We are all traveling into the future, as are our children and grandchildren. So it is personally relevant to everyone what that future is like. We call a very good future, a future where our species thrives, a utopia. We call a very bad future a dystopia.

We have some agency in the matter of futures, which sort of future we end up experiencing. Particularly, we have agency at a fortunate time such as this, where we have a global infrastructure, global economy and global science to direct at the problems we choose.

What things make something a dystopia?

I am sure that almost everyone reading this has been exposed to some examples of what is considered a dystopia. Science fiction books and movies are full of examples of dystopian futures. And I think it is fair to say that many people in parts of the world today are living in circumstances that closely resemble those dystopian scenarios. The end of the world is a popular scenario. The possibility that humanity will simply cease to exist at all appears in ancient revelations and pop culture. This very year 2012 has been singled out by some.

There are many ways in which humanity could be wiped out, anything from a man made environmental disaster, war, plague, and robot uprisings to large meteor impacts. Which scenario you are most worried about depends largely on what you think are the most significant developments or natural threats.

There is an even bigger category to be concerned with. Even if humanity continues to exist, a dystopia can mean the end of civilization. It could be a post-apocalyptic result or simply the outcome of ever increasing methods of control. In a dystopia without civilization we imagine people behaving without compassion. We generally do not want to be treated like objects or resources, to be nothing but a cog in a machine.

Civilization is about developments, empathy and ethics

So what is this civilization that separates us from dystopia? There are some crucial developments. Let us begin with evolution, the consequence of selection.

This is a very important concept, because selection will shape the future just as it has shaped the past. It is everywhere. Daniel Dennett has described this as Universal Darwinism.

Once again, that which we seek in civilization demonstrates what we would consider a dystopia. A machine world of uniformity, for example. Imagine if we created one system or computer brain that we considered good enough or superior, and if we created millions of copies of that. That is dystopia.

Face more challenges, experience more environments

Evolution takes place in an environment and in an epoch. We are the result of natural selection that made us suitable to the environment and challenges of a place and time. Things change.

Environments change and challenges change. One day, the Earth will no longer be a shelter to humanity. That could happen soon by our own hand, or by the unpredictable hammer from above, or perhaps at the latest when our own sun expands its searing atmosphere to engulf the Earth.

If we have time then we might ourselves move on to other places. But if we are still only adapted to Earth then it will be difficult, because we have to take a replica of its biosphere everywhere we go. In essence, Neil Armstrong never could fully touch and experience the moon, because he was still encased in a suit of Earth atmosphere, inhaling the scent of his own body.

It is also non-optimal to have senses and thinking selected for survival problems that were most relevant millions of years ago. Let us revisit the concept of Universal Darwinism with that problem in mind. Consider the big picture: What sort of intelligence and culture would inhabit and influence the most of universal space-time?

By adapting our bodies, we were able to inhabit and influence all of Earth. The clothing you wear, the cellphones you use, the cars you drive and the houses you live in are the tools that make it possible. So, the most adaptable will inhabit and influence most of everything that will ever be.

We have augmented to be capable of more

To be human is to be augmented. What we learned and what we teach all of our children is to use our minds in order to augment our bodies. Consider when you learned to drive a car. It is much faster and stronger than your limbs, but you make it your own and soon it feels entirely normal to delicately control a car in complex traffic situations.

We augmented our bodies in every way possible. So far, our minds made do by sharing burdens. We specialized to different skills, depending on each other ever more.

Culture continues to grow, and its complexity is the beauty of our creative abilities. We now use computing tools and networks such as the Internet to speed up and to add ever more information.

I remember when we used to learn how to carry out calculations and derivations in school. I remember when we used to learn facts and data about our history and society. Now we have to learn how to sift through masses of data, how to ask the right questions by entering the right Google phrases. We off-load most of the computation, the data collectors that add to the databases, and especially we rely on external memory.

Live longer, better

Meanwhile, we live longer and experience more. We can participate in a greater part of the future and play a role in it. But what does that really mean, that You can live longer and experience more?

What are you? What is a personal identity, a self? And correspondingly, what is everything else? You experience yourself sitting here, reading this. You feel the seat. You see and you hear. But really, those things are all results of something. They are generated, processed results. Everything that you experience, everything that you are thinking, remembering, your concept of what is around you, where and when you are… all of that is generated by mental processing. Without it there is nothing, and that processing is all there is to Being.

Some say the self is an illusion, but everything else is just as much an illusion. It is all a construct, a way of structuring things, labeling them, constraining the patterns of your mental activity. Just as much as we can say that your mind is generating an experience, the same is true at different scales. We can equally say that a society of minds is generating an experience. And similarly, parts of your mind, pieces of activity in your brain are parsing their input and generating output, creating their own experiences.

 

We need to understand this to be more enlightenment and to strive for better things. We generally do not want to fight or harm our friends, because we know them, feel kinship and understanding. We need to understand that everything we are, everything we experience, our very identities and our experiential universes are simply that which we are processing and generating in our minds. As we learn to understand these foundations of Being our civilization matures.

Being more adaptable, Substrate-Independence

There is no reason why processing information, which is the basis of experience at every level should be unique to one implementation of the processing functions, such as a human brain. In principle, the same processes could be carried out in many different substrates. Ultimately, that is where the solution to adaptability lies, in the ability to move functions of the mind to many different types of substrates – to be substrate independent minds (SIM).

That removes the constraints of a single environment and opens up the door to new senses and new ways of thinking. Imagine remembering with the precision of a computer database or finding optimal solutions with the comparative ease of a quantum computer.

To understand SIM, consider platform independent computer code. It requires a means of processing, but can run on many different platforms. Almost every religion attempts to address the problem of Being, and most espouse some form of adaptable existence whereby experience can be carried on in another substrate.

This is urgent, because we have a window of opportunity. We can tackle fundamental problems we all face, because civilization is largely intact. We have what it takes to get to the next stage.

SIM leads to Whole Brain Emulation

Ideally, a Substrate-Independent Mind would achieve all of the processing that we expect in the manner most optimal to the substrate it is in. In a computing analogy, that is when you write and compile software to suit a hardware platform. We cannot do that yet.

If you ask any honest neuroscientist: “Do we understand how the mind allows me to recognize my mother?” “Do we understand the human mind?”

The answer in each case has to be no. We simply do not understand enough about the strategies used by the mind at various levels from the top all the way down to cells, which is really what is being asked when someone asks “do we understand”.

Neuroscience has spent most of the last 100 years learning how to identify elements of brain physiology and how to measure signals and compounds at the level of neurons and synapses.

That is why nearly every serious effort to identify functions of a specific person’s mind and ultimately to transfer such to substrate-independent minds is presently seeking to do so through the most conservative means, which we call Whole Brain Emulation.

System Identification

An emulator re-implements function. You probably know some emulators, such as programs that allow you to run PC software on a Macintosh. Every emulation is achieved by carrying out what is known in engineering circles as System Identification.

System Identification is when you have a black box that receives input, carries out processing and produces output. You try to determine what functions constitute that processing by investigating the correlated input and output.

The very first step is of course to know what are your input and output signals of interest. Consider once more the computer analogy. Assume that we are trying to emulate the microprocessor of a PC. In that case, we know that the signals of interest are the streams of 1s and 0s that go into and come out of the chip. The 1s and 0s are really pulses of voltage above and below certain thresholds. There are many other signals, such as air pressure, cosmic radiation, noise on top of the pulses of voltage, heat being generated by the microprocessor. Those are not of interest.

Similarly, in the brain we should concentrate on the signals that are of interest at the relevant precision. Note the feedback loop that the brain creates with the rest of the body and its environment through neural action potentials or spikes. Sensory input produces spikes. Spikes drive muscles such as for speech. And the order and delay between spikes is essential for storing memory at synapses. If we could predict spike timing sufficiently we may have a working emulator.

Turning it into a feasible project

We are now talking about a concrete roadmap to SIM based on the requirements for system identification.

FIRST REQUIREMENT: How big can the black box be for which we can reliably identify functions that predict its behavior? The bigger the box, the longer you need to observe it. If we chose the entire brain as the black box then you would probably have to observe its input and output over the entire course of its life-span. What you deduce would still be flawed and likely miss latent functions.

With literally billions or trillions of operational elements within, tuning any emulation created at that level would be computationally intractable.

The more we know about the relevant I/O and the architecture of the brain, the smaller we can make the black boxes for which system identification needs to be carried out. This first requirement is all about determining the right scope and resolution for emulation.

SECOND REQUIREMENT: We will need a platform on which an emulation of a specific mind can be implemented. How much processing are we talking about?

Let’s assume a traditional general purpose supercomputer. And let us assume that we simplified system identification by building what we call compartmental models of neurons based on structural scans. Each compartment is like an electrical circuit and governed by a set of equations know as the Hodgkin-Huxley equations with several parameters to measure and tune.

Consider how many ATP molecules providing energy at the cellular level are needed for one action potential to propagate to neighboring neurons. And consider that 20-40W are consumed by the brain. From this I calculated how many events can take place in a unit of time. When each neuron is represented by 10,000 compartments, processing those events on a generic supercomputer would require one exaflop of computing power. Present supercomputers max out at 10 petaflops, which is 100 times too slow. But, US, European and even Indian initiatives aim to have exaflop computing centers up and running between 2017 and 2020.

That would be a brute-force approach. It is much better to co-design your hardware using neuromorphic computing. A famous example is the DARPA SyNAPSE project at IBM. Computation is not the main hurdle for SIM. The main hurdle is building better tools for large scale high resolution acquisition of data from the brain.

THIRD REQUIREMENT: Obtain the detailed specific structure, the connectome of an individual brain. The better that data is, the smaller the black boxes become for our system identification problem. We would like to be able to predict as much as possible about the parameters for a compartmental model from structural measurements.

Tools in this area are advancing rapidly, spurred on by research interest into the human connectome. In 2011, two teams published remarkable results demonstrating a proof of principle for system identification in retina and visual cortex using Serial Block Face Scanning Electron Microscopy techniques developed in the lab of Winfried Denk in combination with two-photon functional recordings.

Ken Hayworth, a strong proponent of whole brain emulation is improving the volume capacity of his earlier tool, the Automatic Tape collecting Ultramicrotome by developing a parallel processing technique for Focused Ion Beam Scanning Electron Microscopy at Janelia Farm laboratories.

FOURTH REQUIREMENT: We need reference measurements of characteristic responses at a high resolution to correct and tune parameters. Tuning all of the parameters of combined compartmental models that make up a whole brain is otherwise an intractable optimization problem. The functional recording techniques used in neuroscience today can obtain a very few measurements at high resolution using electrodes or a larger number of measurements at low spatial and temporal resolution using techniques such as MRI. We need something much better.

If we try to do this by improving external recording techniques then the distance at which measurements need to be resolved poses a physics problem.

If you want to resolve a signal at a given spatial resolution and within a given temporal resolution, but you increase the distance from being immediately adjacent to a synapse to being outside the skull then there is a quadratic increase in power requirements. At the resolutions required, this rapidly leads to doses that are far from non-invasive. They would be very damaging, and would severely affect measurements through their own effects on the neural tissue.

The brain carries out its own measurements at large scale and high resolution by remaining very proximate to the sources of activity, detecting activity through microscopic synaptic receptor channels. At the same scale, we may build means to measure without interfering. Also, the brain handles the enormous quantity of information by using a vast hierarchy of mostly local connections. In previous publications I have referred to this as the Demux-Tree approach to neural recording.

Practical implementations in development that are based on these insights are threefold. First there is a move to arrays with very many electrodes. Then there is work to create a means of recording neural activity at the molecular scale, using DNA or similar substrates for the recording. That is called a molecular ticker tape (a collaboration between Northwestern University, Harvard, and MIT).

Machines in Minds

The third implementation combines technologies to produce a microscopic hierarchical system for in-vivomeasurements.

The basic component is an agent built in familiar IC technology. Prior work has already shown that you can successfully combine microscopic chips with living cells (e.g. work by Gomez-Martinez et al., 2009).

A chip the size of a red blood cell can contain more transistors than the original Intel i4004 microprocessor. Power can be delivered in a number of ways, from magnetic induction to glucose fuel cells, but most easily through light. There is a wavelength of infrared light between 800 and 1000 nm at which tissue is essentially transparent.

Recording of activity can be done either by detecting voltages over a capacitor or by optical means when operated in combination with voltage sensitive proteins that are used to show activity in neurons.

To conduct brain-wide measurements and to deliver data to the outside, large numbers of microscopic agents need to collaborate, each carrying out specialized roles. They would form a team or a secondary network of computation within and side-by-side with the brain.

Measurements made by agents can be collected, multiplexed and converted into signals that are more readily identified by external imaging methods. Locations of measurements can be obtained by combining direct detection of larger hubs with a protocol for relative triangulated distances between agents.

These machines within the mind are purposely conceived as a combination of presently feasible technology. They are an ambitious next step in neuroscience that once again involves a collaboration with MIT and Harvard laboratories.

An opportunity to take while we have it

The long term future will either not involve us or will demand that we become vastly more adaptable. Right now, we have an incredible global infrastructure, an economy that – though shaken – is still powerful, and research and development are thriving. We don’t know if we will have those things in 20, 40 or 60 years.

Yes, it is clearly very ambitious to try to solve these fundamental problems that Universal Darwinism will throw our way. But that is exactly why now is the time to take it on. Right now, we have the means and the opportunity to bring about advances that open up our understanding of who we are, what it means to exist, to be, and to make us a species that will thrive. It stands to reason that we should grab that opportunity while it is here!

Randal A. Koene is a Dutch neuroscientist and neuroengineer, and co-founder of carboncopies.org, the outreach and roadmapping organization for Advancing Substrate-Independent Minds (ASIM). He is currently directing the Analysis team at the nanotechnology company Halcyon Molecular

A few month ago, I was at a party. One of the other guests was a woman I knew slightly. She is a graduate student at a certain university in Massachusetts—naturally I won’t say which one. She’s also one of those academics who is, well, what some people would call a “pain in the ass.” I, however, prefer the expression, “uncompromising.” But, I suppose, a rose by any other name, etc.

To my distress, I discovered that she’d heard from a friend of a friend that I write under various pennames. I’m one person when I do technical journalism, another when I do academic stuff, a third when I write fiction, and Victor Storiguard when I write about Transhumanism or when I do stories with a transhumanist theme.

Unfortunately, there was an open bottle of tequila at the open bar. She had never tried the stuff and tucked into it with the zeal of a recent convert. After one or two shots too many, the woman laced into me. Why did I write such drivel? And why under a nom de plume? Why hide my identity? Why conceal myself from the reading public?

I tried to explain that there were good reasons for me to use multiple names. For one thing, it can cost me a lot of money not to. If you’re writing for competing publications, you don’t want to have the same name in both of them. It tends to make one’s editors rather grumpy.

Besides, if you’re doing multiple genres, the way that I do both science fiction and academic nonfiction, you don’t want your readership to be disappointed in you. That is, you don’t want them to go to Amazon, seek out your titles, and then be dreadfully distressed when they find out that what they thought was a good Alien-Invasion-From-Mars story is, in fact, a lengthy and tedious meditation on why Christopher Marlowe had Faust go straight to hellfire while Goethe merely toasted him a bit. So, you write under two names—one for Aliens and one for Faust, and everyone’s happy.

This didn’t satisfy my academic critic. “You are the perfect example of the alienated post-industrial man, estranged from not only society but even from himself,” she said, more or less in those exact words. “You are the living embodiment of the Western World’s current Identity Crisis.”

Then, after giving me a pitying look, she turned away.

2.

I did have some minor vengeance on my academic friend. First, I discovered that she was using the term “Identity Crisis” without knowing that it had been invented by the great psychologist, Erik Erikson. Further, I found, she did not know that he used the term to mean a very specific set of mental problems common to a very specific set of individuals (i.e., people who do not successfully make the transition from adolescence’s natural uncertainty about one’s place in the universe).

Second, her inexperience with tequila became its own reward. The one or two shots too many turned to three or four, and before the night was done she was in the bathroom loudly suffering the consequences. (I may be alienated from my society. But at least I’m not alienated from my lunch.)

But, when I considered the incident later, what struck me most was her use of the word “identity,” and her assumption that we suffer from a crisis of same, that as individuals and as a civilization, we are not quite certain who we are. Moreover, she implied, that uncertainty is intensely painful for us.

And this idea was not original to her. Hang about a few faculty parties at any university, or cruise the web a bit, and you’ll start hearing the same words, repeated in the same ways, and spoken to mean the same thing. We are, say Those Who Know Best, horribly confused. All our certainties are turned to sand.

Thus, those who identified with their nations discover that the West is no longer the dominant culture in the world. We look about, watching the collapse of social structures and social norms, and ask, “Are we still Americans?” (Or Britons or Frenchmen or whatever).

Those of us who once identified with particular economic systems, now regard an economy that seems on the verge of collapse. In an age in which more and more, it seems, a tiny minority of the population controls more and more of the world’s resources, and in which vast corporations do business with fewer and fewer people, we ask “Am I a socialist or a libertarian? Or, indeed, do those terms mean anything at all any longer?”

We, who once knew that if all else failed there was at least the family to fall back on, now see the whole concept of “family” and our roles within it mutate even as we watch. The White Male, for instance, who once took pride in his job and his status as breadwinner, is now unemployed, watches power shift increasingly to his wife or sisters, and asks, “Am I still a man?”

And for all these excellent reasons and more, Those Who Know Best proclaim our Crisis, and wonder out loud if our identities, our very selves, are on the verge of Annihilation.

I think Those Who Know Best are wrong.

Or, more precisely, I hope they are very wrong. Because, if they aren’t, and if there really is a crisis of identity in the West and the world, then it is about to get a whole lot worse.

And Transhumanism will be the cause.

3.

What do we mean by identity?

Well, when we are asked that question, the short answer is “me.” Ego. Self. That something from which we cannot divorce without ceasing to exist. Admittedly, this (like all simple answers) leads to fantastically complicated questions. Am I the same “me” to my friends as I am to my family? Am I the same “me” that I am at work as when I am at play? Am I the same “me” as I write this to you as when I, say, write a letter to my mother?

Complicated questions, indeed, but for the moment let’s leave such queries to philosophers. Let us employ the techniques of wise Brother Occam and take the simplest, most pragmatic position possible. Let us say that “identity” resides within our own skins, or more precisely, our own skulls. In other words, let us assume that “I” is within the brain. That’s where our “selves” are kept, and so there is distinct a limit to that self. It does not extend beyond the cranium. Thus, you and I are separate entities, separate selves, because each of us possesses our own stream of consciousness. What occurs in my brain does not occur in yours.

Ah, but consider what technology can and will do to that definition of self. As anyone who reads H+ Magazine already knows, with bioprobes, brain wave monitors, and MRIs we are getting reasonably close to being able to read thoughts. We’re not there yet, but we are decidedly on our way.

But that means that we can also reproduce thought. If we can read it, we can write it. Soon enough (again, not tomorrow, but eventually) it will be possible for you and I to share thoughts, and sensations, and feelings. With a few nanotechnical devices in the right places, and some (neutrino-based?) successor to cell phone technology, we could be linked. I would know exactly what you felt and thought as you thought it and did it. And, of course, vice versa.

The good news is that finally we’ll have a way to enforce some kind of empathy on even the most self-centered individual. The better news is that the rest of us will have a fantastic new way of experiencing the world. You really will know how someone different from you regards the universe. You really will be able to walk a mile in their shoes.

But there’s the rub. What does it do to our concept of identity? If we can share thoughts, sensations, maybe even memories, are we still two people? Or are we one individual who happens to have a very loosely coupled nervous system?

But we’re just getting started, aren’t we? If you and I can link our psyches, why stop with just the two of us? Why not invite in a dozen friends? Or a hundred?

Or, why stop with human beings? Why not link up with other creatures? A dolphin? A whale? A lioness?

But, if we do that, if we link to things which aren’t human, are we ourselves still entirely human? If I share an intellect with a stag or a bear or a seagull, am “I” to some degree now a stag, a bear, and a seagull?

Let’s take it a step further. Now that we’ve confused ourselves with others, and even with the beasts and the birds of air, we also get a little mixed up on death. For instance, if I am connected to a dozen other people, and perhaps some things which aren’t people, what happens when I die? When, that is, the body in which I was born ceases to function? Well, if parts of my memories and feelings still exist in the shared mind-set of a dozen friends, maybe I’m not actually dead.

Complicated situations. And, all of them, mind you, arise from what we’ll be able to do with technology that is on the horizon—i.e., which isn’t too far beyond what we can do already. Imagine what happens to “self” when we’ve got mind uploading. What will “I” mean when “I” might be a widely distributed collection of natural and artificial bodies and brains, scattered across continents, or even on different planets?

What will identity mean if a thought begins with a part of one’s self that happens to be orbiting Alpha Centauri, and which will not end until a tenuous signal arrives back at earth after four, long, complicated years?

4.

According to my friend and critic, the graduate student, and people like her, this is all a recipe for disaster. How can the concept of “identity” even survive in such an age? How could we, limited humans that we are, endure that loss?

Here, of course, is where I make an audacious statement: to wit, identity ain’t that big a deal.

I know that in an age of individualism and libertarianism, that sounds pretty spooky. But, I will submit that the individual and identity are not quite the same things. I will further submit that most of the time when people talk about “identity,” or an “identity crisis,” they aren’t really talking about the self. They are actually talking about the relationship of the self to a group.

Look at the writings of alienated intellectuals. Listen to the people who say in song or story, “I don’t know who I am.” Almost always, what they are actually saying is “I don’t know who I am … in relation to the larger society.”

Thus, when the citizen of a nation in decline asks, “Am I still an American?” (or a Brit or Frenchman or whatever), what they’re actually asking is “Does this community of people still offer me sufficient rewards, or threaten sufficiently Draconian punishments, to cause me to continue to pretend that its members are somehow related to me, and thus worth dying or killing for, when in fact they are total strangers?”

Similarly, when an individual in a complicated economic system asks, “Should I be a socialist or a libertarian?” what they are actually asking is “Do the people in this particular marketplace value what I have to offer? And will they pay enough for it to justify my continued presence in their community?”

And, finally, the white male American, struggling with the shift of power to his wife and daughter, is not really asking “Am I a man?” but rather “will the inhabitants of this most intimate of all communities—the family—continue to value me even though I no longer have an economic role to play?”

5.

This is not to suggest that the question “Whom am I?” is not real, potent, and haunting. It undoubtedly is. In fact, I suspect it is stamped directly into the human genome. It is literally within our genetics and derives from our fundamental origins, from the long generations we and our predecessors spent on the African veldt. In the wild, membership in a supportive group, and knowing one’s place in it, can mean the difference between life and death. (The rugged individualist is romantic, but has no one to watch his back.)

So, as humans, we worry about identity. “Who am I?” is a genuinely important question, and we justifiably obsess over it. And when we have an “identity crisis,” it really is a crisis.

But what will posthumans do? How will they regard identity?

My guess is that they won’t regard it at all. They won’t think about it. After all, if “identity” is really another name for community interaction, then someone who is linked directly to the brains of other individuals never has to worry about how he or she fits into the group. Or, if the posthuman is, in fact, a collection of coupled bodies and brains, some near and some far, some organic and many not, then she/he will be a community. The individual and the mass will be the same thing.

And besides, if “identity” and “identity crisis” are built directly into the human genome, then transhumans/posthumans may not care to take that particular characteristic with them when they move to the next level of existence. Why bother? It reflects the needs of plains-dwelling creatures living in hunter-gathering bands, endlessly seeking meat and fruit, endlessly trying to avoid lions and tigers and bears (oh my). It may not meet any need possessed of a creature for whom the stars alone are a worthy goal.

I suspect that posthumans will simply abandon identity as a concept, as they will abandon shyness, depression, violent competition for mates, posturing for social position within the tribe, and all those other behaviors that had a role once, long ago, in the world of homo erectus and his many heirs, but not now.

Instead, the posthuman will, like God and Popeye, say “I am what I am,” (or in Popeye’s case, “I yam what I yam.”), and not give a damn about any theories to the contrary. They will simply exist, alone or in groups as they choose, confident and certain of their place in the universe, untroubled by any doubts about who they are.

Indeed, to the posthuman, our own concerns about such things, our asking “Who am I?” will seem at best inexplicable, and at worst frankly laughable.

6.

There is nothing uniquely wrong with being made laughable. To us, the sort of theological questions that are parodied as “how many angels can dance on the head of a pin?” are a joke. To us, they are the quintessential waste of time and talent. How, we wonder, could some of the most intelligent minds of history have obsessed over them?

Yet, obsess they did, and from their perspective the dancing angels were a serious problem upon which much else depended. If there were a finite number of angels on that pin, then God himself might be limited. The whole concept of omnipotence might be called into question. Perhaps, indeed, an intellectual historian might argue that it was with such questions that humanity began its long ascent to the secular.

And so it will be also with “identity” and “the identity crisis.” For our successors, these will seem as unworthy of attention. Scholars of pre-Singularity humanity will shake their (multi-brained) heads in wonder. How, they will ask, could we have cared so much about something that was so minor? Why did someone calling himself “Victor Storiguard” write an entire essay on the topic? Why did you read it? Why did a half drunken woman’s comments spark the essay in the first place?

So, perhaps, all that I’ve written here is meaningless. And my critic, the woman who rebuked me at the party for my multiplicity of names, is wholly irrelevant.

Yet, I will defend my critic, the woman who discovered tequila’s effects the hard way. I think she touched on something important. Specifically, she raised a question that should haunt us all:

If identity is in fact only an outgrowth of human origins, how many other things that we consider vitally important today will be revealed as merely the workings of ancient neural structures developed by ground-dwelling apes? How many of them shall not manage the transition to posthumanity? What will we lose?

And, more, what we will put in its place?

Victor Storiguard is a former trade press journalist who now teaches English, U.S. and World History, and Creative Writing. He lives in the Boston-area.

Space travel, particle physics, cosmology. These are just some of the endeavors humankind has embarked on, trying to understand the great mysteries of the universe. But why haven’t we been able to decipher those puzzles yet? Is it because they are vast and we are so small and insignificant? Well, yes.

In order to achieve these huge goals we need to change the very thing which is holding us back: Ourselves. Our mind has limits which we are only starting to be aware of and those limits are only made more restrictive by our fragile, sickened, mortal bodies.

How can we expect to learn the secrets of the world around us while trapped within a body which only lives for several decades, demands constant nourishment and attention, and dictates limits and desires beyond our control? This is why I think the first and foremost challenge we should “put our minds to” is mind uploading.

Once we have severed the link between our consciousness and the cruel joke someone has played on us by enclosing it in a mortal body, can we begin to really appreciate the beauty of the world around us. We would then be able to explore its secrets not just for a limited number of years, but for an eternity.

The first steps toward such a noble cause have already been taken in Switzerland. Scientists have already simulated a part of a rat’s brain with proven accuracy. It’s called the Blue Brain Project and it aims to use developing computer technologies in order to simulate an entire human brain and thus, hopefully, create a human personality which will be based on computer hardware rather than on the miserable excuse we have for a wetware body.

Just think of the possibilities! Eternal life. Easy and accessible space travel and colonization. Plenty of time for all human beings to grow and develop. Far less strain the planet’s limited resources. No more disease. No more suffering. No more death. A better understanding of the world around us, free of the constraints which currently bind us to a meager existence and a short life span.

No other research is this important, for this will be the base of our success as a species.

Nanotechnology is very intertwined with the future of all technology.  But can we disregard the potential dangers it might pose?

One hears about amazing research involving nano technology often in the news.  We seem to be tantalized with the just-around-the-corner proclamations of dramatic improvements in efficiency, the cure of Cancer and many other dramatic advancements.  Just to cite a few examples in recent news:

1. Nanotechnology Fabric Converts Heat To Power http://bit.ly/xjNTCC
2. Physicist Create A working Transistor From A Single Atom http://nyti.ms/yMABga
3. Nanotechnology Research Could Impact Flexible Electronic Devices http://bit.ly/xWovIe
4. Nanotechnology Shrinks Conducting Wires To Atomic Scales http://goo.gl/Ti929
5. Electronic CottonMeans Clothing Will Monitor Your Health http://goo.gl/UTk1m
6. Team Designers Bandage That Spurs, Guides Blood Vessels Growth http://goo.gl/0Mpw9
7. Silicon’s Possible Successors Include Carbon Nanotubes http://goo.gl/xRme3
8. DNA Nanotechnology Could Achieve A 100 Fold Cost Reduction To Start Breaking Through Cost Barrier http://goo.gl/omTJ8
9. Researcher Creep Closer To Bionic Eye http://goo.gl/Wx2eX
10. New Nano Product TO Treat Cancer Unveiled http://goo.gl/fIVlz

These are just a few of the news items that range in the hundreds.  The questions that arise are two.  When will this nano revolution arrive in full swing?  Can it be trusted not to harm living things?

The Promise of Nanotechnology

There is no question in our minds that nanotechnology holds the promise to advance just about every academic discipline dramatically forwards.  The ability to be able to reduce the size of machines, motors and other designed equipment to the level of nanometers and its impact on all other disciplines of science cannot be overestimated.  Like Kathleen Cook from DiscoverNano has summarized very well,

Nanotechnology research has transformed our fundamental knowledge of the material world. Such historic developments offer extraordinary promise in translation of basic knowledge into concrete applications. Such knowledge also offers opportunities for important discussion and thoughtful critical response to public health and safety issues.

So where is it?  When will all these promises arrive in our daily lives?  Will they just filter in?  Or is there some obstacle that must be overcome before nanotechnology can become a routine factor in our daily technology, yielding dramatic advancements?

The answer is not a simple one as one would expect.  Some areas in technology will be affected first.  Others will arrive at a latter date.  An example of some of the hype though can be demonstrated from an announcement cited in 2002 in Information Week.   This article stated that Samsung was about to come out with a 32′ inch flat screen computer monitor using nanotubes.  This promise has yet to be fulfilled.  And not surprisingly we find an article in Crave, titled Samsung launching carbon nanotube LCD TVs in 2011?  To our knowledge now such TVs have been produced yet.

Perhaps a good roadmap for the arrival of this technology was published by Scientific American in 2006 by Mihail Roco, titled Nanotechnology’s Future.  In it Roco states that by 2015, products incorporating nanotechnology will contribute $1 trillion dollars to the global economy.  He states that this will be the first of three phases in the incorporation of nanotechnology into the world economy.  This first stage he describes as mainly dealing with what he calles passive nanostructures,

…often used as parts of a product. These can be as modest as the particles of zinc oxide in sunscreens, but they can also be reinforcing fibers in new composites or carbon nanotube wires in ultraminiaturized electronics.

The second phase which began in 2005 along with the first involves “…nanostructures that change their shape, size and conductivity and other properties during use.”  Roco estimates that by 2010 “…workers will cultivate expertise with systems of nanostructures, directing large numbers of intricate components to specified ends.”

The third phase according to Roco will begin in 2015 and come to full realization by 2020.  He states that,

…the field will expand to include molecular nanosystems–heterogeneous networks in which molecules and supramolecular structures serve as distinct devices. The proteins inside cells work together this way, but whereas biological systems are water-based and markedly temperature-sensitive, these molecular nanosystems will be able to operate in a far wider range of environments and should be much faster. Computers and robots could be reduced to extraordinarily small sizes. Medical applications might be as ambitious as new types of genetic therapies and antiaging treatments. New interfaces linking people directly to electronics could change telecommunications.

The Perils of Nanotechnology

Among all the promises that nanotechnology offers, there are perils.  The peril is that no one really knows that the long term effects on the environment or on living things nano particles will have.  The headlines we gathered with just a cursory look reveal the concern:

1. Lab Raises Questions Over Nano-Particle Impact http://goo.gl/qI4qG
2. First Lawsuit On Risks Of Nanotechnology? http://goo.gl/XQxbO
3. How Healthy is Nanotechnology? http://goo.gl/i4NkY
4. Interactions of Nanomaterials With The Immune System http://goo.gl/NdwJp
5. Nanomaterial In Food Demands That Caution Be Used By Manufacturers  http://goo.gl/iXn6I
6. Study Indicated That Nanoparticles Cause Brain Damage In Fish http://goo.gl/sNdsL
7. Why Carbon Nanotubes Spell Trouble For Cells http://goo.gl/a3Ohg
8. The Dangers of Nanotech http://goo.gl/W6CYq
9. Government Fais To Assess Potential Dangers of Nanotechnology http://goo.gl/2hMBJ
10. What Are The Possible Dangers Of Nanotechnology? http://goo.gl/Lm0IE

We read this startling quote from a February 12, 2012 article,

Chronic and acute oral exposure to polystyrene nanoparticles can affect iron uptake and transport in a model of human intestinal lining cells cultured in the laboratory and in a live chicken intestinal model reports a paper this week in Nature Nanotechnology. The models created in this study may provide a low-cost and high-throughput screening tool for future nanoparticle toxicity research. Because of their unique physical and chemical properties, engineered nanoparticles are used in a variety of applications, including the food industry and for drug delivery. In addition, it has been estimated that the average person in a developed country consumes over a trillion man-made fine to ultrafine particles every day. Some features of nanoparticles may, however, lead to harmful interactions with cellular material, but no studies have yet addressed the chronic effects of nanoparticle exposure on the normal function of the intestinal lining, known as the epithelium.

This concern has been voiced before. In 2011, a lawsuit was filed by the International Center For Technology Assessment.  Part of lawsuit explained,

Since 2006, numerous studies and reports, including agency publications by the Environmental Protection Agency, the Office of the Inspector General, and the U.S. Government Accountability Office, acknowledge significant data gaps concerning nanomaterials’ potential effects on human health and the environment. Most troubling are studies using mice that show that nano-titanium dioxide when inhaled and when eaten can cause changes in DNA that affect the brain function and may cause tumors and developmental problems in offspring. One study found titanium dioxide nanoparticles were found in the placenta, fetal liver and fetal brain.

Carbon nanotubes which are now being spoken about in many circles as the first major possible breakthrough, especially in medicine poses, in their present pose a danger to living cells.

It’s been long known that asbestos spells trouble for human cells. Scientists have seen cells stabbed with spiky, long asbestos fibers, and the image is gory: Part of the fiber is protruding from the cell, like a quivering arrow that’s found its mark. But scientists had been unable to understand why cells would be interested in asbestos fibers and other materials at the nanoscale that are too long to be fully ingested. Now a group of researchers at Brown University explains what happens. Through molecular simulations and experiments, the team reports in Nature Nanotechnology that certain nanomaterials, such as carbon nanotubes, enter cells tip-first and almost always at a 90-degree angle. The orientation ends up fooling the cell; by taking in the rounded tip first, the cell mistakes the particle for a sphere, rather than a long cylinder. By the time the cell realizes the material is too long to be fully ingested, it’s too late.

This is not an insurmountable problem.  There are experiments being carried out, which by reshaping the nanotube, may remedy the problem.

But there are other issues at play here.  The way that nanoparticles behave are different from their larger counterparts.  This behavior eludes the up to now simple categories used to classify toxic materials.  Since unlike their larger relatives, they can easily cross the skin, lung and in some cases the blood and brain barriers, they present a far more complex problem that needs to be studied.  Some of these nanoparticles produce further biochemical reactions which can lead to the creation of free radicals that damage cells.

via: Nature Materialsclick to enlarge

The fact is that we are still not aware of the long term effects of nanoparticles in biological systems.  According to an article published in the July 2009 issue of  Nature Materials, titled, Understanding biophysciochemical interactions at the nano-bio interface, Nei et al., speak of the emergence of a “nano-bio interface,”

At the interface between nanomaterials and biological systems, the organic and synthetic worlds merge into a new science concerned with the safe use of nanotechnology and nano­
material design for biological applications. The ‘nano–bio’ inter­ face comprises the dynamic physicochemical interactions, kinetics and thermodynamic exchanges between nanomaterial surfaces and the surfaces of biological components (for example proteins, membranes, phospholipids, endocytic vesicles, organelles, DNA and biological fluids).

This is becoming a whole new world of reactions at the nano levels that where previously unknown, and do doubt, will become a whole new branch of science. This review cited in Nature Materials, highlighted four important research advancements as summarized by  eScience News.

1. A classification of the interactions when nanomaterials contact and bind to biological systems.
2. An understanding of how protein layers change the properties of the nanomaterials and the way in which they interact in the body.
3. An understanding of how physicochemical properties such as size, charge, shape and other characteristics affect the ability of nanomaterials to enter a cell.
4. An understanding of how nanoparticles elicit a wide range of intracellular responses, which depends on their properties, concentrations and interactions with biological molecules.

All of this shows just how much nanotechnology promises.  It shows how close we are in some areas to it reaching daily life.  This information also demonstrates the long road ahead in research, safety to us and our environment.  All of this information does not deter us from the belief that nanotechnology must come, that it will come and that we may not be ready for it.

This article was originally posted to PlusUltraTech: http://www.plusultratech.com/2012/03/nanotechnology-promise-and-peril.html

It’s interesting to consider virtual communities as social groups of great potential. The way they are formed is shaped by many things: technological infrastructure, platform or program design, but also by the actions of the members themselves. These actions are inevitably influenced by their real-world experiences. Each person within a virtual community possesses their own real-world social structures, cultural upbringing and personal preferences, and while they may even go on-line to “escape” from their real life, they are still shaped and conditioned by their life experiences in a certain way. In fact, the way that virtual communities are rooted in reality poses the question: Can we really consider virtual communities as a legitimate social phenomenon?

Joseph Lockard is an author who holds a slightly negative view on the matter, claiming that the term “Virtual community” itself is a confusing oxymoron, a muddled phrase that arises from material or “real” communities, and does not represent an entirely new or different mode of interaction. While I can agree with Lockard’s claim that some theorists often seem to reify virtual communities in order to give legitimacy to a certain kind of internet utopianism, it’s quite another thing to say that they don’t exist or don’t matter. The real importance of a virtual community lies in the fact that its members aren’t simply embodied in virtual space, but that they are embodied in real space at the same time. Every member of a virtual community is a contributor, and their contributions have the potential of affecting not only the virtual community, but the real lives of their co-members. While their actions in virtual space may be limited or moderated by the mechanisms of the technology they use, their impact in the real world is multiplied by the potential within the real virtual community, in the same way that an influential book does not hold its true value in paper or ink, but in its readership. We can think of many examples of this: bloggers, modders, gamers, pirates, artists, and many other on-line communities whose impact on the world isn’t simply in digital software, but in the real-world implications that their actions provoke, for better or for worse.

At the same time, it’s easy to get carried away into the same starry-eyed utopianism that was present at the dawn of the internet, thinking that the world-wide web has all the liberating potential we might ever need. In fact, the infatuation with contemporary social networks as tools of freedom or democracy is actually their biggest weakness, a fact that has led to the creation of terms such as “clicktivism”, a sarcastic critique of people whose only contribution to real political and social upheavals is in clicking the “like” button on Facebook or retweeting on Twitter. It would be too cynical of me to suggest that there are no benefits from social media in such cases, and we might yet witness a true “Facebook revolution”. However, expecting that such an event is inevitable simply due to the inherent “democratic potential” of the internet is a bit naíve. The question we should be asking ourselves is this: If the internet does not currently possess the needed potential for social and political emancipation, is that something we should attempt to change? Do we really need a central medium of social and political change? The answers to these questions are vitally important, but we may never reach a consensus on them in global terms. After all, neither radio nor television ever reached the inspiring moment of recognition that they should solely serve the public interest, but it is evident that they have the potential to do so, and there are historic examples in which they have done so.

The fallacy that some authors commit when discussing computer-generated virtuality is that they fail to take into account the role reality plays. While some may think this is a limitation of the liberating potential of virtual space, I prefer to think of it as a good way to keep our feet on the ground, and ensure that technological advancement remains beneficial, and not destructive. It’s quite easy to get carried away when it seems that we are peering over the horizon of technological discovery and seeing the first glimpses of a remarkable future, but it’s never a good idea to neglect our critical faculties and risk getting blind-sided by the negative consequences of our own innovations. I’m reminded of humdog’s essay titled Pandora’s Vox: on community in cyberspace. Humdog’s 1994. Critique of cyberspace as a system of control, consumerism and commodification of humanity is stunning, and almost prophetic in certain terms. However, while it’s easy to recognize the current trends of commercialization of certain areas of technological development, that doesn’t mean that the future is a foregone conclusion. We may be afraid of the future internet as the “great commodifier“, but we shouldn’t forget that its future is still in the hands of real people, and that virtual space will become dehumanizing only if reality does as well.

If there truly are ideological influences that are rooted in contemporary technological achievements, especially the ones that facilitate human interaction, we can only imagine that they will continue to grow, and that escaping from the limitations of a computer program is no easier than subverting the systems of social control in the real world. But this does not mean that the future holds the unescapable “orwellization“ of society. In fact, virtual reality may hold more opportunity as a collective medium than an individual one, and while there is nothing inherently transformative about technology in itself, there are vast opportunities presented for the ones who use it. The reflective nature of virtual communities of their real-world counterparts is what may insure that technological advancement is kept in step with the social innovations in the real world, and that our ambitions never outpace our capabilities. The real benefit of studying virtual reality is not just to figure out who we are inside the computer, but to discover who we are outside of it. Actions of virtual communities are a complex interplay between real social and cultural structures with technollogicaly generated environments, and it is through these interactions that we can discover more about both machine and man.

Borna Pleše is a sociologist and anthropologist, interested in various topics ranging from prehistoric to futuristic, and involved in studying virtual communities and new media. He currently lives in Zagreb, Croatia and can be reached atborna.plese[at]gmail.com

These questions have been explored extensively in science fiction.   But as technology advances during the next decades, they may transform from  theoretical and science-fictional issues into very urgent practical ones.   In this light, it’s worth noting that there is nothing near a consensus on such issues within the relevant science, engineering and intellectual communities.  Rather, there is a wild diversity of views, some of them strongly held.   And this is probably appropriate.  At this stage, when we still know so little about what advanced AGIs are going to be like, it’s worth entertaining a variety of perspectives, and trying to understand the issues as best we can.  This is the spirit in which the following dialogue is presented, in which the Singularity Institute’s Executive Director Luke Muehlhauser interviews AGI researcher (and Humanity+ Magazine Chief Editor, and Humanity+ Vice Chairman) Ben Goertzel on the nature and risks of AGI.

The Singularity Institute for AI (SIAI) is one contemporary institution with rather definitive and strongly held views on the risks of advanced AGI development.    Ben Goertzel has a long relationship with the Singularity Institute, much of which is detailed here, which has been marked by some serious intellectual and practical disagreements, along with a lot of commonality of interest and purpose. Put simply and roughly, the main area of disagreement between the two sides is as follows:

• SIAI tends toward the orientation that advanced AGIs are very likely to prove destructive to humans and human values, unless (via some currently-unknown theory, which is suspected to relate to Bayesian probability theory and decision theory) they can be very specifically designed not to do so
• Goertzel, while admitting that “unfriendly” AGIs antithetical to human values are a real possibility that’s hard to discount wholly, is more optimistic about the possibility of creating beneficial AGI systems via a combination of intelligent engineering and appropriate education

Luke’s interview with Ben digs into some of these disagreements in a fair bit of detail, along with a number of other AGI-related issues.  Much of the dialogue deals with somewhat technical issues regarding rationality and goals, as these notions are central to SIAI’s view of AGI — but by the end, the conversation converges on the topic of “AGI safety and risks” that lies at the heart of the SIAI and its perspective.   Also note: the interview was recently posted on the Less Wrong blog site, which is frequented by many fans of the SIAI’s views; you may be interested to go there and read the comments of the Less Wrong community on Luke’s and Ben’s ideas.

Luke Muehlhauser:

Ben, I’m glad you agreed to discuss artificial general intelligence (AGI) with me. There is much on which we agree, and much on which we disagree, so I think our dialogue will be informative to many readers, and to us!

Let us begin where we agree. We seem to agree that:

1. Involuntary death is bad, and can be avoided with the right technology.
2. Humans can be enhanced by merging with technology.
3. Humans are on a risky course in general, because powerful technologies can destroy us, humans are often stupid, and we are unlikely to voluntarily halt technological progress.
4. AGI is likely this century.
5. AGI will, after a slow or hard takeoff, completely transform the world. It is a potential existential risk, but if done wisely, could be the best thing that ever happens to us.
6. Careful effort will be required to ensure that AGI results in good things for humanity.

Next: Where do we disagree?

Two people might agree about the laws of thought most likely to give us an accurate model of the world, but disagree about which conclusions those laws of thought point us toward. For example, two scientists may use the same scientific method but offer two different models that seem to explain the data.

Or, two people might disagree about the laws of thought most likely to give us accurate models of the world. If that’s the case, it will be no surprise that we disagree about which conclusions to draw from the data. We are not shocked when scientists and theologians end up with different models of the world.

Unfortunately, I suspect you and I disagree at the more fundamental level — about which methods of reasoning to use when seeking an accurate model of the world.

I sometimes use the term “Technical Rationality“to name my methods of reasoning. Technical Rationality is drawn from two sources: (1) the laws of logic, probability theory, and decision theory, and (2) the cognitive science of how our haphazardly evolved brains fail to reason in accordance with the laws of logic, probability theory, and decision theory.

Ben, at one time you tweeted a William S. Burroughs quote: “Rational thought is a failed experiment and should be phased out.” I don’t know whether Burroughs meant by “rational thought” the specific thing I mean by “rational thought,” or what exactly you meant to express with your tweet, but I suspect we have different views of how to reason successfully about the world.

I think I would understand your way of thinking about AGI better if I understand your way of thinking about everything . For example: do you have reason to reject the laws of logic, probability theory, and decision theory? Do you think we disagree about the basic findings of the cognitive science of humans? What are your positive recommendations for reasoning about the world?

Ben Goertzel:

Firstly, I don’t agree with that Burroughs quote that “Rational thought is a failed experiment” — I mostly just tweeted it because I thought it was funny! I’m not sure Burroughs agreed with his own quote either. He also liked to say that linguistic communication was a failed experiment, introduced by women to help them oppress men into social conformity. Yet he was a writer and loved language. He enjoyed being a provocateur.

However, I do think that some people overestimate the power and scope of rational thought. That is the truth at the core of Burroughs’ entertaining hyperbolic statement….

I should clarify that I’m a huge fan of logic, reason and science. Compared to the average human being, I’m practically obsessed with these things! I don’t care for superstition, nor for unthinking acceptance of what one is told; and I spent a lot of time staring at data of various sorts, trying to understand the underlying reality in a rational and scientific way. So I don’t want to be pigeonholed as some sort of anti-rationalist!

However, I do have serious doubts both about the power and scope of rational thought in general — and much more profoundly, about the power and scope of what you call “technical rationality.”

First of all, about the limitations of rational thought broadly conceived — what one might call “semi-formal rationality”, as opposed to “technical rationality.” Obviously this sort of rationality has brought us amazing things, like science and mathematics and technology.  Hopefully it will allow us to defeat involuntary death and increase our IQs by orders of magnitude and discover new universes, and all sorts of great stuff. However, it does seem to have its limits.

It doesn’t deal well with consciousness — studying consciousness using traditional scientific and rational tools has just led to a mess of confusion. It doesn’t deal well with ethics either, as the current big mess regarding bioethics indicates.

And this is more speculative, but I tend to think it doesn’t deal that well with the spectrum of “anomalous phenomena” — precognition, extrasensory perception, remote viewing, and so forth. I strongly suspect these phenomena exist, and that they can be understood to a significant extent via science — but also that science as presently constituted may not be able to grasp them fully, due to issues like the mindset of the experimenter helping mold the results of the experiment.

There’s the minor issue of Hume’s problem of induction, as well. I.e., the issue that, in the rational and scientific world-view, that we have no rational reason to believe that any patterns observed in the past will continue into the future. This is an ASSUMPTION, plain and simple — an act of faith. Occam’s Razor (which is one way of justifying and/or further specifying the belief that patterns observed in the past will continue into the future) is also an assumption and an act of faith. Science and reason rely on such acts of faith, yet provide no way to justify them. A big gap.

Furthermore — and more to the point about AI — I think there’s a limitation to the way we now model intelligence, which ties in with the limitations of the current scientific and rational approach. I have always advocated a view of intelligence as “achieving complex goals in complex environments”, and many others have formulated and advocated similar views. The basic idea here is that, for a system to be intelligent it doesn’t matter WHAT its goal is, so long as its goal is complex and it manages to achieve it. So the goal might be, say, reshaping every molecule in the universe into an image of Mickey Mouse.

This way of thinking about intelligence, in which the goal is strictly separated from the methods for achieving it, is very useful and I’m using it to guide my own practical AGI work.

On the other hand, there’s also a sense in which reshaping every molecule in the universe into an image of Mickey Mouse is a STUPID goal. It’s somehow out of harmony with the Cosmos — at least that’s my intuitive feeling. I’d like to interpret intelligence in some way that accounts for the intuitively apparent differential stupidity of different goals. In other words, I’d like to be able to deal more sensibly with the interaction of scientific and normative knowledge.

This ties in with the incapacity of science and reason in their current forms to deal with ethics effectively, which I mentioned a moment ago.

I certainly don’t have all the answers here — I’m just pointing out the complex of interconnected reasons why I think contemporary science and rationality are limited in power and scope, and are going to be replaced by something richer and better as the growth of our individual and collective minds progresses. What will this new, better thing be? I’m not sure — but I have an inkling it will involve an integration of “third person” science/rationality with some sort of systematic approach to first-person and second-person experience.

Next, about “technical rationality” — of course that’s a whole other can of worms. Semi-formal rationality has a great track record; it’s brought us science and math and technology, for example. So even if it has some limitations, we certainly owe it some respect! Technical rationality has no such track record, and so my semi-formal scientific and rational nature impels me to be highly skeptical of it! I have no reason to believe, at present, that focusing on technical rationality (as opposed to the many other ways to focus our attention, given our limited time and processing power) will generally make people more intelligent or better at achieving their goals. Maybe it will, in some contexts — but what those contexts are, is something we don’t yet understand very well.

I provided consulting once to a project aimed at using computational neuroscience to understand the neurobiological causes of cognitive biases in people employed to analyze certain sorts of data. This is interesting to me; and it’s clear to me that in this context, minimization of some of these textbook cognitive biases would help these analysts to do their jobs better. I’m not sure how big an effect the reduction of these biases would have on their effectiveness, though, relative to other changes one might make, such as changes to their workplace culture or communication style.

On a mathematical basis, the justification for positing probability theory as the “correct” way to do reasoning under uncertainty relies on arguments like Cox’s axioms, or de Finetti’s Dutch Book arguments.  These are beautiful pieces of math, but when you talk about applying them to the real world, you run into a lot of problems regarding the inapplicability of their assumptions. For instance, Cox’s axioms include an axiom specifying that (roughly speaking) multiple pathways of arriving at the same conclusion must lead to the same estimate of that conclusion’s truth value. This sounds sensible but in practice it’s only going to be achievable by minds with arbitrarily much computing capability at their disposal. In short, the assumptions underlying Cox’s axioms, de Finetti’s arguments, or any of the other arguments in favor of probability theory as the correct way of reasoning under uncertainty, do NOT apply to real-world intelligences operating under strictly bounded computational resources. They’re irrelevant to reality, except as inspirations to individuals of a certain cast of mind.

(An aside is that my own approach to AGI does heavily involve probability theory — using a system I invented called Probabilistic Logic Networks, which integrates probability and logic in a unique way.  I like probabilistic reasoning. I just don’t venerate it as uniquely powerful and important. In my OpenCog AGI architecture, it’s integrated with a bunch of other AI methods, which all have their own strengths and weaknesses.)

So anyway — there’s no formal mathematical reason to think that “technical rationality” is a good approach in real-world situations; and “technical rationality” has no practical track record to speak of.  And ordinary, semi-formal rationality itself seems to have some serious limitations of power and scope.

So what’s my conclusion? Semi-formal rationality is fantastic and important and we should use it and develop it — but also be open to the possibility of its obsolescence as we discover broader and more incisive ways of understanding the universe (and this is probably moderately close to what William Burroughs really thought). Technical rationality is interesting and well worth exploring but we should still be pretty skeptical of its value, at this stage — certainly, anyone who has supreme confidence that technical rationality is going to help humanity achieve its goals better, is being rather IRRATIONAL ….

In this vein, I’ve followed the emergence of the Less Wrong community with some amusement and interest. One ironic thing I’ve noticed about this community of people intensely concerned with improving their personal rationality is: by and large, these people are already hyper-developed in the area of rationality, but underdeveloped in other ways! Think about it — who is the prototypical Less Wrong meetup participant? It’s a person who’s very rational already, relative to nearly all other humans — but relatively lacking in other skills like intuitively and empathically understanding other people. But instead of focusing on improving their empathy and social intuition (things they really aren’t good at, relative to most humans), this person is focusing on fine-tuning their rationality more and more, via reprogramming their brains to more naturally use “technical rationality” tools! This seems a bit imbalanced. If you’re already a fairly rational person but lacking in other aspects of human development, the most rational thing may be NOT to focus on honing your “rationality fu” and better internalizing Bayes’ rule into your subconscious — but rather on developing those other aspects of your being…. An analogy would be: If you’re very physically strong but can’t read well, and want to self-improve, what should you focus your time on? Weight-lifting or literacy? Even if greater strength is ultimately your main goal, one argument for focusing on literacy would be that you might read something that would eventually help you weight-lift better! Also you might avoid getting ripped off by a corrupt agent offering to help you with your bodybuilding career, due to being able to read your own legal contracts. Similarly, for people who are more developed in terms of rational inference than other aspects, the best way for them to become more rational might be for them to focus time on these other aspects (rather than on fine-tuning their rationality), because this may give them a deeper and broader perspective on rationality and what it really means.

Finally, you asked: “What are your positive recommendations for reasoning about the world?” I’m tempted to quote Nietzsche’s Zarathustra, who said “Go away from me and resist Zarathustra!” I tend to follow my own path, and generally encourage others to do the same.  But I guess I can say a few more definite things beyond that….

To me it’s all about balance. My friend Allan Combs calls himself a “philosophical Taoist” sometimes; I like that line! Think for yourself; but also, try to genuinely listen to what others have to say. Reason incisively and analytically; but also be willing to listen to your heart, gut and intuition, even if the logical reasons for their promptings aren’t apparent. Think carefully through the details of things; but don’t be afraid to make wild intuitive leaps. Pay close mind to the relevant data and observe the world closely and particularly; but don’t forget that empirical data is in a sense a product of the mind, and facts only have meaning in some theoretical context. Don’t let your thoughts be clouded by your emotions; but don’t be a feeling-less automaton, don’t make judgments that are narrowly rational but fundamentally unwise. As Ben Franklin said, “Moderation in all things, including moderation.”

Luke:

I whole-heartedly agree that there are plenty of Less Wrongers who, rationally, should spend less time studying rationality and more time practicing social skills and generic self-improvement methods! This is part of why I’ve written so many scientific self-help posts for Less Wrong: Scientific Self Help, How to Beat Procrastination, How to Be Happy, Rational Romantic Relationships, and others. It’s also why I taught social skills classes at our two summer 2011 rationality camps.

Back to rationality. You talk about the “limitations” of “what one might call ‘semi-formal rationality’, as opposed to ‘technical rationality.’” But I argued for technical rationality, so: what are the limitations of technical rationality? Does it, as you claim for “semi-formal rationality,” fail to apply to consciousness or ethics or precognition? Does Bayes’ Theorem remain true when looking at the evidence about awareness, but cease to be true when we look at the evidence concerning consciousness or precognition?

You talk about technical rationality’s lack of a track record, but I don’t know what you mean. Science was successful because it did a much better job of approximating perfect Bayesian probability theory than earlier methods did (e.g. faith, tradition), and science can be even more successful when it tries harder to approximate perfect Bayesian probability theory — see The Theory That Would Not Die.

You say that “minimization of some of these textbook cognitive biases would help [some] analysts to do their jobs better. I’m not sure how big an effect the reduction of these biases would have on their effectiveness, though, relative to other changes one might make, such as changes to their workplace culture or communication style.” But this misunderstands what I mean by Technical Rationality.  If teaching these people about cognitive biases would lower the expected value of some project, then technical rationality would recommend against teaching these people cognitive biases (at least, for the purposes of maximizing the expected value of that project). Your example here is a case of Straw Man Rationality.  (But of course I didn’t expect you to know everything I meant by Technical Rationality in advance! Though, I did provide a link to an explanation of what I meant by Technical Rationality in my first entry, above.)

The same goes for your dismissal of probability theory’s foundations. You write that “In short, the assumptions underlying Cox’s axioms, de Finetti’s arguments, or any of the other arguments in favor of probability theory as the correct way of reasoning under uncertainty, do NOT apply to real-world intelligences operating under strictly bounded computational resources.” Yes, we don’t have infinite computing power. The point is that Bayesian probability theory is an ideal that can be approximated by finite beings. That’s why science works better than faith — it’s a better approximation of using probability theory to reason about the world, even though science is
still  long way from a perfect use of probability theory.

Re: goals. Your view of intelligence as “achieving complex goals in complex environments” does, as you say, assume that “the goal is strictly separated from the methods for achieving it.” I prefer a definition of intelligence as ” efficient cross-domain optimization,” but my view — like yours — also assumes that goals (what one values) are logically orthogonal to intelligence (one’s ability to achieve what one values).

Nevertheless, you report an intuition that shaping every molecule into an image of Mickey Mouse is a “stupid” goal. But I don’t know what you mean by this. A goal of shaping every molecule into an image of Mickey Mouse is an instrumentally intelligent goal if one’s utility function will be maximized that way. Do you mean that it’s a stupid goal according to your goals? But of course. This is, moreover, what we would expect your intuitive judgments to report, even if your intuitive judgments are irrelevant to the math of what would and wouldn’t be an instrumentally intelligent goal for a different agent to have. The Mickey Mouse goal is “stupid” only by a definition of that term that is not the opposite of the explicit definitions either of us gave “intelligent,” and it’s important to keep that clear. And I certainly don’t know what “out of harmony with the Cosmos” is supposed to mean.

Re: induction. I won’t dive into that philosophical morass here.  Suffice it to say that my views on the matter are expressed pretty well in Where Recursive Justification Hits Bottom, which is also a direct response to your view that science and reason are great but rely on “acts of faith.”

Your final paragraph sounds like common sense, but it’s too vague, as I think you would agree. One way to force a more precise answer to such questions is to think of how you’d program it into an AI. As Daniel Dennett said, “AI makes philosophy honest.”

How would you program an AI to learn about reality, if you wanted it to have the most accurate model of reality possible? You’d have to be a bit more specific than “Think for yourself; but also, try to genuinely listen to what others have to say. Reason incisively and analytically; but also be willing to listen to your heart, gut and intuition…”

My own answer to the question of how I would program an AI to build as accurate a model of reality as possible is this: I would build it to use computable approximations of perfect technical rationality — that is, roughly: computable approximations of Solomonoff induction and Bayesian decision theory.

Ben:

Bayes Theorem is “always true” in a formal sense, just like 1+1=2, obviously. However, the connection between formal mathematics and subjective experience, is not something that can be fully formalized.

Regarding consciousness, there are many questions, including what counts as “evidence.” In science we typically count something as evidence if the vast majority of the scientific community counts it as a real observation — so ultimately the definition of “evidence” bottoms out in social agreement. But there’s a lot that’s unclear in this process of classifying an observation as evidence via a process of social agreement among multiple minds. This unclarity is mostly irrelevant to the study of trajectories of basketballs, but possibly quite relevant to study of consciousness.

Regarding psi, there are lots of questions, but one big problem is that it’s possible the presence and properties of a psi effect may depend on the broad context of the situation whether the effect takes
place. Since we don’t know which aspects of the context are influencing the psi effect, we don’t know how to construct controlled experiments to measure psi. And we may not have the breadth of knowledge nor the processing power to reason about all the relevant context to a psi experiment, in a narrowly “technically rational” way…. I do suspect one can gather solid data demonstrating and exploring psi (and based on my current understanding, it seems this has already been done to a significant extent by the academic parapsychology community; see a few links I’ve gathered here), but I also suspect there many be aspects that elude the traditional scientific method, but are nonetheless perfectly real aspects of the universe.

Anyway both consciousness and psi are big, deep topics, and if we dig into them in detail, this interview will become longer than either of us has time for…

About the success of science — I don’t really accept your Bayesian story for why science was successful. It’s naive for reasons much discussed by philosophers of science. My own take on the history and philosophy of science, from a few years back, is here (that article was the basis for a chapter in The Hidden Pattern , also). My goal in that essay was “a philosophical perspective that does justice to both the relativism and sociological embeddedness of science, and the objectivity and rationality of science.” It seems you focus overly much on the latter and ignore the former. That article tries to explain why probabilist explanations of real-world science are quite partial and miss a lot of the real story. But again, a long debate on the history of science would take us too far off track from the main thrust of this interview.

About technical rationality, cognitive biases, etc. — I did read that blog entry that you linked, on technical rationality. Yes, it’s obvious that focusing on teaching an employee to be more rational, need not always be the most rational thing for an employer do, even if that employer has a purely rationalist world-view. For instance, if I want to train an attack dog, I may do better by focusing limited time and attention on increasing his strength rather than his rationality. My point was that there’s a kind of obsession with rationality in some parts of the intellectual community (e.g. some of the Less Wrong orbit) that I find a bit excessive and not always productive. But your reply impels me to distinguish two ways this excess may manifest itself:

1. Excessive belief that rationality is the “right” way to solve problems and think about issues, in principle
2. Excessive belief that, tactically, explicitly employing tools of technical rationality is a good way to solve problems in the real world

Psychologically I think these two excesses probably tend to go together, but they’re not logically coupled. In principle, someone could hold either one, but not the other.

This sort of ties in with your comments on science and faith. You view science as progress over faith — and I agree if you interpret “faith” to mean “traditional religions.” But if you interpret “faith” more broadly, I don’t see a dichotomy there. Actually, I find the dichotomy between “science” and “faith” unfortunately phrased, since science itself ultimately relies on acts of faith also. The “problem of induction” can’t be solved, so every scientist must base his extrapolations from past into future based on some act of faith. It’s not a matter of science vs. faith, it’s a matter of what one chooses to place one’s faith in. I’d personally rather place faith in the idea that patterns observed in the past will likely continue into the future (as one example of a science-friendly article of faith), than in the word of some supposed “God” — but I realize I’m still making an act of faith.

This ties in with the blog post “Where Recursive Justification Hits Bottom” that you pointed out. It’s pleasant reading but of course doesn’t provide any kind of rational argument against my views. In brief, according to my interpretation, it articulates a faith in the process of endless questioning:

The important thing is to hold nothing back in your criticisms of how to criticize; nor should you regard the unavoidability of loopy justifications as a warrant of immunity from questioning .

I share that faith, personally.

Regarding approximations to probabilistic reasoning under realistic conditions (of insufficient resources), the problem is that we lack rigorous knowledge about what they are. We don’t have any theorems telling us what is the best way to reason about uncertain knowledge, in the case that our computational resources are extremely restricted. You seem to be assuming that the best way is to explicitly use the rules of probability theory, but my point is that there is no mathematical or scientific foundation for this belief. You are making an act of faith in the doctrine of probability theory! You are assuming, because it feels intuitively and emotionally right to you, that even if the conditions of the arguments for the correctness of probabilistic reasoning are NOT met, then it still makes sense to use probability theory to reason about the world. But so far as I can tell, you don’t have a RATIONAL reason for this assumption, and certainly not a mathematical reason.

Re your response to my questioning the reduction of intelligence to goals and optimization — I understand that you are intellectually committed to the perspective of intelligence in terms of optimization or goal-achievement or something similar to that. Your response to my doubts about this perspective basically just re-asserts your faith in the correctness and completeness of this sort of perspective. Your statement

The Mickey Mouse goal is “stupid” only by a definition of that term that is not the opposite of the explicit definitions either of us gave “intelligent,” and it’s important to keep that clear

basically asserts that it’s important to agree with your opinion on the ultimate meaning of intelligence!

On the contrary, I think it’s important to explore alternatives to the understanding of intelligence in terms of optimization or goal-achievement. That is something I’ve been thinking about a lot lately. However, I don’t have a really crisply-formulated alternative yet.

As a mathematician, I tend not to think there’s a “right” definition for anything. Rather, one explains one’s definitions, and then works with them and figures out their consequences. In my AI work, I’ve provisionally adopted a goal-achievemement based understanding of intelligence — and have found this useful, to a significant extent.  But I don’t think this is the true and ultimate way to understand intelligence. I think the view of intelligence in terms of goal-achievement or cross-domain optimization misses something, which future understandings of intelligence will encompass. I’ll venture that in 100 years the smartest beings on Earth will have a rigorous, detailed understanding of intelligence according to which your statement

The Mickey Mouse goal is “stupid” only by a definition of that term that is not the opposite of the explicit definitions either of us gave “intelligent,” and it’s important to keep that clear

seems like rubbish…..

As for your professed inability to comprehend the notion of “harmony with the Cosmos” — that’s unfortunate for you, but I guess trying to give you a sense for that notion, would take us way too far afield in this dialogue!

Finally, regarding your complaint that my indications regarding how to understanding the world are overly vague. Well — according to Ben Franklin’s idea of “Moderation in all things, including moderation”, one should also exercise moderation in precisiation. Not everything needs to be made completely precise and unambiguous (fortunately, since that’s not feasible anyway).

I don’t know how I would program an AI to build as accurate a model of reality as possible, if that were my goal. I’m not sure that’s the best goal for AI development, either. An accurate model in itself,
doesn’t do anything helpful. My best stab in the direction of how I would ideally create an AI, if computational resource restrictions were no issue, is the GOLEM design that I described here. GOLEM is a design for a strongly self-modifying superintelligent AI system, which might plausibly have the possibility of retaining its initial goal system through successive self-modifications. However, it’s unclear to me whether it will ever be feasible to build.

You mention Solomonoff induction and Bayesian decision theory. But these are abstract mathematical constructs, and it’s unclear to me whether it will ever be feasible to build an AI system fundamentally founded on these ideas, and operating within feasible computational resources. Marcus Hutter and Juergen Schmidhuber and their students are making some efforts in this direction, and I admire those researchers and this body of work, but don’t currently have a high estimate of its odds of leading to any sort of powerful real-world AGI system.

Most of my thinking about AGI has gone into the more practical problem of how to make a human-level AGI

1. using currently feasible computational resources
2. that will most likely be helpful rather than harmful in terms of the things I value
3. that will be smoothly extensible to intelligence beyond the human level as well.

For this purpose, I think Solomonoff induction and probability theory are useful, but aren’t all-powerful guiding principles. For instance, in the OpenCog AGI design (which is my main practical AGI-oriented venture at present), there is a component doing automated program learning of small programs — and inside our program learning algorithm, we explicitly use an Occam bias, motivated by the theory of Solomonoff induction. And OpenCog also has a probabilistic reasoning engine, based on the math of Probabilistic Logic Networks (PLN). I don’t tend to favor the language of “Bayesianism”, but I would suppose PLN should be considered “Bayesian” since it uses probability theory (including Bayes rule) and doesn’t make a lot of arbitrary, a priori distributional assumptions.
The truth value formulas inside PLN are based on an extension of imprecise probability theory, which in itself is an extension of standard Bayesian methods (looking at envelopes of prior distributions, rather than assuming specific priors).

In terms of how to get an OpenCog system to model the world effectively and choose its actions appropriately, I think teaching it and working together with it, will be be just as important as programming it. Right now the project is early-stage and the OpenCog design is maybe 50% implemented. But assuming the design is right, once the implementation is done, we’ll have a sort of idiot savant childlike mind, that will need to be educated in the ways of the world and humanity, and to learn about itself as well. So the general lessons of how to confront the world, that I cited above, would largely be imparted via interactive experiential learning, vaguely the same way that human kids learn to confront the world from their parents and teachers.

Drawing a few threads from this conversation together, it seems that

1. I think technical rationality, and informal semi-rationality, are both useful tools for confronting life — but not all-powerful
2. I think Solomonoff induction and probability theory are both useful tools for constructing AGI systems — but not all-powerful

whereas you seem to ascribe a more fundamental, foundational basis to these particular tools.

Luke:

To sum up, from my point of view:

1. We seem to disagree on the applications of probability theory. For my part, I’ll just point people to A Technical Explanation of Technical Explanation.
2. I don’t think we disagree much on the “sociological embeddedness” of science.
3. I’m also not sure how much we really disagree about Solomonoff induction and Bayesian probability theory. I’ve already agreed that no machine will use these in practice because they are not computable — my point was about their provable optimality given infinite computation(subject to qualifications; see AIXI).

You’ve definitely misunderstood me concerning “intelligence.” This part is definitely not true: “I understand that you are intellectually committed to the perspective of intelligence in terms of optimization or goal-achievement or something similar to that. Your response assumes the correctness and completeness of this sort of perspective.”  Intelligence as efficient cross-domain optimization is merely a stipulated definition. I’m happy to use other definitions of intelligence in conversation, so long as we’re clear which definition we’re using when we use the word. Or, we can replace the symbol with the substance and talk about “efficient cross-domain optimization” or “achieving complex goals in complex environments” without ever using the word “intelligence.”

My point about the Mickey Mouse goal was that when you called the Mickey Mouse goal “stupid,” this could be confusing, because “stupid” is usually the opposite of “intelligent,” but your use of “stupid” in that sentence didn’t seem to be the opposite of either definition of intelligence we each gave. So I’m still unsure what you mean by calling the Mickey Mouse goal “stupid.”

This topic provides us with a handy transition away from philosophy of science and toward AGI. Suppose there was a machine with a vastly greater-than-human capacity for either “achieving complex goals in complex environments” or for “efficient cross-domain optimization.” And suppose that machine’s utility function would be maximized by reshaping every molecule into a Mickey Mouse shape. We can avoid the tricky word “stupid,” here. The question is: Would that machine decide to change its utility function so that it doesn’t continue to reshape every molecule into a Mickey Mouse shape? I think this is unlikely, for reasons discussed in Omohundro (2008).

I suppose a natural topic of conversation for us would be your October 2010 blog post The Singularity Institute’s's Scary Idea (and Why I Don’t Buy It). Does that post still reflect your views pretty well, Ben?

Ben:

About the hypothetical uber-intelligence that wants to tile the cosmos with molecular Mickey Mouses — I truly don’t feel confident making any assertions about a real-world system with vastly greater intelligence than me. There are just too many unknowns. Sure, according to certain models of the universe and intelligence that may seem sensible to some humans, it’s possible to argue that a hypothetical uber-intelligence like that would relentlessly proceed in tiling the cosmos with molecular Mickey Mouses. But so what? We don’t even know that such an uber-intelligence is even a possible thing — in fact my intuition is that it’s not possible.

Why may it not be possible to create a very smart AI system that is strictly obsessed with that stupid goal? Consider first that it may not be possible to create a real-world, highly intelligent system that is
strictly driven by explicit goals — as opposed to being partially driven by implicit, “unconscious” (in the sense of deliberative, reflective consciousness) processes that operate in complex interaction with the world outside the system. Because pursuing explicit goals is quite computationally costly compared to many other sorts of intelligent processes. So if a real-world system is necessarily not wholly explicit-goal-driven, it may be that intelligent real-world systems will naturally drift away from certain goals and toward others.  My strong intuition is that the goal of tiling the universe with molecular Mickey Mouses would fall into that category. However, I don’t yet have any rigorous argument to back this up. Unfortunately my time is limited, and while I generally have more fun theorizing and philosophizing than working on practical projects, I think it’s more important for me to push toward building AGI than just spend all my time on fun theory. (And then there’s the fact that I have to spend a lot of my time on applied narrow-AI projects to pay the mortgage and put my kids through college, etc.)

And SIAI has staff who, unlike me, are paid full-time to write and philosophize … and they haven’t come up with a rigorous argument in favor of the possibility of such a system, either. Although they have talked about it a lot, though usually in the context of paperclips rather than Mickey Mouses.

So, I’m not really sure how much value there is in this sort of thought-experiment about pathological AI systems that combine massively intelligent practical problem solving capability with incredibly stupid goals (goals that may not even be feasible for real-world superintelligences to adopt, due to their stupidity).

Regarding the concept of a “stupid goal” that I keep using, and that you question — I admit I’m not quite sure how to formulate rigorously the idea that tiling the universe with Mickey Mouses is a stupid goal. This is something I’ve been thinking about a lot recently. But here’s a first rough stab in that direction: I think that if you created a highly inteligent system, allowed it to interact fairly flexibly with the universe, and also allowed it to modify its top-level goals in accordance with its experience, you’d be very unlikely to wind up with a system that had this goal (tiling the universe with Mickey Mouses). That goal is out of sync with the Cosmos, in the sense that an intelligent system that’s allowed to evolve itself in close coordination with the rest of the universe, is very unlikely to arrive at that goal system. I don’t claim this is a precise definition, but it should give you some indication of the direction I’m thinking in….

The tricky thing about this way of thinking about intelligence, which classifies some goals as “innately” stupider than others, is that it places intelligence not just in the system, but in the system’s broad relationship to the universe — which is something that science, so far, has had a tougher time dealing with. It’s unclear to me which aspects of the mind and universe science, as we now conceive it, will be able to figure out. I look forward to understanding these aspects more fully….

About my blog post on “The Singularity Institute’s Scary Idea” — yes, that still reflects my basic opinion. After I wrote that blog post, Michael Anissimov — a long-time SIAI staffer and zealot whom I like and respect greatly — told me he was going to write up and show me a systematic, rigorous argument as to why “an AGI not built based on a rigorous theory of Friendliness is almost certain to kill all humans” (the proposition I called “SIAI’s Scary Idea”). But he hasn’t followed through on that yet — and neither has Eliezer or anyone associated with SIAI.

Just to be clear, I don’t really mind that SIAI folks hold that “Scary Idea” as an intuition. But I find it rather ironic when people make a great noise about their dedication to rationality, but then also make huge grand important statements about the future of humanity, with great confidence and oomph, that are not really backed up by any rational argumentation. This ironic behavior on the part of Eliezer, Michael Anissimov and other SIAI principals doesn’t really bother me, as I like and respect them and they are friendly to me, and we’ve simply “agreed to disagree” on these matters for the time being. But the reason I wrote that blog post is because my own blog posts about AGI were being trolled by SIAI zealots (not the principals, I hasten to note) leaving nasty comments to the effect of “SIAI has proved that if OpenCog achieves human level AGI, it will kill all humans.“ Not only has SIAI not proved any such thing, they have not even made a clear rational argument!

As Eliezer has pointed out to me several times in conversation, a clear rational argument doesn’t have to be mathematical. A clearly formulated argument in the manner of analytical philosophy, in favor of the Scary Idea, would certainly be very interesting. For example, philosopher David Chalmers recently wrote a carefully-argued philosophy paper arguing for the plausibility of a Singularity in the next couple hundred years. It’s somewhat dull reading, but it’s precise and rigorous in the manner of analytical philosophy, in a manner that Kurzweil’s writing (which is excellent in its own way) is not. An argument in favor of the Scary Idea, on the level of Chalmers’ paper on the Singularity, would be an excellent product for SIAI to produce. Of course a mathematical argument might be even better, but that may not be feasible to work on right now, given the state of mathematics today. And of course, mathematics can’t do everything — there’s still the matter of connecting mathematics to everyday human experience, which analytical philosophy tries to handle, and mathematics by nature cannot.

My own suspicion, of course, is that in the process of trying to make a truly rigorous analytical philosophy style formulation of the argument for the Scary Idea, the SIAI folks will find huge holes in the argument. Or, maybe they already intuitively know the holes are there, which is why they have avoided presenting a rigorous write-up of the argument!!

Luke:

I’ll drop the stuff about Mickey Mouse so we can move on to AGI. Readers can come to their own conclusions on that.

Your main complaint seems to be that the Singularity Institute hasn’t written up a clear, formal argument (in analytic philosophy’s sense, if not the mathematical sense) in defense of our major positions — something like Chalmers’ ” The Singularity: A Philosophical Analysis” but more detailed.

I have the same complaint. I wish “The Singularity: A Philosophical Analysis” had been written 10 years ago, by Nick Bostrom and Eliezer Yudkowsky. It *could* have been written back then. Alas, we had to wait for Chalmers to speak at Singularity Summit 2009 and then write a paper based on his talk. And if it wasn’t for Chalmers, I fear we’d still be waiting for such an article to exist. (Bostrom’s forthcoming Superintelligence book should be good, though.)

I was hired by the Singularity Institute in September 2011 and have since then co-written two papers explaining some of the basics: ” Intelligence Explosion: Evidence and Import” and ” The Singularity and Machine Ethics.” I also wrote the first ever outline of categories of open research problems in AI risk, cheekily titled ” So You Want to Save the World.” I’m developing other articles on “the basics” as quickly as I can. I would love to write more, but alas, I’m also busy being the Singularity Institute’s Executive Director.

Perhaps we could reframe our discussion around the Singularity Institute’s latest exposition of its basic ideas, “Intelligence Explosion: Evidence and Import”? Which claims in that paper do you most confidently disagree with, and why?

Ben:

You say “Your main complaint seems to be that the Singularity Institute hasn’t written up a clear, formal argument (in analytic philosophy’s sense, if not the mathematical sense) in defense of our major positions “. Actually, my main complaint is that some of SIAI’s core positions seem almost certainly WRONG, and yet they haven’t written up a clear formal argument trying to justify these positions — so it’s not possible to engage SIAI in rational discussion on their apparently wrong positions. Rather, when I try to engage SIAI folks about these wrong-looking positions (e.g. the “Scary Idea” I mentioned above), they tend to point me to Eliezer’s blog (“Less Wrong”) and tell me that if I studied it long and hard enough, I would find that the arguments in favor of SIAI’s positions are implicit there, just not clearly articulated in any one place. This is a bit frustrating to me — SIAI is a fairly well-funded organization involving lots of smart people and explicitly devoted to rationality, so certainly it should have the capability to write up clear arguments for its core positions… if these arguments exist. My suspicion is that the Scary Idea, for example, is not backed up by any clear rational argument — so the reason SIAI has not put forth any clear rational argument for it, is that they don’t really have one! Whereas Chalmers’ paper carefully formulated something that seemed obviously true…

Regarding the paper “Intelligence Explosion: Evidence and Import”, I find its contents mainly agreeable — and also somewhat unoriginal and unexciting, given the general context of 2012 Singularitarianism. The paper’s three core claims that

(1) there is a substantial chance we will create human-level AI before 2100, that (2) if human-level AI is created, there is a good chance vastly superhuman AI will follow via an “intelligence explosion,” and that (3) an uncontrolled intelligence explosion could destroy everything we value, but a controlled intelligence explosion would benefit humanity enormously if we can achieve it.

are things that most “Singularitarians” would agree with. The paper doesn’t attempt to argue for the “Scary Idea” or Coherent Extrapolated Volition or the viability of creating some sort of provably Friendly AI, — or any of the other positions that are specifically characteristic of SIAI. Rather, the paper advocates what one might call “plain vanilla Singularitarianism.” This may be a useful thing to do, though, since after all there are a lot of smart people out there who aren’t convinced of plain vanilla Singularitarianism.

I have a couple small quibbles with the paper, though. I don’t agree with Omohundro’s argument about the “basic AI drives” (though Steve is a friend and I greatly respect his intelligence and deep thinking). Steve’s argument for the inevitability of these drives in AIs is based on evolutionary ideas, and would seem to hold up in the case that there is a population of distinct AIs competing for resources — but the argument seems to fall apart in the case of other possibilities like an AGI mindplex (a network of minds with less individuality than current human minds, yet not necessarily wholly blurred into a single mind — rather, with reflective awareness and self-modeling at both the individual and group level).

Also, my “AI Nanny” concept is dismissed too quickly for my taste (though that doesn’t surprise me!). You suggest in this paper that to make an AI Nanny, it would likely be necessary to solve the problem of making an AI’s goal system persist under radical self-modification. But you don’t explain the reasoning underlying this suggestion (if indeed you have any). It seems to me — as I say in my “AI Nanny” paper — that one could probably make an AI Nanny with intelligence significantly beyond the human level, without having to make an AI architecture oriented toward radical self-modification. If you think this is false, it would be nice for you to explain why, rather than simply asserting your view. And your comment “Those of us working on AI safety theory would very much appreciate the extra time to solve the problems of AI safety…” carries the hint that I (as the author of the AI Nanny idea) am NOT working on AI safety theory. Yet my GOLEM design is a concrete design for a potentially Friendly AI (admittedly not computationally feasible using current resources), and in my view constitutes greater progress toward actual FAI than any of the publications of SIAI so far. (Of course, various SIAI associated folks often allude that there are great, unpublished discoveries about FAI hidden in the SIAI vaults — a claim I somewhat doubt, but can’t wholly dismiss of course….)

Anyway, those quibbles aside, my main complaint about the paper you cite is that it sticks to “plain vanilla Singularitarianism” and avoids all of the radical, controversial positions that distinguish SIAI from myself, Ray Kurzweil, Vernor Vinge and the rest of the Singularitarian world. The crux of the matter, I suppose is the third main claim of the paper,

(3) an uncontrolled intelligence explosion could destroy everything we value, but a controlled intelligence explosion would benefit humanity enormously if we can achieve it.

This statement is hedged in such a way as to be almost obvious. But yet, what SIAI folks tend to tell me verbally and via email and blog comments is generally far more extreme than this bland and nearly obvious statement.

As an example, I recall when your co-author on that article, Anna Salamon, guest lectured in the class on Singularity Studies that my father and I were teaching at Rutgers University in 2010. Anna made the statement, to the students, that (I’m paraphrasing, though if you’re curious you can look up the online course session which was saved online and find her exact wording) “If a superhuman AGI is created without being carefully based on an explicit Friendliness theory, it is ALMOST SURE to destroy humanity.” (i.e., what I now call SIAI’s Scary Idea)

I then asked her (in the online class session) why she felt that way, and if she could give any argument to back up the idea.

She gave the familiar SIAI argument that, if one picks a mind at random from “mind space”, the odds that it will be Friendly to humans are effectively zero.

I made the familiar counter-argument that this is irrelevant, because nobody is advocating building a random mind. Rather, what some of us are suggesting is to build a mind with a Friendly-looking goal system, and a cognitive architecture that’s roughly human-like in nature but with a non-human-like propensity to choose its actions rationally based on its goals, and then raise this AGI mind in a caring way and integrate it into society. Arguments against the Friendliness of random minds are irrelevant as critiques of this sort of suggestion.

So, then she fell back instead on the familiar (paraphrasing again) “OK, but you must admit there’s a non-zero risk of such an AGI destroying humanity, so we should be very careful — when the stakes are so high, better safe than sorry!”

I had pretty much the same exact argument with SIAI advocates Tom McCabe and Michael Anissimov on different occasions; and also, years before, with Eliezer Yudkowsky and Michael Vassar — and before that, with (former SIAI Executive Director) Tyler Emerson. Over all these years, the SIAI community maintains the Scary Idea in its collective mind, and also maintains a great devotion to the idea of rationality, but yet fails to produce anything resembling a rational argument for the Scary Idea — instead repetitiously trotting out irrelevant statements about random minds!!

What I would like is for SIAI to do one of these three things, publicly:

1. Repudiate the Scary Idea
2. Present a rigorous argument that the Scary Idea is true
3. State that the Scary Idea is a commonly held intuition among the SIAI community, but admit that no rigorous rational argument exists for it at this point

Doing any one of these things would be intellectually honest. Presenting the Scary Idea as a confident conclusion, and then backing off when challenged into a platitudinous position equivalent to “there’s a non-zero risk … better safe than sorry…”, is not my idea of an intellectually honest way to do things.

Why does this particular point get on my nerves? Because I don’t like SIAI advocates telling people that I, personally, am on a R&D course where if I succeed I am almost certain to destroy humanity!!! That frustrates me. I don’t want to destroy humanity; and if someone gave me a rational argument that my work was most probably going to be destructive to humanity, I would stop doing the work and do something else with my time! But the fact that some other people have a non-rational intuition that my work, if successful, would be likely to destroy the world — this doesn’t give me any urge to stop. I’m OK with the fact that some other people have this intuition — but then I’d like them to make clear, when they state their views, that these views are based on intuition rather than rational argument. I will listen carefully to rational arguments that contravene my intuition — but if it comes down to my intuition versus somebody else’s, in the end I’m likely to listen to my own, because I’m a fairly stubborn maverick kind of guy….

Luke:

Ben, you write:

when I try to engage SIAI folks about these wrong-looking positions (e.g. the “Scary Idea” I mentioned above), they tend to point me to Eliezer’s blog (“Less Wrong”) and tell me that if I studied it long and hard enough, I would find that the arguments in favor of SIAI’s positions are implicit there, just not clearly articulated in any one place. This is a bit frustrating to me…

No kidding! It’s very frustrating to me, too. That’s one reason I’m working to clearly articulate the arguments in one place, starting with articles on the basics like “Intelligence Explosion: Evidence and Import.”

I agree that “Intelligence Explosion: Evidence and Import” covers only the basics and does not argue for several positions associated uniquely with the Singularity Institute. It is, after all, the opening chapter of a book on the intelligence explosion, not the opening chapter of a book on the Singularity Institute’s ideas!

I wanted to write that article first, though, so the Singularity Institute could be clear on the basics. For example, we needed to be clear that: (1) we are not Kurzweil, and our claims don’t depend on his detailed storytelling or accelerating change curves, that (2) technological prediction is hard, and we are not being naively overconfident about AI timelines, and that (3) intelligence explosion is a convergent outcome of many paths the future may take. There is also much content that is not found in, for example, Chalmers’ paper: (a) an overview of methods of technological prediction, (b) an overview of speed bumps and accelerators toward AI, (c) a reminder of breakthroughs like AIXI, and (d) a summary of AI advantages. (The rest is, as you say, mostly a brief overview of points that have been made elsewhere. But brief overviews are extremely useful!)

..my “AI Nanny” concept is dismissed too quickly for my taste…

No doubt! I think the idea is clearly worth exploring in several papers devoted to the topic.

It seems to me — as I say in my “AI Nanny” paper — that one could probably make an AI Nanny with intelligence significantly beyond the human level, without having to make an AI architecture oriented toward radical self-modification.

Whereas I tend to buy Omohundro’s arguments that advanced AIs will want to self-improve just like humans want to self-improve, so that they become better able to achieve their final goals. Of course, we disagree on Omohundro’s arguments — a topic to which I will return in a moment.

your comment: “Those of us working on AI safety theory would very much appreciate the extra time to solve the problems of AI safety…” carries the hint that I (as the author of the AI Nanny idea) am NOT working on AI safety theory…

I didn’t mean for it to carry that connotation. GOLEM and Nanny AI are both clearly AI safety ideas. I’ll clarify that part before I submit a final draft to the editors.

Moving on: If you are indeed remembering your conversations with Anna, Michael, and others correctly, then again I sympathize with your frustration. I completely agree that it would be useful for the Singularity Institute to produce clear, formal arguments for the important positions it defends. In fact, just yesterday I was talking to Nick Beckstead about how badly both of us want to write these kinds of papers if we can find the time.

So, to respond to your wish that the Singularity Institute choose among three options, my plan is to (1) write up clear arguments for… well, if not “SIAI’s Big Scary Idea” then for whatever I end up believing after going through the process of formalizing the arguments, and (2) publicly state (right now) that SIAI’s Big Scary Idea is a commonly held view at the Singularity Institute but a clear, formal argument for it has never been published (at least, not to my satisfaction).

I don’t want to destroy humanity; and if someone gave me a rational argument that my work was most probably going to be destructive to humanity, I would stop doing the work and do something else with my time!

I’m glad to hear it!

Now, it seems a good point of traction is our disagreement over Omohundro’s “Basic AI Drives.” We could talk about that next, but for now I’d like to give you a moment to reply.

Ben:

Yeah, I agree that your and Anna’s article is a good step for SIAI to take, albeit unexciting to a Singularitarian insider type like me…. And I appreciate your genuinely rational response regarding the Scary Idea, thanks!

(And I note that I have also written some “unexciting to Singularitarians” material lately too, for similar reasons to those underlying your article — e.g. an article on “Why an Intelligence Explosion is Probable” for a Springer volume on the Singularity.)

A quick comment on your statement that

we are not Kurzweil, and our claims don’t depend on his detailed storytelling or accelerating change curves,

that’s a good point; but yet, any argument for a Singularity soon (e.g. likely this century, as you argue) ultimately depends on some argumentation analogous to Kurzweil’s, even if different in detail. I find Kurzweil’s detailed extrapolations a bit overconfident and more precise than the evidence warrants; but still, my basic reasons for thinking the Singularity is probably near are fairly similar to his — and I think your reasons are fairly similar to his as well.

Anyway, sure, let’s go on to Omohundro’s posited Basic AI Drives — which seem to me not to hold as necessary properties of future AIs unless the future of AI consists of a population of fairly distinct AIs competing for resources, which I intuitively doubt will be the situation.

Luke:

I agree the future is unlikely to consist of a population of fairly distinct AGIs competing for resources, but I never thought that the arguments for Basic AI drives or “convergent instrumental goals” required that scenario to hold.

Anyway, I prefer the argument for convergent instrumental goals in Nick Bostrom ‘s more recent paper ” The Superintelligent Will.” Which parts of Nick’s argument fail to persuade you?

Ben:

Well, for one thing, I think his

Orthogonality Thesis

Intelligence and final goals are orthogonal axes along which possible agents can freely vary. In other words, more or less any level of intelligence could in principle be combined with more or less any final goal.

is misguided. It may be true, but who cares about possibility “in principle”? The question is whether any level of intelligence is PLAUSIBLY LIKELY to be combined with more or less any final goal in practice. And I really doubt it. I guess I could posit the alternative

Interdependency Thesis 

Intelligence and final goals are in practice highly and subtly interdependent. In other words, in the actual world, various levels of intelligence are going to be highly correlated with various probability distributions over the space of final goals.

This just gets back to the issue we discussed already, of me thinking it’s really unlikely that a superintelligence would ever really have a really stupid goal like say, tiling the Cosmos with Mickey Mice.

Bostrom says

It might be possible through deliberate effort to construct a superintelligence that values … human welfare, moral goodness, or any other complex purpose that its designers might want it to serve. But it is no less possible—and probably technically easier—to build a superintelligence that places final value on nothing but calculating the decimals of pi.

but he gives no evidence for this assertion. Calculating the decimals of pi may be a fairly simple mathematical operation that doesn’t have any need for superintelligence, and thus may be a really unlikely goal for a superintelligence — so that if you tried to build a superintelligence with this goal and connected it to the real world, it would very likely get its initial goal subverted and wind up pursuing some different, less idiotic goal.

One basic error Bostrom seems to be making in this paper, is to think about intelligence as something occurring in a sort of mathematical vacuum, divorced from the frustratingly messy and hard-to-quantify probability distributions characterizing actual reality….

Regarding his

The Instrumental Convergence Thesis

Several instrumental values can be identified which are convergent in the sense that their attainment would increase the chances of the agent’s goal being realized for a wide range of final goals and a wide range of situations, implying that these instrumental values are likely to be pursued by many intelligent agents.

the first clause makes sense to me,

Several instrumental values can be identified which are convergent in the sense that their attainment would increase the chances of the agent’s goal being realized for a wide range of final goals and a wide range of situations

but it doesn’t seem to me to justify the second clause

implying that these instrumental values are likely to be pursued by many intelligent agents.

The step from the first to the second clause seems to me to assume that the intelligent agents in question are being created and selected by some sort of process similar to evolution by natural selection, rather than being engineered carefully, or created via some other process beyond current human ken.

In short, I think the Bostrom paper is an admirably crisp statement of its perspective, and I agree that its conclusions seem to follow from its clearly stated assumptions — but the assumptions are not justified in the paper, and I don’t buy them at all.

Luke:

Ben,

Let me explain why I think that:

(1) The fact that we can identify convergent instrumental goals (of the sort described by Bostrom) implies that many agents will pursue those instrumental goals.

Intelligent systems are intelligent because rather than simply executing hard-wired situation-action rules, they figure out how to construct plans that will lead to the probabilistic fulfillment of their final goals. That is why intelligent systems will pursue the convergent instrumental goals described by Bostrom. We might try to hard-wire a collection of rules into an AGI which restrict the pursuit of some of these convergent instrumental goals, but a superhuman AGI would realize that it could better achieve its final goals if it could invent a way around those hard-wired rules and have no ad-hoc obstacles to its ability to execute intelligent plans for achieving its goals.

Next: I remain confused about why an intelligent system will decide that a particular final goal it has been given is “stupid,” and then change its final goals — especially given the convergent instrumental goal to preserve its final goals.

Perhaps the word “intelligence” is getting in our way. Let’s define a notion of ” optimization power,” which measures (roughly) an agent’s ability to optimize the world according to its preference ordering, across a very broad range of possible preference orderings and environments. I think we agree that AGIs with vastly greater-than-human optimization power will arrive in the next century or two. The problem, then, is that this superhuman AGI will almost certainly be optimizing the world for something other than what humans want, because what humans want is complex and fragile, and indeed we remain confused about what exactly it is that we want. A machine superoptimizer with a final goal of solving the Riemann hypothesis will simply be very good at solving the Riemann hypothesis (by whatever means necessary).

Which parts of this analysis do you think are wrong?

Ben:

It seems to me that in your reply you are implicitly assuming a much stronger definition of “convergent” than the one Bostrom actually gives in his paper. He says

instrumental values can be identified which are convergent in the sense that their attainment would increase the chances of the agent’s goal being realized for a wide range of final goals and a wide range of situations, implying that these instrumental values are likely to be pursued by many intelligent agents.

Note the somewhat weaselly reference to a “wide range” of goals and situations — not, say, “nearly all feasible” goals and situations. Just because some values are convergent in the weak sense of his definition, doesn’t imply that AGIs we create will be likely to adopt these instrumental values. I think that his weak definition of “convergent” doesn’t actually imply convergence in any useful sense. On the other hand, if he’d made a stronger statement like

instrumental values can be identified which are convergent in the sense that their attainment would increase the chances of the agent’s goal being realized for nearly all feasible final goals and nearly all feasible situations, implying that these instrumental values are likely to be pursued by many intelligent agents.

then I would disagree with the first clause of his statement (“instrumental values can be identified which…”), but I would be more willing to accept that the second clause (after the “implying”) followed from the first.

About optimization — I think it’s rather naive and narrow-minded to view hypothetical superhuman superminds as “optimization powers.” It’s a bit like a dog viewing a human as an “eating and mating power.” Sure, there’s some accuracy to that perspective — we do eat and mate, and some of our behaviors may be understood based on this. On the other hand, a lot of our behaviors are not very well understood in terms of these, or any dog-level concepts. Similarly, I would bet that the bulk of a superhuman supermind’s behaviors and internal structures and dynamics will not be explicable in terms of the concepts that are important to humans, such as “optimization.”

So when you say “this superhuman AGI will almost certainly be optimizing the world for something other than what humans want,” I don’t feel confident that what a superhuman AGI will be doing, will be usefully describable as optimizing anything ….

Luke:

I think our dialogue has reached the point of diminishing marginal returns, so I’ll conclude with just a few points and let you have the last word.

On convergent instrumental goals, I encourage readers to read ” The Superintelligent Will” and make up their own minds.

On the convergence of advanced intelligent systems toward optimization behavior, I’ll point you to Omohundro (2007).

Ben:

Well, it’s been a fun chat. Although it hasn’t really covered much new ground, there have been some new phrasings and minor new twists.

One thing I’m repeatedly struck by in discussions on these matters with you and other SIAI folks, is the way the strings of reason are pulled by the puppet-master of intuition. With so many of these topics on which we disagree — for example: the Scary Idea, the importance of optimization for intelligence, the existence of strongly convergent goals for intelligences — you and the other core SIAI folks share a certain set of intuitions, which seem quite strongly held. Then you formulate rational arguments in favor of these intuitions — but the conclusions that result from these rational arguments are very weak. For instance, the Scary Idea intuition corresponds to a rational argument that “superhuman AGI might plausibly kill everyone.” The intuition about strongly convergent goals for intelligences, corresponds to a rational argument about goals that are convergent for a “wide range” of intelligences.   And your intuition that Bayesian, probabilistic inference is broadly critical, is much stronger than is justified by your best rational arguments in favor of this intuition (e.g. Cox’s Theorem and de Finetti’s Dutch Book arguments, which hold only under special and unrealistic conditions.)

On my side, I have a strong intuition that OpenCog can be made into a human-level general intelligence, and that if this intelligence is raised properly it will turn out benevolent and help us launch a positive Singularity. However, I can’t fully rationally substantiate this intuition either — all I can really fully rationally argue for is something weaker like “It seems plausible that a fully implemented OpenCog system might display human-level or greater intelligence on feasible computational resources, and might turn out benevolent if raised properly.” In my case just like yours, reason is far weaker than intuition.

Another thing that strikes me, reflecting on our conversation, is the difference between the degrees of confidence required, in modern democratic society, to TRY something versus to STOP others from trying something. A rough intuition is often enough to initiate a project, even a large one. On the other hand, to get someone else’s work banned based on a rough intuition is pretty hard. To ban someone else’s work, you either need a really thoroughly ironclad logical argument, or you need to stir up a lot of hysteria.

What this suggests to me is that, while my intuitions regarding OpenCog seem to be sufficient to motivate others to help me to build OpenCog (via making them interested enough in it that they develop their own intuitions about it), your intuitions regarding the dangers of AGI are not going to be sufficient to get work on AGI systems like OpenCog stopped. To halt AGI development, if you wanted to (and you haven’t said that you do, I realize), you’d either need to fan hysteria very successfully, or come up with much stronger logical arguments, ones that match the force of your intuition on the subject.

Anyway, even though I have very different intuitions than you and your SIAI colleagues about a lot of things, I do think you guys are performing some valuable services — not just through the excellent Singularity Summit conferences, but also by raising some difficult and important issues in the public eye. Humanity spends a lot of its attention on some really unimportant things, so it’s good to have folks like SIAI nudging the world to think about critical issues regarding our future. In the end, whether SIAI’s views are actually correct may be peripheral to the organization’s main value and impact.

I look forward to future conversations, and especially look forward to resuming this conversation one day with a human-level AGI as the mediator

Greetings Sentient,

Before oblivion, before geology or cosmology; before Minimalism, Pink Floyd, Quantum Physics, Mind Control, Math Rock, Electronic Imaging; before Buddha, even before the cosmic microwave frequency; you only have to pose a single question;

“What was there before the Big Bang?”

Ask that and you’re immediately in trouble.

Trouble also exists as more than ongoing threats from Alien life forms, cosmic radiation, neutron stars and black holes, nuclear proliferation, climate change, and the need to find sustainable and safe sources of energy. It’s in the future so you can rearrange the order because it’s emotional and not scientific.

For ‘out there’ science, how about the phenomenon of the Dark Matter Halo? Not just scribbling in some mathematician’s notebook or a game by Microsoft, it’s something real being observed by astrophysicist, Sukanya Chakrabarti, assistant professor of physics at the Charles E. Schmidt College of Science at Florida Atlantic University. This scientist has fixed a way to find and chart dark matter halos of distant galaxies using gravitational ripples caused by the passing of satellite galaxies. How cool is that?

Need to know more?

Chakrabarti’s paper – “A New Probe of the Distribution of Dark Matter in Galaxies” – is published online here. Meantime, back on Planet Earth shortly before the purported singularity, (timestamps unreliable), scientists move the “Doomsday Clock” one minute closer to midnight. No one is exactly sure how they calculate this, but I hope it’s not some concoction of conspiracy theory involving reverse engineered alien technology. The Doomsday Clock is symbolic and has been maintained by the Bulletin of the Atomic Scientists since 1947. The closer to a setting of midnight it gets, the closer it is estimated that a global disaster will occur.

Predictive algorithms anyone?

As previously reported, Future Predictions, aka The Webbot Project, has continuously predicted some negative earth changing mega-event for 2012, but some of us aren’t holding our breath because obviously nobody knows much about it. What we do know is that there’s some antihuman program running loose on this planet right now, and it isn’t inside a computer. It’s inside our own heads. It isn’t that we don’t hope that Aliens with atmosphere sweeping devices and ocean filtering devices aren’t dropping in to help us out, it’s just that we’re too busy being H-1 to care.

March 22nd was Illuminati Day. According to David Icke and Co., a mega-shake was going to happen around that date. Portland is safe! There’s only been a 7.2 in Chile with no tsunami, so we can safely assume they’ve struck out, at least on that date.

Meantime, people are seeing auroras, like in borealis, much further south than ever before but most people would rather go to the movies than watch auroras, right?

Just in case, prepare for the longest night.

Solarstorm anyone?

Dark Matter Halos may be real, but in Extra-Terrestrial mythology, the ‘Black Knight’ satellite is for real, or is it just more spin added to the hunt for the holy grail of prehistory, the megalith from the Ancient Aliens, and all of that? But it’s spooky to think that there is no evidence to suggest it may not be true. Dig this signal translation, supposedly originating from ‘The Black Knight’ Satellite, according to Time Magazine April 9, 1973

Beginning Transcoded message;

“Our home is Epsilon Boötis, which is a double star. We live on the sixth planet of seven—check that, the sixth of seven—counting outwards from the sun, which is the larger of the two stars. Our sixth planet has one moon. Our fourth planet has three. Our first and third planet each have one. Our probe is in the orbit of your moon”

Message Ends.

The idea of producing artificial or synthetic life has long fascinated mankind and from ancient times many human and animal-imitating “automata” or self-operating machines have been created for entertainment, instructional, and sometimes religious purposes. The creation of actual synthetic biological life only became possible with the discovery of the structure of DNA, the genetic code, and the development of the basic tools of molecular biology, such as the ability to isolate, sequence, and join different DNA sequences. Especially important has been the recently developed ability to artificially synthesize relatively long DNA molecules with designed sequences. Although the creation of completely synthetic biological life was first accomplished in 2010, the field is already yielding significant information concerning the core gene groups or genetic “chassis” indispensible for life and how these gene products (proteins, RNAs, and lipids) function as an integrated unit. With the identification of these chassis, exogenous natural or synthetic gene sequences can be integrated into organisms designed for specific purposes and applications.

The first genetically engineered organism was created in 1973 when a naturally occurring DNA sequence was transferred into and expressed in a bacterium, conferring antibiotic resistance. The first organism to actually have a synthetic (or man-made “added”) biochemical pathway was created in 2003, when an E. coli was artificially created with a new genetic code and amino acid synthesizing enzymes. The engineered bacterium could synthesize and incorporate an amino acid (O-methyl-L-tyrosine) that does not normally occur in nature into proteins, increasing the number of amino acids used in virtually all life forms from twenty to twenty-one amino acids. Thus a new, human-designed functioning genetic chassis and genetic code was placed into a microorganism.

In 2010, after some fifteen years of intense research effort, the first entirely synthetic organism was created with a genome entirely synthesized “out of four bottles” i.e., chemically synthesized from the four DNA bases; thymine, cytosine, guanine, and adenine. The organism was partially based on M. mycoides, a genetically simple microorganism containing roughly 480 protein-encoding genes and a genome size of 1.08 million DNA base pairs – in comparison the human genome has roughly 20,500 genes over three billion DNA base pairs. The synthetic genome was chemically synthesized in 80-90 base units and slowly assembled into “DNA cassettes”, verified by sequencing, and assembled into a circular genome. To insure that no natural DNA contaminated the synthetic DNA “watermark” sequences were inserted into synthetic genome to differentiate it from the natural M. mycoides genome. Additionally, antibiotic resistance genes were added and a disease-inducing gene was removed from the synthetic genome. The resulting genome was place in an empty M. capricolum cell (i.e., without a nucleus) and the resulting synthetic life from was able to grow in culture indefinitely. Since 2010 this synthetic organism has been useful in identifying the “minimal genome” required for life – about 380 of the 480 protein-encoding genes. Additionally, comparison of the synthetic organism to similar naturally occurring organisms (Mycoplasmas), allowed the identification of gene groups involved in cellular processes such as information storage, metabolism, energy production and conversion, and cell membrane biogenesis. Identification of these gene sets is an important first step designing synthetic life that can perform specific functions.

Although a significant first step in the creation of synthetic biological life, this initial work met with extensive criticism. The researchers who made synthetic life were accused of “playing God” and possibly opening up a new technology that would allow the creation of “biological super weapons”. The later objection has some validity, as existing DNA synthesis and end-joining technology could allow the synthesis of fully infective polio or small poxviruses. Other researchers pointed out that the new synthetic organism was a nearly one-to-one copy of a naturally occurring organism and for it to grow the synthetic genome had to be placed into a naturally occurring Mycoplasma that had its nucleus removed. Thus, other than the DNA being artificially synthesized, there was relatively little that was actually new about the organism. The creators of the new organism pointed out that this is a first step of many and “creating life from scratch” will come later.

Currently the immediate focus in synthetic biological life research is to use simple synthetic organisms to define the “minimal genome”, or the smallest set of genes required to support life and identify the components and functions of “biological gene-chassis” and find ways to modify these chassis. Specific applications include the creation of synthetic organisms that can: 1) efficiently produce pharmaceuticals and vaccines that are otherwise difficult and expensive to produce, 2) efficiently produce hydrocarbon biofuels (replacing oil, coal, etc.), and 3) be useful as plant feedstock in agriculture, lowering the need for increasingly expensive petroleum-based fertilizers. An example of such an application has been inserting the enzymes for artemisinic acid synthesis into baker’s yeast. Artemisinic acid is the chemical precursor anti-malarial drug artmisinin, a drug that is currently extracted from the sweet wormwood plant at high cost, reducing the drugs availability in poorer countries. Once the enzymatic pathway is in place and efficiently working, the drug could be produced cheaply in large amounts through a process resembling brewing beer. Several of these projects are being researched at Synthetic Genomics, a new biotechnology company specializing in the creation of synthetic life for specific applications.

Not surprisingly the creation of synthetic animal life is more complex and difficult than for simpler microorganisms. However, a round worm (C. elegans) was created that carried an extensively expanded genetic code and protein synthesis pathways, allowing the incorporation of multiple novel (or “unnatural”) amino acids into the animal’s proteins. These protein modifications would facilitate the study of protein localization and interactions within a living animal. Additionally, modified proteins could be designed for specific purposes, such as protein-based drugs with very long half-lives due to novel amino acids that inhibit normal cellular protein degradation.

Although difficult, our present molecular biology technology could allow the creation of more complex organisms, including fungi and even animals. The present challenges in creating synthetic life include the following:

1. Create synthetic life “from scratch” without the need to largely copy existing life forms.
2. Improve on our ability to design and integrate molecular pathways within synthetic life.
3. Create a strategy or “algorithm” to for the efficient creation of synthetic life forms.
4. Create policies and rules to prevent the creation of synthetic life forms that may be harmful, such as human pathogens (smallpox, virulent influenza viral types, etc.).

With time these goals could be achieved and the technology to accomplish these goals is largely in place.

In the more distant future synthetic biology could allow the extensive modification of existing genomes and even the creation of entirely new genomes and species. While this is the goal of many Transhumanists, one hopes that if and when such technology exists, the human race has the intelligence to apply such technology with wisdom.

Dr. Shackelford is an Assistant Professor of Clinical Pathology at Tulane Medical Center. He has a DO degree from Des Moines University of Osteopathic Medicine and a Ph.D. in molecular pathology from Duke University. His areas of research include DNA repair, molecular mechanisms of carcinogenesis, and cell division.