THE SINGULARITY IS
When Humans Transcend Biology
By Ray Kurzweil, Viking Press
So what is the Singularity?
Within a quarter century, nonbiological intelligence
will match the range and subtlety of human intelligence. It will
then soar past it because of the continuing acceleration of information-based
technologies, as well as the ability of machines to instantly share
their knowledge. Intelligent nanorobots will be deeply integrated
in our bodies, our brains, and our environment, overcoming pollution
and poverty, providing vastly extended longevity, full-immersion
virtual reality incorporating all of the senses (like “The
Matrix”), “experience beaming” (like “Being
John Malkovich”), and vastly enhanced human intelligence.
The result will be an intimate merger between the technology-creating
species and the technological evolutionary process it spawned.
No, that’s just the precursor. Nonbiological
intelligence will have access to its own design and will be able
to improve itself in an increasingly rapid redesign cycle. We’ll
get to a point where technical progress will be so fast that unenhanced
human intelligence will be unable to follow it. That will mark the
When will that occur?
I set the date for the Singularity—representing
a profound and disruptive transformation in human capability—as
2045. The nonbiological intelligence created in that year will be
one billion times more powerful than all human intelligence today.
Why is this called
The term “Singularity” in my book is comparable
to the use of this term by the physics community. Just as we find
it hard to see beyond the event horizon of a black hole, we also
find it difficult to see beyond the event horizon of the historical
Singularity. How can we, with our limited biological brains, imagine
what our future civilization, with its intelligence multiplied trillions-fold,
be capable of thinking and doing? Nevertheless, just as we can draw
conclusions about the nature of black holes through our conceptual
thinking, despite never having actually been inside one, our thinking
today is powerful enough to have meaningful insights into the implications
of the Singularity. That’s what I’ve tried to do in
Okay, let’s break
this down. It seems a key part of your thesis is that we will be
able to capture the intelligence of our brains in a machine.
So how are we going
to achieve that?
We can break this down further into hardware
and software requirements. In the book, I show how we need about
10 quadrillion (1016) calculations per second (cps) to
provide a functional equivalent to all the regions of the brain.
Some estimates are lower than this by a factor of 100. Supercomputers
are already at 100 trillion (1014) cps, and will hit
1016 cps around the end of this decade. Several supercomputers
with 1 quadrillion cps are already on the drawing board, with two
Japanese efforts targeting 10 quadrillion cps around the end of
the decade. By 2020, 10 quadrillion cps will be available for around
$1,000. Achieving the hardware requirement was controversial when
my last book on this topic, The Age of Spiritual Machines,
came out in 1999, but is now pretty much of a mainstream view among
informed observers. Now the controversy is focused on the algorithms.
And how will we recreate
the algorithms of human intelligence?
To understand the principles of human intelligence
we need to reverse-engineer the human brain. Here, progress is far
greater than most people realize. The spatial and temporal (time)
resolution of brain scanning is also progressing at an exponential
rate, roughly doubling each year, like most everything else having
to do with information. Just recently, scanning tools can see individual
interneuronal connections, and watch them fire in real time. Already,
we have mathematical models and simulations of a couple dozen regions
of the brain, including the cerebellum, which comprises more than
half the neurons in the brain. IBM is now creating a simulation
of about 10,000 cortical neurons, including tens of millions of
connections. The first version will simulate the electrical activity,
and a future version will also simulate the relevant chemical activity.
By the mid 2020s, it’s conservative to conclude that we will
have effective models for all of the brain.
So at that point
we’ll just copy a human brain into a supercomputer?
I would rather put it this way: At that point, we’ll
have a full understanding of the methods of the human brain. One
benefit will be a deep understanding of ourselves, but the key implication
is that it will expand the toolkit of techniques we can apply to
create artificial intelligence. We will then be able to create nonbiological
systems that match human intelligence in the ways that humans are
now superior, for example, our pattern- recognition abilities. These
superintelligent computers will be able to do things we are not
able to do, such as share knowledge and skills at electronic speeds.
By 2030, a thousand dollars of computation will be
about a thousand times more powerful than a human brain. Keep in
mind also that computers will not be organized as discrete objects
as they are today. There will be a web of computing deeply integrated
into the environment, our bodies and brains.
You mentioned the
AI tool kit. Hasn’t AI failed to live up to its expectations?
There was a boom and bust cycle in AI during the 1980s,
similar to what we saw recently in e-commerce and telecommunications.
Such boom-bust cycles are often harbingers of true revolutions;
recall the railroad boom and bust in the 19th century. But just
as the Internet “bust” was not the end of the Internet,
the so-called “AI Winter” was not the end of the story
for AI either. There are hundreds of applications of “narrow
AI” (machine intelligence that equals or exceeds human intelligence
for specific tasks) now permeating our modern infrastructure. Every
time you send an email or make a cell phone call, intelligent algorithms
route the information. AI programs diagnose electrocardiograms with
an accuracy rivaling doctors, evaluate medical images, fly and land
airplanes, guide intelligent autonomous weapons, make automated
investment decisions for over a trillion dollars of funds, and guide
industrial processes. These were all research projects a couple
of decades ago. If all the intelligent software in the world were
to suddenly stop functioning, modern civilization would grind to
a halt. Of course, our AI programs are not intelligent enough to
organize such a conspiracy, at least not yet.
Why don’t more people
see these profound changes ahead?
Hopefully after they read my new book, they will.
But the primary failure is the inability of many observers to think
in exponential terms. Most long-range forecasts of what is technically
feasible in future time periods dramatically underestimate the power
of future developments because they are based on what I call the
“intuitive linear” view of history rather than the “historical
exponential” view. My models show that we are doubling the
paradigm-shift rate every decade. Thus the 20th century was gradually
speeding up to the rate of progress at the end of the century; its
achievements, therefore, were equivalent to about twenty years of
progress at the rate in 2000. We’ll make another twenty years
of progress in just fourteen years (by 2014), and then do the same
again in only seven years. To express this another way, we won’t
experience one hundred years of technological advance in the 21st
century; we will witness on the order of 20,000 years of progress
(again, when measured by the rate of progress in 2000), or about
1,000 times greater than what was achieved in the 20th century.
The exponential growth of information technologies
is even greater: we’re doubling the power of information technologies,
as measured by price-performance, bandwidth, capacity and many other
types of measures, about every year. That’s a factor of a
thousand in ten years, a million in twenty years, and a billion
in thirty years. This goes far beyond Moore’s law (the shrinking
of transistors on an integrated circuit, allowing us to double the
price-performance of electronics each year). Electronics is just
one example of many. As another example, it took us 14 years to
sequence HIV; we recently sequenced SARS in only 31 days.
So this acceleration of
information technologies applies to biology as well?
Absolutely. It’s not just computer devices like
cell phones and digital cameras that are accelerating in capability.
Ultimately, everything of importance will be comprised essentially
of information technology. With the advent of nanotechnology-based
manufacturing in the 2020s, we’ll be able to use inexpensive
table-top devices to manufacture on-demand just about anything from
very inexpensive raw materials using information processes that
will rearrange matter and energy at the molecular level.
We’ll meet our energy needs using nanotechnology-based
solar panels that will capture the energy in .03 percent of the
sunlight that falls on the Earth, which is all we need to meet our
projected energy needs in 2030. We’ll store the energy in
highly distributed fuel cells.
I want to come back to both
biology and nanotechnology, but how can you be so sure of these
developments? Isn’t technical progress on specific projects
Predicting specific projects is indeed not feasible.
But the result of the overall complex, chaotic evolutionary process
of technological progress is predictable.
People intuitively assume that the current rate of
progress will continue for future periods. Even for those who have
been around long enough to experience how the pace of change increases
over time, unexamined intuition leaves one with the impression that
change occurs at the same rate that we have experienced most recently.
From the mathematician’s perspective, the reason for this
is that an exponential curve looks like a straight line when examined
for only a brief duration. As a result, even sophisticated commentators,
when considering the future, typically use the current pace of change
to determine their expectations in extrapolating progress over the
next ten years or one hundred years. This is why I describe this
way of looking at the future as the “intuitive linear”
view. But a serious assessment of the history of technology reveals
that technological change is exponential. Exponential growth is
a feature of any evolutionary process, of which technology is a
As I show in the book, this has also been true of
biological evolution. Indeed, technological evolution emerges from
biological evolution. You can examine the data in different ways,
on different timescales, and for a wide variety of technologies,
ranging from electronic to biological, as well as for their implications,
ranging from the amount of human knowledge to the size of the economy,
and you get the same exponential—not linear—progression.
I have over forty graphs in the book from a broad variety of fields
that show the exponential nature of progress in information-based
measures. For the price-performance of computing, this goes back
over a century, well before Gordon Moore was even born.
Aren’t there are a
lot of predictions of the future from the past that look a little
Yes, any number of bad predictions from other futurists
in earlier eras can be cited to support the notion that we cannot
make reliable predictions. In general, these prognosticators were
not using a methodology based on a sound theory of technology evolution.
I say this not just looking backwards now. I’ve been making
accurate forward-looking predictions for over twenty years based
on these models.
But how can it be the case
that we can reliably predict the overall progression of these technologies
if we cannot even predict the outcome of a single project?
Predicting which company or product will succeed is
indeed very difficult, if not impossible. The same difficulty occurs
in predicting which technical design or standard will prevail. For
example, how will the wireless-communication protocols Wimax, CDMA,
and 3G fare over the next several years? However, as I argue extensively
in the book, we find remarkably precise and predictable exponential
trends when assessing the overall effectiveness (as measured in
a variety of ways) of information technologies. And as I mentioned
above, information technology will ultimately underlie everything
But how can that be?
We see examples in other areas of science of very
smooth and reliable outcomes resulting from the interaction of a
great many unpredictable events. Consider that predicting the path
of a single molecule in a gas is essentially impossible, but predicting
the properties of the entire gas—comprised of a great many
chaotically interacting molecules—can be done very reliably
through the laws of thermodynamics. Analogously, it is not possible
to reliably predict the results of a specific project or company,
but the overall capabilities of information technology, comprised
of many chaotic activities, can nonetheless be dependably anticipated
through what I call "the law of accelerating returns."
What will the impact
of these developments be?
Radical life extension, for one.
how does that work?
In the book, I talk about three great overlapping
revolutions that go by the letters “GNR,” which stands
for genetics, nanotechnology, and robotics. Each will provide a
dramatic increase to human longevity, among other profound impacts.
We’re in the early stages of the genetics—also called
biotechnology—revolution right now. Biotechnology is providing
the means to actually change your genes: not just designer babies
but designer baby boomers. We’ll also be able to rejuvenate
all of your body’s tissues and organs by transforming your
skin cells into youthful versions of every other cell type. Already,
new drug development is precisely targeting key steps in the process
of atherosclerosis (the cause of heart disease), cancerous tumor
formation, and the metabolic processes underlying each major disease
and aging process. The biotechnology revolution is already in its
early stages and will reach its peak in the second decade of this
century, at which point we’ll be able to overcome most major
diseases and dramatically slow down the aging process.
That will bring us to the nanotechnology revolution,
which will achieve maturity in the 2020s. With nanotechnology, we
will be able to go beyond the limits of biology, and replace your
current “human body version 1.0” with a dramatically
upgraded version 2.0, providing radical life extension.
And how does that
The “killer app” of nanotechnology is
“nanobots,” which are blood-cell sized robots that can
travel in the bloodstream destroying pathogens, removing debris,
correcting DNA errors, and reversing aging processes.
Human body version
We’re already in the early stages of augmenting
and replacing each of our organs, even portions of our brains with
neural implants, the most recent versions of which allow patients
to download new software to their neural implants from outside their
bodies. In the book, I describe how each of our organs will ultimately
be replaced. For example, nanobots could deliver to our bloodstream
an optimal set of all the nutrients, hormones, and other substances
we need, as well as remove toxins and waste products. The gastrointestinal
tract could be reserved for culinary pleasures rather than the tedious
biological function of providing nutrients. After all, we’ve
already in some ways separated the communication and pleasurable
aspects of sex from its biological function.
And the third revolution?
The robotics revolution, which really refers to “strong”
AI, that is, artificial intelligence at the human level, which we
talked about earlier. We’ll have both the hardware and software
to recreate human intelligence by the end of the 2020s. We’ll
be able to improve these methods and harness the speed, memory capabilities,
and knowledge- sharing ability of machines.
We’ll ultimately be able to scan all the salient
details of our brains from inside, using billions of nanobots in
the capillaries. We can then back up the information. Using nanotechnology-based
manufacturing, we could recreate your brain, or better yet reinstantiate
it in a more capable computing substrate.
Our biological brains use chemical signaling, which
transmit information at only a few hundred feet per second. Electronics
is already millions of times faster than this. In the book, I show
how one cubic inch of nanotube circuitry would be about one hundred
million times more powerful than the human brain. So we’ll
have more powerful means of instantiating our intelligence than
the extremely slow speeds of our interneuronal connections.
So we’ll just replace
our biological brains with circuitry?
I see this starting with nanobots in our bodies and
brains. The nanobots will keep us healthy, provide full-immersion
virtual reality from within the nervous system, provide direct brain-to-brain
communication over the Internet, and otherwise greatly expand human
intelligence. But keep in mind that nonbiological intelligence is
doubling in capability each year, whereas our biological intelligence
is essentially fixed in capacity. As we get to the 2030s, the nonbiological
portion of our intelligence will predominate.
The closest life
extension technology, however, is biotechnology, isn’t that
There’s certainly overlap in the G, N and R
revolutions, but that’s essentially correct.
So tell me more about
how genetics or biotechnology works.
As we are learning about the information processes
underlying biology, we are devising ways of mastering them to overcome
disease and aging and extend human potential. One powerful approach
is to start with biology's information backbone: the genome. With
gene technologies, we're now on the verge of being able to control
how genes express themselves. We now have a powerful new tool called
RNA interference (RNAi), which is capable of turning specific genes
off. It blocks the messenger RNA of specific genes, preventing them
from creating proteins. Since viral diseases, cancer, and many other
diseases use gene expression at some crucial point in their life
cycle, this promises to be a breakthrough technology. One gene we’d
like to turn off is the fat insulin receptor gene, which tells the
fat cells to hold on to every calorie. When that gene was blocked
in mice, those mice ate a lot but remained thin and healthy, and
actually lived 20 percent longer.
New means of adding new genes, called gene therapy,
are also emerging that have overcome earlier problems with achieving
precise placement of the new genetic information. One company I’m
involved with, United Therapeutics, cured pulmonary hypertension
in animals using a new form of gene therapy and it has now been
approved for human trials.
So we’re going
to essentially reprogram our DNA.
That’s a good way to put it, but that’s
only one broad approach. Another important line of attack is to
regrow our own cells, tissues, and even whole organs, and introduce
them into our bodies without surgery. One major benefit of this
“therapeutic cloning” technique is that we will be able
to create these new tissues and organs from versions of our cells
that have also been made younger—the emerging field
of rejuvenation medicine. For example, we will be able to create
new heart cells from your skin cells and introduce them into your
system through the bloodstream. Over time, your heart cells get
replaced with these new cells, and the result is a rejuvenated “young”
heart with your own DNA.
Drug discovery was once a matter of finding substances
that produced some beneficial effect without excessive side effects.
This process was similar to early humans’ tool discovery,
which was limited to simply finding rocks and natural implements
that could be used for helpful purposes. Today, we are learning
the precise biochemical pathways that underlie both disease and
aging processes, and are able to design drugs to carry out precise
missions at the molecular level. The scope and scale of these efforts
But perfecting our biology will only get us so far.
The reality is that biology will never be able to match what we
will be capable of engineering, now that we are gaining a deep understanding
of biology's principles of operation.
Not at all. Our interneuronal connections compute
at about 200 transactions per second, at least a million times slower
than electronics. As another example, a nanotechnology theorist,
Rob Freitas, has a conceptual design for nanobots that replace our
red blood cells. A conservative analysis shows that if you replaced
10 percent of your red blood cells with Freitas’ “respirocytes,”
you could sit at the bottom of a pool for four hours without taking
If people stop dying,
isn’t that going to lead to overpopulation?
A common mistake that people make when considering
the future is to envision a major change to today’s world,
such as radical life extension, as if nothing else were going to
change. The GNR revolutions will result in other transformations
that address this issue. For example, nanotechnology will enable
us to create virtually any physical product from information and
very inexpensive raw materials, leading to radical wealth creation.
We’ll have the means to meet the material needs of any conceivable
size population of biological humans. Nanotechnology will also provide
the means of cleaning up environmental damage from earlier stages
So we’ll overcome
disease, pollution, and poverty—sounds like a utopian vision.
It’s true that the dramatic scale of the technologies
of the next couple of decades will enable human civilization to
overcome problems that we have struggled with for eons. But these
developments are not without their dangers. Technology is a double
edged sword—we don’t have to look past the 20th century
to see the intertwined promise and peril of technology.
What sort of perils?
G, N, and R each have their downsides. The existential
threat from genetic technologies is already here: the same technology
that will soon make major strides against cancer, heart disease,
and other diseases could also be employed by a bioterrorist to create
a bioengineered biological virus that combines ease of transmission,
deadliness, and stealthiness, that is, a long incubation period.
The tools and knowledge to do this are far more widespread than
the tools and knowledge to create an atomic bomb, and the impact
could be far worse.
So maybe we shouldn’t
go down this road.
It’s a little late for that. But the idea of
relinquishing new technologies such as biotechnology and nanotechnology
is already being advocated. I argue in the book that this would
be the wrong strategy. Besides depriving human society of the profound
benefits of these technologies, such a strategy would actually make
the dangers worse by driving development underground, where responsible
scientists would not have easy access to the tools needed to defend
So how do we protect
I discuss strategies for protecting against dangers
from abuse or accidental misuse of these very powerful technologies
in chapter 8. The overall message is that we need to give a higher
priority to preparing protective strategies and systems. We need
to put a few more stones on the defense side of the scale. I’ve
given testimony to Congress on a specific proposal for a “Manhattan”
style project to create a rapid response system that could protect
society from a new virulent biological virus. One strategy would
be to use RNAi, which has been shown to be effective against viral
diseases. We would set up a system that could quickly sequence a
new virus, prepare a RNA interference medication, and rapidly gear
up production. We have the knowledge to create such a system, but
we have not done so. We need to have something like this in place
before its needed.
Ultimately, however, nanotechnology will provide a
completely effective defense against biological viruses.
nanotechnology have its own self-replicating danger?
Yes, but that potential won’t exist for a couple
more decades. The existential threat from engineered biological
viruses exists right now.
Okay, but how will
we defend against self-replicating nanotechnology?
There are already proposals for ethical standards
for nanotechnology that are based on the Asilomar conference standards
that have worked well thus far in biotechnology. These standards
will be effective against unintentional dangers. For example, we
do not need to provide self-replication to accomplish nanotechnology
But what about intentional
abuse, as in terrorism?
We’ll need to create a nanotechnology immune
system—good nanobots that can protect us from the bad ones.
Blue goo to protect
us from the gray goo!
Yes, well put. And ultimately we’ll need the
nanobots comprising the immune system to be self-replicating. I’ve
debated this particular point with a number of other theorists,
but I show in the book why the nanobot immune system we put in place
will need the ability to self-replicate. That’s basically
the same “lesson” that biological evolution learned.
Ultimately, however, strong AI will provide a completely
effective defense against self-replicating nanotechnology.
going to protect us against a pathological AI?
Yes, well, that would have to be a yet more intelligent
This is starting to sound
like that story about the universe being on the back of a turtle,
and that turtle standing on the back of another turtle, and so on
all the way down. So what if this more intelligent AI is unfriendly?
Another even smarter AI?
History teaches us that the more intelligent civilization—the
one with the most advanced technology—prevails. But I do have
an overall strategy for dealing with unfriendly AI, which I discuss
in chapter 8.
Okay, so I’ll
have to read the book for that one. But aren’t there limits
to exponential growth? You know the story about rabbits in Australia—they
didn’t keep growing exponentially forever.
There are limits to the exponential growth inherent
in each paradigm. Moore’s law was not the first paradigm to
bring exponential growth to computing, but rather the fifth. In
the 1950s they were shrinking vacuum tubes to keep the exponential
growth going and then that paradigm hit a wall. But the exponential
growth of computing didn’t stop. It kept going, with the new
paradigm of transistors taking over. Each time we can see the end
of the road for a paradigm, it creates research pressure to create
the next one. That’s happening now with Moore’s law,
even though we are still about fifteen years away from the end of
our ability to shrink transistors on a flat integrated circuit.
We’re making dramatic progress in creating the sixth paradigm,
which is three-dimensional molecular computing.
But isn’t there
an overall limit to our ability to expand the power of computation?
Yes, I discuss these limits in the book. The ultimate
2 pound computer could provide 1042 cps, which will be about 10
quadrillion (1016) times more powerful than all human
brains put together today. And that’s if we restrict the computer
to staying at a cold temperature. If we allow it to get hot, we
could improve that by a factor of another 100 million. And, of course,
we’ll be devoting more than two pounds of matter to computing.
Ultimately, we’ll use a significant portion of the matter
and energy in our vicinity. So, yes, there are limits, but they’re
not very limiting.
And when we saturate
the ability of the matter and energy in our solar system to support
intelligent processes, what happens then?
Then we’ll expand to the rest of the Universe.
Which will take a
long time I presume.
Well, that depends on whether we can use wormholes
to get to other places in the Universe quickly, or otherwise circumvent
the speed of light. If wormholes are feasible, and analyses show
they are consistent with general relativity, we could saturate the
universe with our intelligence within a couple of centuries. I discuss
the prospects for this in the chapter 6. But regardless of speculation
on wormholes, we’ll get to the limits of computing in our
solar system within this century. At that point, we’ll have
expanded the powers of our intelligence by trillions of trillions.
Getting back to life extension,
isn’t it natural to age, to die?
Other natural things include malaria, Ebola, appendicitis,
and tsunamis. Many natural things are worth changing. Aging may
be “natural,” but I don’t see anything positive
in losing my mental agility, sensory acuity, physical limberness,
sexual desire, or any other human ability.
In my view, death is a tragedy. It's a tremendous
loss of personality, skills, knowledge, relationships. We've rationalized
it as a good thing because that's really been the only alternative
we've had. But disease, aging, and death are problems we are now
in a position to overcome.
Wait, you said that
the golden era of biotechnology was still a decade away. We don’t
have radical life extension today, do we?
In my last book, Fantastic Voyage, Live Long Enough
to Live Forever, which I coauthored with Terry Grossman, M.D., we
describe a detailed and personalized program you can implement now
(which we call “bridge one”) that will enable most people
to live long enough to get to the mature phase of the biotechnology
evolution (“bridge two”). That in turn will get us to
“bridge three,” which is nanotechnology and strong AI,
which will result in being able to live indefinitely.
Okay, but won’t it
get boring to live many hundreds of years?
If humans lived many hundreds of years with no other
change in the nature of human life, then, yes, that would lead to
a deep ennui. But the same nanobots in the bloodstream that will
keep us healthy—by destroying pathogens and reversing aging
processes —will also vastly augment our intelligence and experiences.
As is its nature, the nonbiological portion of our intelligence
will expand its powers exponentially, so it will ultimately predominate.
The result will be accelerating change—so we will not be bored.
Won’t the Singularity
create the ultimate “digital divide” due to unequal
access to radical life extension and superintelligent computers?
We need to consider an important feature of the law
of accelerating returns, which is a 50 percent annual deflation
factor for information technologies, a factor which itself will
increase. Technologies start out affordable only by the wealthy,
but at this stage, they actually don’t work very well. At
the next stage, they’re merely expensive, and work a bit better.
Then they work quite well and are inexpensive. Ultimately, they’re
almost free. Cell phones are now at the inexpensive stage. There
are countries in Asia where most people were pushing a plow fifteen
years ago, yet now have thriving information economies and most
people have a cell phone. This progression from early adoption of
unaffordable technologies that don’t work well to late adoption
of refined technologies that are very inexpensive is currently a
decade-long process. But that too will accelerate. Ten years from
now, this will be a five year progression, and twenty years from
now it will be only a two- to three-year lag.
This model applies not just to electronic gadgets
but to anything having to do with information, and ultimately that
will be mean everything of value, including all manufactured products.
In biology, we went from a cost of ten dollars to sequence a base
pair of DNA in 1990 to about a penny today. AIDS drugs started out
costing tens of thousands of dollars per patient per year and didn’t
work very well, whereas today, effective drugs are about a hundred
dollars per patient per year in poor countries. That’s still
more than we’d like, but the technology is moving in the right
direction. So the digital divide and the have-have not divide is
diminishing, not exacerbating. Ultimately, everyone will have great
wealth at their disposal.
such as war, intolerance, environmental degradation prevent us from
reaching the Singularity?
We had a lot of war in the 20th century. Fifty million
people died in World War II, and there were many other wars. We
also had a lot of intolerance, relatively little democracy until
late in the century, and a lot of environmental pollution. All of
these problems of the 20th century had no effect on the law of accelerating
returns. The exponential growth of information technologies proceeded
smoothly through war and peace, through depression and prosperity.
The emerging 21st century technologies tend to be
decentralized and relatively friendly to the environment. With the
maturation of nanotechnology, we will also have the opportunity
to clean up the mess left from the crude early technologies of industrialization.
But won’t there
still be objections from religious and political leaders, not to
mention the common man and woman, to such a radical transformation
There were objections to the plow also, but that didn’t
stop people form using it. The same can be said for every new step
in technology. Technologies do have to prove themselves. For every
technology that is adopted, many are discarded. Each technology
has to demonstrate that it meets basic human needs. The cell phone,
for example, meets our need to communicate with one another. We
are not going to reach the Singularity in some single great leap
forward, but rather through a great many small steps, each seemingly
benign and modest in scope.
But what about controversies
such as the stem cell issue? Government opposition is clearly slowing
down progress in that field.
I clearly support stem cell research, but it is not
the case that the field of cell therapies has been significantly
slowed down. If anything, the controversy has accelerated creative
ways of achieving the holy grail of this field, which is transdifferentiation,
that is, creating new differentiated cells you need from your own
cells—for example, converting skin cells into heart cells
or pancreatic Islet cells. Transdifferentiation has already been
demonstrated in the lab. Objections such as those expressed against
stem- cell research end up being stones in the water: the stream
of progress just flows around them.
Where does God fit
into the Singularity?
Although the different religious traditions have somewhat
different conceptions of God, the common thread is that God represents
unlimited—infinite—levels of intelligence, knowledge,
creativity, beauty, and love. As systems evolve—through biology
and technology—we find that they become more complex, more
intelligent and more knowledgeable. They become more intricate and
more beautiful, more capable of higher emotions such as love. So
they grow exponentially in intelligence, knowledge, creativity,
beauty, and love, all of the qualities people ascribe to God without
limit. Although evolution does not reach a literally infinite level
of these attributes, it does accelerate towards ever greater levels,
so we can view evolution as a spiritual process, moving ever closer
to this ideal. The Singularity will represent an explosion of these
higher values of complexity.
So are you trying
to play God?
Actually, I’m trying to play a human. I’m
trying to do what humans do well, which is solve problems.
But will we still
be human after all these changes?
That depends on how you define human. Some observers
define human based on our limitations. I prefer to define us as
the species that seeks—and succeeds—in going beyond
Many observers point out how science has thrown us
off our pedestal, showing us that we’re not as central as
we thought, that the stars don’t circle around the Earth,
that we’re not descended from the Gods but rather from monkeys,
and before that earthworms.
All of that is true, but it turns out that we are
central after all. Our ability to create models—virtual realities—in
our brains, combined with our modest-looking thumbs, are enabling
us to expand our horizons without limit.