwheels were not becoming cheaper every year. A hammer was not easier to use from one decade to next.  Iron was not increasing in strength. The yield of corn seed varied by the season’s climate, instead of bettering each year. You could not upgrade your oxen’s yoke for anything much better than what you already had. And your own expected longevity, or your children’s, was whatever it was for your parents. Wars, famine, storms, and curious events came and went, but there was no steady movement in any direction. There was in short, change without progress.

Progress as a notion did not arrive until the 17th century or so, when it appeared in the West during the Enlightenment. Progress is a child of science and technology. It was born out of the observation that our inventions make life better. Sanitation made us healthier, Farm tools make more food for less work. Gadgets made our homes more comfortable. The more inventions, the better. There was a tight feedback loop as increased knowledge enabled us to discover and manufacture more tools, and these tools allowed us to discover and learn more knowledge, and both the tools and knowledge made our lives easier and longer. The general enlargement of knowledge and comfort and choices – and the sense of well-being – was called progress.

The rise of progress coincided with the rise of technology. But what pushed technology? We had thousands, if not tens of thousands of years of human culture, steadily learning, passing on information from one generation to the next – but no progress. Sure, new things would occasionally be discovered and slowly disseminated, or rediscovered independently, but whatever improvement one might measure over centuries in the old days would be very small. In fact the average farming peasant who lived in 1650 AD had a life that was nearly indistinguishable from the average farming peasant who lived in 1650 BC, or 3650 BC. In some valleys of the world in some particular times, the fate of citizens might rise above historical average, but only to descend when a dynasty ended, or the climate shifted. Before 300 years ago the standard of the average human’s life was fairly interchangeable anywhere in time or place: people were perennially hungry, short-lived, limited in choices, and extremely dependent on traditions simply to survive to the next generation. (They may have been just as happy and maybe even more content than us, but that is another story.)

For thousands of years this slow cycle of birth and death crept along when suddenly, boom! technology appears and everything starts moving very fast. What caused the boom in the first place? What is the origin of our progress?

There are several factors but chief among them is the invention of what we loosely call science. The ancient world accumulated many fabulous inventions such as arch bridges, aqueducts, iron plows, stirrups, steel, suspension bridges, watermills, paper, vegetable dyes, and so on. These innovations were distributed unevenly throughout the ancient world because each was discovered in a trial and error fashion, and the dissemination of their benefits was haphazard and unlikely. Geographical and cultural boundaries often prevented many innovations from spreading far. For instance, the Chinese independently invented most of the ancient technologies listed above centuries, and in some cases millennia, before Europeans did. Their use was either very parochial, culturally bound, or even sometimes deliberately restricted. But in all cases of ancient ingenuity in Asia, Europe, Africa and the Americas, each invention was discovered by the typical hit or miss process of tinkerers making small darwinian variations on something that worked and then using the variation themselves. Most of these changes made no difference, but the few that did improve performance took centuries to migrate elsewhere. There was no method for successful invention.

The invention that transformed this uneven haphazard accumulation of improvement was the tool of science. Science entails not only the canonical process of observation and experiment, but also the systematic accumulation of what worked and why. A large system of peer-review journals, science societies, and reference libraries was more essential to the uplifting influence of science than was the notion of a predictive hypothesis. By systematically recording the evidence for beliefs, and investigating the reasons for why things worked, and then carefully distributing proven innovations, science quickly became the best tool for making new things the world had ever seen. Science was in fact a superior method for a culture to learn. It beat the best trial and error approach of the past.

That was why the enlightened West zoomed past the vast lead in innovations that China had built up over centuries. China was the origin of most of the great discoveries up until the age of science. The Chinese culture had invented all these things via trial and error. But the one central invention the Chinese never made was the invention of science itself.  Why China never invented science was the puzzle that obsessed the scholar Joseph Needham; if China could invent the most important inventions of all time, the compass, gunpowder and paper, why couldn’t they invent the scientific method as well? This conundrum eventually became known as Needham’s Question. While Needham proved China’s role in much of the world’s ancient inventions, he never came up with a good answer to his own question.  For whatever complicated cultural reason, ingenious China never devised the system of knowledge improvement we know as science.

It’s really too bad they did not because science is sort of like the third wish for the magic lantern. It is the tool that invents new tools. Once you invent science – which allows you to quickly invent many things – you have your hand on a grand lever that can propel you forward very quickly. And that’s what happened in the West starting approximately in the 17th century. By the 18th century, science had launched the industrial revolution, and progress was noticeable in the growing spread of cities.  As the contemporary charts of progress show, from there its rate kept accelerating over the years until it takes our breath away today.

But why was science invented in the Enlightenment? Why didn’t the Greeks invent it? Or the Egyptians? At first glance there seems to be no technological impediment for Egyptian (or Greek or Chinese) science. The necessary ingredients of the scientific method are conceptual and fairly low tech: A way to record, catalog and communicate written evidence, and the time to experiment.  A time traveler from today could journey back to that era and set up the scientific method in ancient Alexandria or Athens without much trouble. But would it prosper?

Maybe not. Science is costly for an individual. Sharing results is a marginal benefit if  you are chiefly seeking a better tool for today. The infrastructure costs of building a road or bridge are happily paid by individuals because the benefits of a road, bridge or aqueduct to an individual are immediate. The benefits of science are not apparent nor immediate for individuals. Science therefore requires more surplus and leisure in order to attain a sufficient number of individuals to join the collective and to willingly pay its costs of time and energy. Science may require a certain density of leisured population to thrive. That leisure is generated by pre-science inventions such as the plough, grain mills, domesticated power-animals, and other techniques which permit a steady surplus of food for large numbers of people. In Guns, Germs, and Steel Jared Diamond outlines a geographical theory for why Europe was the first to reach this threshold of surplus. Lucky Europe took thousands of years to slowly accumulate the necessary levels of technology needed to increase its population. Its early prosperity also enabled it to build the costly infrastructure of communication and wealth needed for inefficient experimentation and pursuit of abstract theories. While a well-fed population grew in number, the market and source for innovations also grew. Outside of the reign of science and technology a growing population will collapse as it meets Malthusian limits. But inside the reign of science a growing population creates a positive feedback loop wherein more people participate in scientific innovation and purchase the results, driving more innovation, and which births better nutrition, more surplus, more population, which feeds the cycle further.

In no time there is an exponential explosion of both people and progress. But this curious pairing of population and progress has not been examined very much. If we return to the charts of progress we find they fit almost exactly the curves of population. As population rises so does progress and vice versa. The two growths are heavily correlated, but correlated without causation.

We have many examples in modern times of increasing population suffering through declining living standards. That is happening in parts of Africa right now. On the other hand, throughout history we have very few examples of rising prosperity over the long term with declining population. Declining population is almost always associated with declining prosperity. Even during the decimations of the Black Plague, when 30% of an area’s population died, the change in living standards was uneven. Many of the overpopulated peasants in Europe and China prospered as their competition thinned out, but the quality of life for merchants and the upper class declined substantially. There was a redistribution of living standards, but not a net gain in new levels of progress during this time.  From this evidence we might deduce that population growth is necessary but not sufficient for progress.

Clearly the roots of progress lie deep in the structured knowledge of science and technology. But the flowering of this progressive growth seems to also need the growth of large human populations. Historian Niall Ferguson believes that on the global scale, the origins of progress lie only in expanding population. By this framework in order to elevate populations beyond Malthusian limits you need science, but in the end, it is the increase in the number of humans that drives prosperity. More human minds invent more things and buy more inventions, including how to support more humans. More human minds equal more progress. The oft-reviled economist Julian Simon believed the same thing. He called human minds “the ultimate resource.” In his calculations, minds were the prime source of progress. The more the better.

Progress stems from the growth of human minds in two ways. It comes from the increase in number of minds and the increase in their collective structure and power. Science is a collective action. The solitary scientific genius is a myth. All the significant gains in science have come from integrating new knowledge into the deep wells of old knowledge. In fact the definition of a scientific discovery is not really “something we did not know before” but “something we did not know before that now is woven into everything we knew before.” Without that latter part, the new knowledge is esoteric and idiosyncratic, and not part of “what we know.” The rich botanical and medical knowledge of indigenous shamans will remain “undiscovered” until this knowledge can be linked into the entire corpus of existing knowledge. Once that new nonintegrated knowledge is connected to our other knowledge, we can say we know it as a scientific society. In this way science is both the way we know things and what we collectively know. It is performed by individuals, but it inhabits a culture. The greater the pool of individuals in the culture, the smarter science gets.

The economy works in similar way. Much of our current economic prosperity is due to growth. The population of the US has steadily grown over the past few centuries ensuring a steadily expanding market for innovations. At the same time world population has been expanding ensuring economic growth worldwide. That world population has also grown in accessibility and desire as billions moved from subsistence farming into the marketplace. But try to imagine the same rise of wealth and stock prices in the past two centuries if the world market or the US market shrank every year.

If it is true that progress expands as human population expands, then we should be worried. Everyone has seen the official graph of peak human population. The peak number of humans on Earth keeps changing (downward) but the shape of their history does not. It looks like this:

But I bet that you have not seen anywhere a chart which shows you the other side of the peak after the year 2050. After the population peaks what happens? Does it sink, swim or rise again? Why is that never shown? Most charts simply ignore the question. There is no apology for the blank spot. Showing just one half of the curve has been so common for so long that no one asks for the other half. Why does our forecast stop precisely at the peak in 2050? Why don't we keep the forecast going? The only source I have found for a reliable projection of what happens on the other side of the peak of human population around 2050 is a set of UN scenarios for World Population in 2300, that is, for the next 300 years.

The high scenario assumes fertility rates remain at 1995 rates, or 2.35 children per woman. We already know this extreme version is not happening. The middle scenario assumes that the average fertility dips below replacement levels for 100 years and then for some reason returns to replacement level for the next 200 years. The low scenario assumes 1.85 children per woman. Today every country in Europe is below 2.0, and Japan is at 1.34.

Fertility rates in Europe. Dotted line is replacement level. (Source)

As countries become developed their fertility rate drops. This drop-off has happened for every modernizing country, and this universal decrease in fertility rates is known as the “demographic transition.” The problem is the demographic transition has no bottom. In developed countries the fertility rate keeps dropping. And dropping. Look at Europe (above) or Japan. Their fertility rate is headed to zero. In fact most countries, even developing countries, see their fertility rates dropping. Nearly half of the countries in the world are already under replacement level.

In other words, as prosperity increases due to expanding population, fertility rates drop, which will shrink population. This might be a homeostasis feedback mechanism that reins in exponential rates of progress. Or it might be wrong.

The UN 2300 scenarios are scary but the problem with the UN 300-year forecasts is that their dire scenario is not dire enough. The experts assume that even in the "worst-case scenario" fertility rates cannot go lower than the low rates found in places like Europe or Japan. Why do they assume this? Because it has never happened before. But of course this level of prosperity has never occurred before either. So far all evidence suggests that increased prosperity keeps lowering the number of children the average women wants. What if global fertility rates keep dropping below the replacement rate of 2.1 offspring for every woman in developed countries and 2.3 in developing countries? The replacement rate is what is needed to simply not decline, simply to maintain zero growth. To average 2.1 offspring means a significant portion of women have to have three, or four, or five babies in order to counter the childless and those with only one or two babies. What counter cultural force is at work prompting billions of modern, educated, working women to have 3, 4 or 5 babies? How many of your friends have four children? Or three? Just-a-few won’t matter in the long run.

Keep in mind that an enduring global fertility rate only a little below replacement level, say 1.9, will eventually, inevitably bring the world population to zero, because each year there are less and less babies. But long before human population drops to zero, the Amish and Mormons would save humankind with their prolific breeding and large families. Zeroing out is not the worry. The question is, if rising prosperity hinges on rising population, what happens to progress if there are centuries of slow population decline?

There are five scenarios:

1. The decline in world population halts at some manageable level, at a point where cultural forces encourage a steady replacement level of fertility. For instance, after the peak, the world population declines to 2 billion people with a fertility rate somewhere around 2.1. Perhaps technology makes having babies much easier, or much cheaper, though it is hard to imagine any way in which technology makes rearing three children any easier. Or perhaps there is social pressure to maintain the species, or social status in having a lot of children. Maybe robotic nannies change everything and having more than 2 kids becomes fashionable. It is not impossible to speculate on ways to maintain a status quo. But even if population leveled off, we don’t have any experience that a stagnant population produces rising progress.

2. While the census of human minds may decrease, we can build artificial minds, maybe even in the billions. Perhaps these artificial minds are all that is needed to keep prosperity expanding. To do so they would need to not only keep producing ideas, but also consuming them as well, just as humans do. Since they aren’t human (if you want a human mind make a baby) the prosperity and progress would likely look different from it is today.

3. Rather than expanding the number of human minds, maybe progress can keep increasing if the average human mind gets better, more powerful. Perhaps with the aid of always-on technologies, or genetic engineering, or pills, the potential of individual human minds increases, and this increase propels progress. Perhaps we increase our attention span, sleep less, live longer, and consume more, produce more, create more. The cycle spins faster with few more powerful minds.

4. We might have it all wrong. Maybe prosperity has nothing to do with increasing numbers of minds. Maybe consumption has no part in progress. We simply figure out how to increase living quality, choices, and possibilities with fewer and fewer people (who live longer and longer). It’s a very green vision, but also very alien to our current system. If every year there are less people as my potential audience, or my potential customers, I have to create things for a different reason than growth in audience or customers. A non-growth economy is hard to imagine. But stranger things have happened.

5. We plunge to small remnants, which in desperation breed madly and prosper. World population oscillates, up and down.

If the origins of prosperity lie solely in growth of human population, then it will paradoxically temper itself in the coming century. If the origins of progress lie outside of population growth, we’ll need to identify its source so that on the other side of the population peak, we can proceed to prosper.

I suspect, but cannot prove, the seeds of progress lie not in increasing numbers of human minds, or artificial minds, or more powerful individual minds, but in the emergence of a more complex group mind, made of fewer humans, many more machines, and a new way of thinking.

Many folks responded to my inquiry about evidence of a global super-organism. Among the most detailed and well-considered was Nova Spivack's long essay posted on Twine. Twine is a crowd-sourced aggregator of knowledge, superficially like the shared bookmarks of Delicious, or Stumbleupon, but with more room for comments and potentially more connections between posts. Nova founded Twine. I've been trying it out. One idea Nova mentioned in his essay I think is worth developing. He suggest three stages of development for collective action.

1. Crowds. Crowds are collectives in which the individuals are not aware of the whole and in which there is no unified sense of identity or purpose. Nevertheless crowds do intelligent things. Consider for example, schools of fish, or flocks of birds. There is no single leader, yet the individuals, by adapting to what their nearby neighbors are doing, behave collectively as a single entity of sorts.

2. Groups. Groups are the next step up from crowds. Groups have some form of structure, which usually includes a system for command and control. They are more organized. Groups are capable of much more directed and intelligent behaviors. Families, cities, workgroups, sports teams, armies, universities, corporations, and nations are examples of groups. They may have a primitive sense of identity and self, and on the basis of that, they are capable of planning and acting in a more coordinated fashion.

3. Meta-Individuals. The highest level of collective intelligence is the meta-individual. This emerges when what was once a crowd of separate individuals, evolves to become a new individual in its own right, and is facilitated by the formation of a sophisticated meta-level self-construct for the collective. This new whole resembles the parts, but transcends their abilities.  High level collective consciousness requires a sophisticated collective self construct to serve as a catalyst.

What Nova Spivack suggests here is that the path from random population to meta-individual is a path of increasing structure. The parts are more tightly bound in relationships, and as they gain in interdependence, the whole advances to the next phase. I think a close study of how meta-individuals, or super-organisms (which I think are the same thing), form would reveal that there they be more than 3 stages, or perhaps more than one pathway.  I think the main research hurdle in describing this development is to specify what exactly is being structured. My guess is that it is the informational nature of the organism.

In the landmark book "The Major Transitions in Evolution"  the authors Smith and Szathmary lay out the eight major phases of development in biological evolution so far, and perhaps not remarkably, these eight stages resemble the path from random population to meta-individuals at each level. In other words, Smith and Szathmary say that evolution is the continued, graduated progression in which smaller units form larger, higher level units, and then those new meta-individuals start to form a new group, where each meta-individual is a mere individual. Thus life has formed a super-organism structure eight times so far.  These eight levels or stages of super-organization are:

From replicating molecules to bounded population of molecules
From populations of replicators to chromosomes
From RNA chromosomes to DNA genes and proteins
From Prokaryotes to Eukaryotes
From Asexual clones to sexual populations
From single cell protists to multicelluar organisms
From solitary individuals to colonies
From animal societies to language-based human societies

As the Wikipedia entry on the theory states, Smith and Szathmary extract out several principles they find common to these eight transitions.

  1. Smaller entities have often come about together to form larger entities. e.g. Chromosomes, eukaryotes, sex multicellular colonies.
  2. Smaller entities often become differentiated as part of a larger entity. e.g. DNA & protein, organelles, anisogamy, tissues, castes
  3. The smaller entities are often unable to replicate in the absence of the larger entity. e.g. Organelles, tissues, castes
  4. The smaller entities can sometimes disrupt the development of the larger entity e.g. Meiotic drive (selfish non-Mendelian genes), parthenogenesis, cancers, coup d’état
  5. New ways of transmitting information have arisen.e.g. DNA-protein, cell heredity, epigenesis, universal grammar.

I believe the last point is the cause and not a symptom of the transition.

Another way to view these transitions is as increased levels or varieties of cooperation. At each stage there is a tension between the selfish needs of the individual and the needs of the collective.  Robert Wright, writing in "Nonzero" argues that the evolution of humanity is one long progression of increasing cooperation, starting from the first cell of life, where both "sides" win. Rather than having to choose the interests of the individual or the meta-individual collective in a zero-sum game, evolution innovates ways to structure cooperation so that both the individual and the group benefit in a non-zero-sum win/win.  John Stewart, author of "Evolution's Arrow", argues that the direction of evolution is to extend cooperation over large spans of time and space. In the beginning atoms "cooperated" to form molecules, than replicators, then DNA, and so on, where greater amounts of material are interdependent for greater lengths of time. He suggests we can see where evolution is going by imagining a next phase which will increases the span of cooperation further.

That of course, would be the ninth transition,

From human society to a global super-organism containing both humans and their machines.

For this to happen, humans would have to benefit directly as well as the One Machine. (Nova suggests we abbreviate the One Machines as OM, pronounced Om, as in the mantra. That works for me.) There has to be a non-zero sum benefit for individual humans and for the larger collective of the OM. We see such benefits in the use of the web. In fact the web is ruled by network effects, which is another way of stating the increase benefits accrue to a collective (network) with the participation of additional individuals, who join because they also get direct benefit. Humans use Google because they benefit greatly, and their use makes Google better.

At every stage of evolutionary development we see

1. Increased cooperation among parts, benefiting both parts and the whole.
2. Increased span of interdependence in space and time.
3. Increase complexity of informational flow.
4. Emergence of a new level of control.

For the ninth transition in life's evolution -- the transition to a planetary level organization of humans and machines -- we should expect to see:

1. Increased cooperation among humans, benefiting both humans and the OM.
2. Increased span of interdependence. Planetary scale, things happening and enduring longer or quicker than before.
3. Increase complexity of informational flow. New ways of connecting, organizing, relating not possible before.
4. Emergence of a new level of control. An innovation (like DNA, or spinal cord, government) that takes control of functions in order to benefit constituents non-zero-ly.

I am not the first, nor the only one, to believe a superorganism is emerging from the cloak of wires, radio waves, and electronic nodes wrapping the surface of our planet. No one can dispute the scale or reality of this vast connectivity. What's uncertain is, what is it? Is this global web of computers, servers and trunk lines a mere mechanical circuit, a very large tool, or does it reach a threshold where something, well, different happens?

So far the proposition that a global superorganism is forming along the internet power lines has been treated as a lyrical metaphor at best, and as a mystical illusion at worst. I've decided to treat the idea of a global superorganism seriously, and to see if I could muster a falsifiable claim and evidence for its emergence.

My hypothesis is this: The rapidly increasing sum of all computational devices in the world connected online, including wirelessly, forms a superorganism of computation  with its own emergent behaviors.

Superorganisms are a different type of organism. Large things are made from smaller things. Big machines are made from small parts, and visible living organisms from invisible cells. But these parts don't usually stand on their own. In a slightly fractal recursion, the parts of a superorganism lead fairly autonomous existences on their own. A superorganism such as an insect or mole rat colony contains many sub-individuals. These individual organisms eat, move about, get things done on their own. From most perspectives they appear complete. But in the case of the social insects and the naked mole rat these autonomous sub individuals need the super colony to reproduce themselves. In this way reproduction is a phenomenon that occurs at the level of the superorganism.

I define the One Machine as the emerging superorganism of computers. It is a megasupercomputer composed of billions of sub computers. The sub computers can compute individually on their own, and from most perspectives these units are distinct complete pieces of gear. But there is an emerging smartness in their collective that is smarter than any individual computer. We could say learning (or smartness) occurs at the level of the superorganism.

Supercomputers built from subcomputers were invented 50 years ago. Back then clusters of tightly integrated specialized computer chips in close proximity were designed to work on one kind of task, such as simulations. This was known as cluster computing. In recent years, we've created supercomputers composed of loosely integrated individual computers not centralized in one building, but geographically distributed over continents and designed to be versatile and general purpose. This later supercomputer is called grid computing because the computation is served up as a utility to be delivered anywhere on the grid, like electricity. It is also called cloud computing because the tally of the exact component machines is dynamic and amorphous - like a cloud. The actual contours of the grid or cloud can change by the minute as machines come on or off line.

There are many cloud computers at this time. Amazon is credited with building one of the first commercial cloud computers. Google probably has the largest cloud computer in operation. According to Jeff Dean one of their infrastructure engineers, Google is hoping to scale up their cloud computer to encompass 10 million processors in 1,000 locations.

Each of these processors is an off-the-shelf PC chip that is nearly identical to the ones that power your laptop. A few years ago computer scientists realized that it did not pay to make specialized chips for a supercomputer. It was far more cost effective to just gang up rows and rows of cheap generic personal computer chips, and route around them when they fail. The data centers for cloud computers are now filled with racks and racks of the most mass-produced chips on the planet. An unexpected bonus of this strategy is that their high production volume means bugs are minimized and so the generic chips are more reliable than any custom chip they could have designed.

If the cloud is a vast array of personal computer processors, then why not add your own laptop or desktop computer to it?  It in a certain way it already is. Whenever you are online, whenever you click on a link, or create a link, your processor is participating in the yet larger cloud, the cloud of all computer chips online. I call this cloud the One Machine because in many ways it acts as one supermegacomputer.

The majority of the content of the web is created within this one virtual computer. Links are programmed, clicks are chosen, files are moved and code is installed from the dispersed, extended cloud created by consumers and enterprise - the tons of smart phones, Macbooks, Blackberries, and workstations we work in front of. While the business of moving bits and storing their history all happens deep in the tombs of server farms, the cloud's interaction with the real world takes place in the extremely distributed field of laptop, hand-held and desktop devices. Unlike servers these outer devices have output screens, and eyes, skin, ears in the form of cameras, touch pads, and microphones. We might say the cloud is embodied primarily by these computer chips in parts only loosely joined to grid.

This megasupercomputer is the Cloud of all clouds, the largest possible inclusion of communicating chips. It is a vast machine of extraordinary dimensions. It is comprised of quadrillion chips, and consumes 5% of the planet's electricity. It is not owned by any one corporation or nation (yet), nor is it really governed by humans at all. Several corporations run the larger sub clouds, and one of them, Google, dominates the user interface to the One Machine at the moment.

None of this is controversial. Seen from an abstract level there surely must be a very large collective virtual machine. But that is not what most people think of when they hear the term a "global superorganism." That phrase suggests the sustained integrity of a living organism, or a defensible and defended boundary, or maybe a sense of self, or even conscious intelligence.

Sadly, there is no ironclad definition for some of the terms we most care about, such as life, mind, intelligence and consciousness. Each of these terms has a long list of traits often but not always associated with them.  Whenever these traits are cast into a qualifying definition, we can easily find troublesome exceptions. For instance, if reproduction is needed for the definition of life, what about mules, which are sterile?  Mules are obviously alive. Intelligence is a notoriously slippery threshold, and consciousness more so. The logical answer is that all these phenomenon are continuums. Some things are smarter, more alive, or less conscious than others. The thresholds for life, intelligence, and consciousness are gradients, rather than off-on binary.

With that perspective a useful way to tackle the question of whether a planetary superorganism is emerging is to offer a gradient of four assertions.

There exists on this planet:

• I    A manufactured superorganism

• II    An autonomous superorganism
• III  An autonomous smart superorganism
• IV  An autonomous conscious superorganism

These four could be thought of as an escalating set of definitions. At the bottom we start with the almost trivial observation that we have constructed a globally distributed cluster of machines that can exhibit large-scale behavior. Call this the weak form of the claim. Next come the two intermediate levels, which are uncertain and vexing (and therefore probably the most productive to explore). Then we end up at the top with the extreme assertion of "Oh my God, it's thinking!"  That's the strong form of the superorganism. Very few people would deny the weak claim and very few affirm the strong.

My claim is that in addition to these four strengths of definitions, the four levels are developmental stages through which the One Machine progresses. It starts out forming a plain superorganism, than becomes autonomous, then smart, then conscious. The phases are soft, feathered, and blurred. My hunch is that the One Machine has advanced through levels I and II in the past decades and is presently entering level III. If that is true we should find initial evidence of an autonomous smart (but not conscious) computational superorganism operating today.

But let's start at the beginning.

LEVEL I
A manufactured superorganism

By definition, organisms and superorganisms have boundaries. An outside and inside. The boundary of the One Machine is clear: if a device is on the internet, it is inside. "On" means it is communicating with the other inside parts. Even though some components are "on" in terms of consuming power, they may be on (communicating) for only brief periods. Your laptop may be useful to you on a 5-hour plane ride, but it may be technically "on" the One Machine only when you land and it finds a wifi connection. An unconnected TV is not part of the superorganism; a connected TV is.  Most of the time the embedded chip in your car is off the grid, but on the few occasions when its contents are downloaded for diagnostic purposes, it becomes part of the greater cloud. The dimensions of this network are measurable and finite, although variable.

The One Machine consumes electricity to produce structured information. Like other organisms, it is growing. Its size is increasing rapidly, close to 66% per year, which is basically the rate of Moore's Law. Every year it consumes more power, more material, more money, more information, and more of our attention. And each year it produces more structured information, more wealth, and more interest.

On average the cells of biological organisms have a resting metabolism rate of between 1- 10 watts per kilogram. Based on research by Jonathan Koomey a UC Berkeley, the most efficient common data servers in 2005 (by IBM and Sun) have a metabolism rate of 11 watts per kilogram. Currently the other parts of the Machine (the electric grid itself, the telephone system) may not be as efficient, but I haven't found any data on it yet. Energy efficiency is a huge issue for engineers. As the size of the One Machine scales up the metabolism rate for the whole will probably drop (although the total amount of energy consumed rises).

The span of the Machine is roughly the size of the surface of the earth. Some portion of it floats a few hundred miles above in orbit, but at the scale of the planet, satellites, cell towers and servers farms form the same thin layer.  Activity in one part can be sensed across the entire organism; it forms a unified whole.

Within a hive honeybees are incapable of thermoregulation. The hive superorganism must regulate the bee's working temperature. It does this by collectively fanning thousands of tiny bee wings, which moves hot air out of the colony. Individual computers are incapable of governing the flow of bits between themselves in the One Machine.

Prediction: the One Machine will continue to grow. We should see how data flows around this whole machine in response to daily usage patterns (see Follow the Moon). The metabolism rate of the whole should approach that of a living organism.

LEVEL II
An autonomous superorganism

Autonomy is a problematic concept. There are many who believe that no non-living entity can truly be said to be autonomous. We have plenty of examples of partial autonomy in created things. Autonomous airplane drones: they steer themselves, but they don't repair themselves. We have self-repairing networks that don't reproduce themselves. We have self-reproducing computer viruses, but they don't have a metabolism. All these inventions require human help for at least aspect of their survival. To date we have not conjured up a fully human-free sustainable synthetic artifact of any type.

But autonomy too is a continuum. Partial autonomy is often all we need - or want. We'll be happy with miniature autonomous cleaning bots that requires our help, and approval, to reproduce. A global superorganism doesn't need to be fully human-free for us to sense its autonomy. We would acknowledge a degree of autonomy if an entity displayed any of these traits: self-repair, self-defense, self-maintenance (securing energy, disposing waste), self-control of goals, self-improvement. The common element in all these characteristics is of course the emergence of a self at the level of the superorganism.

In the case of the One Machine we should look for evidence of self-governance at the level of the greater cloud rather than at the component chip level. A very common cloud-level phenomenon is a DDoS attack. In a Distributed Denial of Service (DDoS) attack a vast hidden network of computers under the control of a master computer are awakened from their ordinary tasks and secretly assigned to "ping" (call) a particular target computer in mass in order to overwhelm it and take it offline. Some of these networks (called bot nets) may reach a million unsuspecting computers, so the effect of this distributed attack is quite substantial. From the individual level it is hard to detect the net, to pin down its command, and to stop it. DDoS attacks are so massive that they can disrupt traffic flows outside of the targeted routers - a consequence we might expect from an superorganism level event.

I don't think we can make too much of it yet, but researchers such as Reginald Smith have noticed there was a profound change in the nature of traffic on the communications network in the last few decades as it shifted from chiefly voice to a mixture of data, voice, and everything else. Voice traffic during the Bell/AT&T era obeyed a pattern known as Poisson distribution, sort of like a Gaussian bell curve. But ever since data from diverse components and web pages became the majority of bits on the lines, the traffic on the internet has been following a scale-invariant, or fractal, or power-law pattern. Here the distribution of very large and very small packets fall out onto a curve familiarly recognized as the long-tail curve. The scale-invariant, or long tail traffic patterns of the recent internet has meant engineers needed to devise a whole set of new algorithms for shaping the teletraffic. This phase change toward scale-invariant traffic patterns may be evidence for an elevated degree of autonomy. Other researchers have detected sensitivity to initial conditions, "strange attractor" patterns and stable periodic orbits in the self-similar nature of traffic - all indications of self-governing systems. Scale-free distributions can be understood as a result of internal feedback, usually brought about by loose interdependence between the units. Feedback loops constrain the actions of the bits by other bits.  For instance the Ethernet collision detection management algorithm (CSMA/CD) employs feedback loops to manage congestion by backing off collisions in response to other traffic.  The foundational TCP/IP system underpinning internet traffic therefore "behaves in part as a massive closed loop feedback system." While the scale free pattern of internet traffic is indisputable and verified by many studies, there is dispute whether it means the system itself is tending to optimize traffic efficiency - but some believe it is.

Unsurprisingly the vast flows of bits in the global internet exhibit periodic rhythms. Most of these are diurnal, and resemble a heartbeat. But perturbations of internet bit flows caused by massive traffic congestion can also be seen. Analysis of these "abnormal" events show great similarity to abnormal heart beats. They deviate from an "at rest" rhythms the same way that fluctuations of a diseased heart deviated from a healthy heart beat.

Prediction: The One Machine has a low order of autonomy at present. If the superorganism hypothesis is correct in the next decade we should detect increased scale-invariant phenomenon, more cases of stabilizing feedback loops, and a more autonomous traffic management system.

LEVEL III
An autonomous smart superorganism

Organisms can be smart without being conscious. A rat is smart, but we presume, without much self-awareness. If the One Machine was as unconsciously smart as a rat, we would expect it to follow the strategies a clever animal would pursue. It would seek sources of energy, it would gather as many other resources it could find, maybe even hoard them. It would look for safe, secure shelter. It would steal anything it needed to grow. It would fend off attempts to kill it. It would resist parasites, but not bother to eliminate them if they caused no mortal harm. It would learn and get smarter over time.

Google and Amazon, two clouds of distributed computers, are getting smarter. Google has learned to spell. By watching the patterns of correct-spelling humans online it has become a good enough speller that it now corrects bad-spelling humans. Google is learning dozens of languages, and is constantly getting better at translating from one language to another. It is learning how to perceive the objects in a photo. And of course it is constantly getting better at answering everyday questions. In much the same manner Amazon has learned to use the collective behavior of humans to anticipate their reading and buying habits. It is far smarter than a rat in this department.

Cloud computers such as Google and Amazon form the learning center for the smart superorganism. Let's call this organ el Googazon, or el Goog for short. El Goog encompasses more than the functions the company Google and includes all the functions provided by Yahoo, Amazon, Microsoft online and other cloud-based services. This loosely defined cloud behaves like an animal.

El Goog seeks sources of energy. It is building power plants around the world at strategic points of cheap energy. It is using its own smart web to find yet cheaper energy places and to plan future power plants. El Goog is sucking in the smartest humans on earth to work for it, to help make it smarter. The smarter it gets, the more smart people, and smarter people, want to work for it. El Goog ropes in money. Money is its higher metabolism. It takes the money of investors to create technology which attracts human attention (ads), which in turns creates more money (profits), which attracts more investments.  The smarter it makes itself, the more attention and money will flow to it.

Manufactured intelligence is a new commodity in the world. Until now all useable intelligence came in the package of humans - and all their troubles.  El Goog and the One Machine offer intelligence without human troubles. In the beginning this intelligence is transhuman rather than non-human intelligence. It is the smartness derived from the wisdom of human crowds, but as it continues to develop this smartness transcends a human type of thinking. Humans will eagerly pay for El Goog intelligence. It is a different kind of intelligence. It is not artificial - i.e. a mechanical  -- because it is extracted from billions of humans working within the One Machine. It is a hybrid intelligence, half humanity, half computer chip.  Therefore it is probably more useful to us. We don't know what the limits are to its value. How much would you pay for a portable genius who knew all there was known?

With the snowballing wealth from this fiercely desirable intelligence, el Goog builds a robust network that cannot be unplugged. It uses its distributed intelligence to devise more efficient energy technologies, more wealth producing inventions, and more favorable human laws for its continued prosperity. El Goog is developing an immune system to restrict the damage from viruses, worms and bot storms to the edges of its perimeter. These parasites plague humans but they won't affect el Goog's core functions. While El Goog is constantly seeking chips to occupy, energy to burn, wires to fill, radio waves to ride, what it wants and needs most is money. So one test of its success is when El Goog becomes our bank. Not only will all data flow through it, but all money as well.

This New York Times chart of the October 2008 financial market crash shows how global markets were synchronized, as if they were one organism responding to a signal.

How far away is this? "Closer than you think" say the actual CEOs of Google, the company. I like the way George Dyson puts it:

If you build a machine that makes connections between everything, accumulates all the data in the world, and you then harness all available minds to collectively teach it where the meaningful connections and meaningful data are (Who is searching Whom?) while implementing deceptively simple algorithms that reinforce meaningful connections while physically moving, optimizing and replicating the data structures accordingly - if you do all this you will, from highly economical (yes, profitable) position arrive at a result - an intelligence -- that is "not as far off as people think."

To accomplish all this el Goog need not be conscious, just smart.

Prediction: The mega-cloud will learn more languages, answer more of our questions, anticipate more of our actions, process more of our money, create more wealth, and become harder to turn off.

LEVEL IV
An autonomous conscious superorganism

How would we know if there was an autonomous conscious superorganism? We would need a Turing Test for a global AI. But the Turing Test is flawed for this search because it is meant to detect human-like intelligence, and if a consciousness emerged at the scale of a global megacomputer, its intelligence would unlikely to be anything human-like.  We might need to turn to SETI, the search for extraterrestrial intelligence (ETI), for guidance. By definition, it is a test for non-human intelligence. We would have to turn the search from the stars to our own planet, from an ETI, to an ii - an internet intelligence. I call this proposed systematic program Sii, the Search for Internet Intelligence.

This search assumes the intelligence we are looking for is not human-like. It may operate at frequencies alien to our minds. Remember the tree-ish Ents in Lord of the Rings? It took them hours just to say hello. Or the gas cloud intelligence in Fred Hoyle's "The Black Cloud". A global conscious superorganism might have "thoughts" at such a high level, or low frequency, that we might be unable to detect it. Sii would require a very broad sensitivity to intelligence.

But as Allen Tough, an ETI theorist told me, "Unfortunately, radio and optical SETI astronomers pay remarkably little attention to intelligence.  Their attention is focused on the search for anomalous radio waves and rapidly pulsed laser signals from outer space.  They do not think much about the intelligence that would produce those signals." The cloud computer a global superorganism swims in is nothing but unnatural waves and non-random signals, so the current set of SETI tools and techniques won't help in a Sii.

For instance, in 2002 researchers analyzed some 300 million packets on the internet to classify their origins. They were particularly interested in the very small percentage of packets that passed through malformed. Packets (the message's envelope) are malformed by either malicious hackers to crash computers or by various bugs in the system. Turns out some 5% of all malformed packets examined by the study had unknown origins - neither malicious origins nor bugs. The researchers shrug these off. The unreadable packets are simply labeled "unknown." Maybe they were hatched by hackers with goals unknown to the researches, or by bugs not found. But a malformed packet could also be an emergent signal. A self-created packet. Almost by definition, these will not be tracked, or monitored, and when seen shrugged off as "unknown."

There are scads of science fiction scenarios for the first contact (awareness) of an emerging planetary AI. Allen Tough suggested two others:

One strategy is to assume that Internet Intelligence might have its own web page in which it explains how it came into being, what it is doing now, and its plans and hopes for the future. Another strategy is to post an invitation to ii (just as we have posted an invitation to ETI).  Invite it to reveal itself, to dialogue, to join with us in mutually beneficial projects. It is possible, of course, that Internet Intelligence has made a firm decision not to reveal itself, but it is also possible that it is undecided and our invitation will tip the balance.

The main problem with these "tests" for a conscious ii superorganism is that they don't seem like the place to begin. I doubt the first debut act of consciousness is to post its biography, or to respond to an evite. The course of our own awakening consciousness when we were children is probably more fruitful. A standard test for self-awareness in a baby or adult primate is to reflect its image back in a mirror. When it can recognize its mirrored behavior as its own it has a developed sense of self. What would the equivalent mirror be for an ii?

But even before passing a mirror test, an intelligent consciousness would acquire a representation of itself, or more accurately a representation of a self. So one indication of a conscious ii would be the detection of a "map" of itself. Not a centrally located visible chart, but an articulation of its being. A "picture" of itself. What was inside and what was outside.  It would have to be a real time atlas, probably distributed, of what it was. Part inventory, part operating manual, part self-portrait, it would act like an internal mirror. It would pay attention to this map. One test would be to disturb the internal self-portrait to see if the rest of the organism was disturbed. It is important to note that there need be no self-awareness of this self map. It would be like asking a baby to describe itself.

Long before a conscious global AI tries to hide itself, or take over the world, or begin to manipulate the stock market, or blackmail hackers to eliminate any competing ii's (see the science fiction novel "Daemon"), it will be a fragile baby of a superorganism. It's intelligence and consciousness will only be a glimmer, even if we know how to measure and detect it. Imagine if we were Martians and didn't know whether human babies were conscious or not. How old would they be before we were utterly convinced they were conscious beings? Probably long after they were.

Prediction: The cloud will develop an active and controlling map of itself (which includes a recursive map in the map), and a governing sense of "otherness."

What's so important about superorganism?

We don't have very scientific tests for general intelligence in animals or humans. We have some tests for a few very narrow tasks, but we have no reliable measurements for grades or varieties of intelligence beyond the range of normal IQ tests. What difference does it make whether we measure a global organism? Why bother?

Measuring the degree of self-organization of the One Machine is important for these reasons:

• 1) The more we are aware of how the big cloud of this Machine behaves, the more useful it will be to us. If it adapts like an organism, then it is essential to know this. If it can self-repair, that is vital knowledge. If it is smart, figuring the precise way it is smart will help us to be smarter.
• 2) In general, a more self-organized machine is more useful. We can engineer aspects of the machine to be more ready to self-organize. We can favor improvements that enable self-organization. We can assist its development by being aware of its growth and opening up possibilities in its development.
• 3) There are many ways to be smart and powerful. We have no clue to the range of possibilities a superorganism this big, made out of a billion small chips, might take, but we know the number of possible forms is more than one. By being aware early in the process we can shape the kind of self-organization and intelligence a global superorganism could have.

As I said, I am not the first nor only person to consider all this. In 2007 Philip Tetlow published an entire book, The Web's Awake, exploring this concept. He lays out many analogs between living systems and the web, but of course they are only parallels, not proof.

I welcome suggestions, additions, corrections, and constructive comments. And, of course, if el Goog has anything to say, just go ahead and send me an email.

What kind of evidence would you need to be persuaded we have Level I, II, III, or IV?

Wikipedia: Where consistent opinions are correct opinions. [Ooops. I inadvertently published this entry before I was finished. I'll return to this later.]

While there is only One Machine, there are many cloud computers. Each is a collective of computers acting as one computer. The Machine is the mega-cloud of all clouds. In a cloud world, all your work and data are stored on the web. For daily routines you are usually connected. Your devices are primarily gateways to the cloud.  You do all your work on the web, using web-based applications.  Common web apps are hosted email, Google Docs and Calendar, Facebook, Flickr, and most social network sites. Most importantly clouds should be invisible. You should not be aware that your music, or term papers, or shopping cart is stored on a distributed server farm. It should feel like all this info and activity is on your pod.

In fact, that is apparently what happens. According the just-released Pew Internet & American Life Project report on Use of Cloud Computing (PDF), two thirds of Americans online use cloud applications, even though very few of us are aware of it.

Sixty nine percent of online Americans use cloud computing in some form, with the largest usage seen for webmail (56 percent of respondents) and personal photo storage (34 percent).

It is easy to imagine moving a lot more of our informational activities to the cloud. If we migrate entirely to the cloud, what will life on the cloud feel like? How will our behavior change if this migration really is as invisible as it is suppose to be? How will cloudiness change us?

Right now clouds are chiefly created and run for the benefit of enterprise, rather than users. Or to be more exact, the initial customers of cloud computing are businesses. Firms serving up web services. Cloud computing is also known as grid computing and utility computing. There is a small industry of providers, suppliers and makers of applications emerging. Besides the well known clouds of Google, Amazon Web Services, there is also GridLayer, and Aptana Cloud, From the marketing page of Aptana Cloud comes this fairly utilitarian description of cloud computing from the enterprise POV:
 

Rather than worrying about where to host your web sites, how to configure your web server, and how to set up additional services, the Cloud enables you to push all of these concerns and worries to someone else, and more importantly, somewhere else. It's all handled for you on the internet, dynamically and completely managed. In short, all of your technology needs on the back-end are handled for you as a service, much like your electric or phone bill. 

That's the mechanics on the back side. What about us? What is the culture of cloudiness? My hunch (which I cannot prove yet) is that the consequences of going from the web to the cloud will exceed the changes we saw going onto the web originally.  I've teased out some cultural dynamics I think will prevail in a cloudy world:

Always On. Constant connection makes the "on" invisible. We do nothing to connect since it is now the default. It is like air. As behavior economists have shown, defaults make huge differences. The on default biases us toward connection and sharing. The always on default biases us toward expecting everything to be connected and always on. We expect all agents should always be on. All services should always be available. The drive toward 24/7 availability for everything continues. Not being always on is a disadvantage (with some exceptions). Always on also means more of our lives are captured, analyzed, digested, and "on". The more the cloud is always on, the more of our self is moved into the cloud.

Omnigenous. The distinction between being on the cloud and off disappears as more of the world is included. In the beginning the cloud is the cloud of servers, then it becomes the cloud of servers and all our laptops, and then it includes all those plus all our mobile phones and then all our TV screens as well. As the cloud keeps improving "network effects" kick in and those improvements draw in more devices, more sensors, more chips, making it even more attractive, until the cloud is omnigenous and includes every kind of thing. Cameras, microphones -- anything producing data will shift toward the cloud. So the cloud is the first place we go to for whatever we want. We may not always find it there, but it will always be the place we begin.

More Smarter. Clouds don't have to be smarter than the web we have now, but they are likely to be.  The web can be thought of hyperlinked documents. The  clouds can be thought of as hyper-linked data. Ultimately the chief reason to put things onto the cloud is to share their data deeply.  Not just to have a convenient backup, or to have always on access, which the cloud WILL give, but to be able to weave together the data and interactivity of the parts, and thereby make all the pieces much smarter and more powerful than they could possibly be alone.  It is not too much of an exaggeration to think of the cloud as the tool which allows us to share the elemental aspects of our data and activities in a way makes them smarter. The cloud is sort of a hivemind tool.

Inseparable Dependence. "Always on" plus superior performance will lead to supreme dependence on our part. There is the curious paradox that as the hard-lifting computation leaves the devices near our bodies and takes place in the invisible cloud it psychologically moves the device closer to us. As devices get smarter they get more intimate. A friend of mine had to ground their teenager for a serious infraction. They took her cell phone away. They were horrified when she became physically ill. It was almost as if she had an amputation. And she had in one sense. I was reminded of the book/movie The Golden Compass wherein the children in that world have spiritual guardian animals, called demons. These intangible animals sit on their shoulders or hover nearby and advise and comfort them. The most horrible torture in this world is to be separated from your demon. In the future, the cloud and cloud intelligence will be our Golden Compass demons. Separation from the advice and comfort afforded by the cloud will be horrendous and unbearable.

Extreme Reliability. No machine (or body) is perfect, but clouds will be more reliable than your standalone computer. The number of outage incidents recorded for clouds is fairly small given the total number of access-hours they provide.  According to the Cloud Computing Incident Database there have been 11 reported incidents in 2008. My very stable Mac has frozen more times than that this year. The reliability index for the cloud will mean it will increasingly be seen as the Backup. Our life's backup. No matter how many copies of something important you have offline, it won't feel safe until you put it online, on the cloud. We may also feel that if it is only on the cloud, it is not safe, but the reliability of the cloud will likely trump our own reliability. The consensus reliability of Wikipedia is changing our attitudes about where trust lies. In cloud life we may come to trust the aggregation of all sources over any single source.

The Extended Self. Where is my stuff? If I google my own mail to find out what I said, or rely on the cloud for my memory, where do "I" end and it starts? If all the images of my life, and all the snippets of interest, and all my notes, and all my chitchat with friends, and all my choices, and all my recommendations, and all my thoughts, and all my wishes -- if all this is sitting somewhere -- but nowhere in particular -- it changes how I think of myself. What happens if it were to go away? A very distributed aspect of me would go away. If McLuhan is right that tools are extensions of our selves -- a wheel an extended leg, a camera an extended eye -- than the cloud is our extended soul.  Or, if you prefer, our extended self.

Legal Conflict. The war over copyright will seem tame compared to the legal battles that the life in the cloud will hatch. Who's laws will prevail? The laws of your domicile, the laws of your server's domicile, or the laws of international exchange? Who gets your taxes if all the work is being done in the cloud? The transparent discontinuity between legal regimes will be a threat to the expansion of the cloud.  This friction will also force the growth of multiple clouds. Clouds with varying legal frameworks will compete at the global level, although within many geographical regions, there may be little choice. But the legal issues are not merely international. Who owns the data, you or the cloud? If all your email and voice calls go through the cloud, who is responsible for what it says? In the new intimacy of the cloud, when you have half-baked thoughts, weird daydreams, should they not be treated differently than what you really believe? What are the rights (and duties) of government's attempt at justice and fairness in an always on, omni cloud.

SharePrivacy. Privacy is over. Or more precisely, privacy as we imagined it is over. The extended self requires a different finesse for grappling with the levels of intimacy humans need. The binary functions of public/private, or even friend/not friend have to yield to more nuanced, more complex ways to describe our relationships. The Chinese have a unique name for every type of cousin (younger than you, older than you, your mom's brother, your dad's sister's son, etc.); the cloud will breed distinct ways of relating to agents we know, agents we once knew, agents we know we don't know, and so on. Sharing is the foundational action on the cloud. Some types of sharing will come to resemble what we used to call privacy.  It is impossible to share the same cloud to do everything and not evolve our notions and powers of sharing.

Socialism 2.0. The cloud is a collective. Social media is a type of socialism. Open source software projects are kinds of communitarian schemes. When people share their medical records (Patients Like Me), or personal genomes (23andme), or their family photo albums -- they are feeding a collective because by sharing them, their goods increase in value. The success of Wikipedia, Linux, and the web in general is priming a generation to be open to the power of the group. But unlike the old socialism models of old, the top-down social media of communism, the individuals are not forced to homogenize. Instead in this emerging Socialism 2.0, individuals (anyone can edit the encyclopedia!) are liberated via the power of the group. We don't have a very good vocabulary for this dynamic right now, so we are stuck using words like socialism which carry a very heavy cultural baggage. Nonetheless, living in the collective cloud will enhance the status of group power.

There must  be many others. If you think of one I haven't mentioned, please add it in the comments or email.

[Translations: Traditional Chinese, Dutch]

The fastest growing entity today is information. Information is expanding ten times faster than the growth of any other manufactured or natural product on this planet. According to a calculation Hal Varian, an economist at Google, and I made, world-wide information has been increasing at the rate of 66% per year for many decades. Compare that explosion to the rate of increase in even the most prolific manufactured stuff – like concrete, or paper -- which averages only 7% annually over decades.

We see the expansion of information everywhere. Less visible, harder to track, but exploding the same is the expanision of knowledge. The number of scientific articles published each year has been increasing in a steady rise for more than 50 years. Over the last 150 years the number of patent applications has increased. By this rough metric, knowledge is growing exponentially.

If knowlegde is growing exponentially we should be quickly running out of puzzles. Because of our accelerating rate of learning, a few writers declared we must be in the age of “the end of science.” This stance is hard to maintain for more than nano-second in view the current state-of-belief in physics: that 96% of all matter and energy in our universe is some unknown variety we call dark. It is clear that “dark” is a euphemism for ignorance.  We really have no idea what the bulk of the universe is made of.  We find a similar state of ignorance if we probe deeply into the cell, the brain, or even the earth.  We don’t know nothin’.

Yet it is also clear that we know vastly more about the universe than we did a century ago. This new knowledge has been put to practical use in such consumer goods as GPS and iPods, and a steady increase in our own lifespans. Our beneficial progress in knowledge comes from tools and technology. Telescopes, microscopes, fluoroscopes, oscilloscopes for instance, allow us to see in new ways, and when we looked with new tools, we suddenly win many new answers.

Yet the paradox of science is that every answer breeds at least two new questions. More answers, more questions. Telesco