Computational Biology Quotes

DNA is like a computer program but far, far more advanced than any software ever created.

The information contained in an English sentence or computer software does not derive from the chemistry of the ink or the physics of magnetism, but from a source extrinsic to physics and chemistry altogether. Indeed, in both cases, the message transcends the properties of the medium. The information in DNA also transcends the properties of its material medium.

Considering that we live in an era of evolutionary everything---evolutionary biology, evolutionary medicine, evolutionary ecology, evolutionary psychology, evolutionary economics, evolutionary computing---it was surprising how rarely people thought in evolutionary terms. It was a human blind spot. We look at the world around us as a snapshot when it was really a movie, constantly changing.

By the end of this decade, computers will disappear as distinct physical objects, with displays built in our eyeglasses, and electronics woven in our clothing, providing full-immersion visual virtual reality.

Thinking is computation, I claim, but that does not mean that the computer is a good metaphor for the mind. The mind is a set of modules, but the modules are not encapsulated boxes or circumscribed swatches on the surface of the brain. The organization of our mental modules comes from our genetic program, but that does not mean that there is a gene for every trait or that learning is less important than we used to think. The mind is an adaptation designed by natural selection, but that does not mean that everything we think, feel, and do is biologically adaptive. We evolved from apes, but that does not mean we have the same minds as apes. And the ultimate goal of natural selection is to propagate genes, but that does not mean that the ultimate goal of people is to propagate genes.

The secret of DNA's success is that it carries information like that of a computer program, but far more advanced. Since experience shows that intelligence is the only presently acting cause of information, we can infer that intelligence is the best explanation for the information in DNA.

He had also gone through a bad divorce, become estranged from his only daughter and been diagnosed with skin cancer, but he insisted that all of that, however painful, was secondary to the sudden realization that it was mathematics—not nuclear weapons, computers, biological warfare or our climate Armageddon—which was changing our world to the point where, in a couple of decades at most, we would simply not be able to grasp what being human really meant.

When I started reading the literature of molecular biology, I was stunned by certain descriptions. Admittedly, I was on the lookout for anything unusual, as my investigation had led me to consider that DNA and its cellular machinery truly were an extremely sophisticated technology of cosmic origin. But as I pored over thousands of pages of biological texts, I discovered a world of science fiction that seemed to confirm my hypothesis. Proteins and enzymes were described as 'miniature robots,' ribosomes were 'molecular computers,' cells were 'factories,' DNA itself was a 'text,' a 'program,' a 'language,' or 'data.' One only had to do a literal reading of contemporary biology to reach shattering conclusions; yet most authors display a total lack of astonishment and seem to consider that life is merely 'a normal physiochemical phenomenon.

A thousand-bit quantum computer would vastly outperform any conceivable DNA computer, or for that matter any conceivable nonquantum computer.

Biological quantum coherence process is different from optical quantum coherence. Biological quantum coherence is long, and more robust in warm, noisy, and complex environment. They are the fundamental process of all living organisms.

What is truly revolutionary about molecular biology in the post-Watson-Crick era is that it has become digital...the machine code of the genes is uncannily computer-like.' -Richard Dawkins

Electronic circuits are millions of times faster than our biological circuits. At first we will have to devote all of this speed increase to compensating for the relative lack of parallelism in our computers, but ultimately the digital neocortex will be much faster than the biological variety and will only continue to increase in speed.

I explained my opinion of the ship’s logic. “That is a strange designation,” said the ship. “While I have certain organic elements incorporated into my substructure and decentralized DNA computing components, I am not—in the strictest sense of the term—a biological organism. I have no digestive system. No need for elimination, other than the occasional waste gas and passenger effluvium. Therefore, I have no anus in either real or figurative terms. Therefore, I hardly believe I could qualify to be called an …” “Shut up,” I said.

How Smart Is a Rock? To appreciate the feasibility of computing with no energy and no heat, consider the computation that takes place in an ordinary rock. Although it may appear that nothing much is going on inside a rock, the approximately 1025 (ten trillion trillion) atoms in a kilogram of matter are actually extremely active. Despite the apparent solidity of the object, the atoms are all in motion, sharing electrons back and forth, changing particle spins, and generating rapidly moving electromagnetic fields. All of this activity represents computation, even if not very meaningfully organized. We’ve already shown that atoms can store information at a density of greater than one bit per atom, such as in computing systems built from nuclear magnetic-resonance devices. University of Oklahoma researchers stored 1,024 bits in the magnetic interactions of the protons of a single molecule containing nineteen hydrogen atoms.51 Thus, the state of the rock at any one moment represents at least 1027 bits of memory.

... we have created a man with not one brain but two. ... This new brain is intended to control the biological brain. ... The patient's biological brain is the peripheral terminal -- the only peripheral terminal -- for the new computer. ... And therefore the patient's biological brain, indeed his whole body, has become a terminal for the new computer. We have created a man who is one single, large, complex computer terminal. The patient is a read-out device for the new computer, and is helpless to control the readout as a TV screen is helpless to control the information presented on it.

Eyes often have an implicit censorious power.22 Post a large picture of a pair of eyes at a bus stop (versus a picture of flowers), and people become more likely to clean up litter. Post a picture of eyes in a workplace coffee room, and the money paid on the honor system triples. Show a pair of eyes on a computer screen and people become more generous in online economic games.

Real arms races are run by highly intelligent, bespectacled engineers in glass offices thoughtfully designing shiny weapons on modern computers. But there's no thinking in the mud and cold of nature's trenches. At best, weapons thrown together amidst the explosions and confusion of smoky battlefields are tiny variations on old ones, held together by chewing gum. If they don't work, then something else is thrown at the enemy, including the kitchen sink - there's nothing "progressive" about that. At its usual worst, trench warfare is fought by attrition. If the enemy can be stopped or slowed by burning your own bridges and bombing your own radio towers and oil refineries, then away they go. Darwinian trench warfare does not lead to progress - it leads back to the Stone Age.

There are no inherent barriers to our being able to reverse engineer the operating principles of human intelligence and replicate these capabilities in the more powerful computational substrates that will become available in the decades ahead. The human brain is a complex hierarchy of complex systems, but it does not represent a level of complexity beyond what we are already capable of handling.

We're presently in the midst of a third intellectual revolution. The first came with Newton: the planets obey physical laws. The second came with Darwin: biology obeys genetic laws. In today’s third revolution, were coming to realize that even minds and societies emerge from interacting laws that can be regarded as computations. Everything is a computation.

Ultimately, we will be able to port our mental processes to a more suitable computational substrate. Then our minds won’t have to stay so small.

b × c × d = ahh! Biological knowledge multiplied by Computing power multiplied by Data equals Ability to Hack Humans.

Biological knowledge multiplied by Computing power multiplied by Data equals Ability to Hack Humans.

On the other hand it is possible that human control over the machines may be retained. In that case the average man may have control over certain private machines of his own, such as his car of his personal computer, but control over large systems of machines will be in the hands of a tiny elite -- just as it is today, but with two difference. Due to improved techniques the elite will have greater control over the masses; and because human work will no longer be necessary the masses will be superfluous, a useless burden on the system. If the elite is ruthless the may simply decide to exterminate the mass of humanity. If they are humane they may use propaganda or other psychological or biological techniques to reduce the birth rate until the mass of humanity becomes extinct, leaving the world to the elite. Or, if the elite consist of soft-hearted liberals, they may decide to play the role of good shepherds to the rest of the human race. They will see to it that everyone's physical needs are satisfied, that all children are raised under psychologically hygienic conditions, that everyone has a wholesome hobby to keep him busy, and that anyone who may become dissatisfied undergoes "treatment" to cure his "problem." Of course, life will be so purposeless that people will have to be biologically or psychologically engineered either to remove their need for the power process or to make them "sublimate" their drive for power into some harmless hobby. These engineered human beings may be happy in such a society, but they most certainly will not be free. They will have been reduced to the status of domestic animals.

Even the tiniest chunk of code, like Coronavirus (COVID-19), may cause a major disruptive impact on the global operating system, something that was suddenly revealed to the public awareness in early 2020.

Wise people throughout history have been those who saw that while life is real, life’s problems are an illusion, they are thought-created. These people know that we manufacture and blow problems way out of proportion through our own ability to think. They also know that if we can step outside the boundaries of our own thinking, we can find the answer we are looking for. This, in a nutshell, is wisdom: the ability to see an answer without having to think of an answer. Wisdom is the ‘ah ha, that’s so obvious’ experience most of us have had many times. Few people seem to understand that this voice is always available to us. Wisdom is indeed your inner sense of knowing. It is true mental health, a peaceful state of mind where answers to questions are as plentiful as the problems you see when you aren’t experiencing wisdom. It’s as if wisdom lies in the space between your thoughts, in those quiet moments when your ‘biological computer’ is turned off.

A solitary ant, afield, cannot be considered to have much of anything on his mind; indeed, with only a few neurons strung together by fibers, he can’t be imagined to have a mind at all, much less a thought. He is more like a ganglion on legs. Four ants together, or ten, encircling a dead moth on a path, begin to look more like an idea. They fumble and shove, gradually moving the food toward the Hill, but as though by blind chance. It is only when you watch the dense mass of thousands of ants, crowded together around the Hill, blackening the ground, that you begin to see the whole beast, and now you observe it thinking, planning, calculating. It is an intelligence, a kind of live computer, with crawling bits for its wits.

Most of the complexity of a human neuron is devoted to maintaining its life-support functions, not its information-processing capabilities. Ultimately, we will be able to port our mental processes to a more suitable computational substrate. Then our minds won’t have to stay so small.

Yet once biologists concluded that organisms are algorithms, they dismantled the wall between the organic and the inorganic, turned the computer revolution from a purely mechanical affair into a biological cataclysm, and shifted authority from individual humans to networked algorithms.

The fourth industrial revolution, however, is not only about smart and connected machines and systems. Its scope is much wider. Occurring simultaneously are waves of further breakthroughs in areas ranging from gene sequencing to nanotechnology, from renewables to quantum computing. It is the fusion of these technologies and their interaction across the physical, digital and biological domains that make the fourth industrial revolution fundamentally different from previous revolutions. In

I think that the people that say we will never develop computer intelligence — they merely prove that some biological systems don't have much intelligence.

A “better” biological virus — like a computer virus — will perhaps just make its host sick, but still well enough to keep spreading the virus

b×c×d = ahh! Biological knowledge multiplied by Computing power multiplied by Data equals Ability to Hack Humans.

To put it succinctly, we can use the following formula: b×c×d = ahh! Biological knowledge multiplied by Computing power multiplied by Data equals Ability to Hack Humans.

Envisioning fungi as nanoconductors in mycocomputers, Gorman (2003) and his fellow researchers at Northwestern University have manipulated mycelia of Aspergillus niger to organize gold into its DNA, in effect creating mycelial conductors of electrical potentials. NASA reports that microbiologists at the University of Tennessee, led by Gary Sayler, have developed a rugged biological computer chip housing bacteria that glow upon sensing pollutants, from heavy metals to PCBs (Miller 2004). Such innovations hint at new microbiotechnologies on the near horizon. Working together, fungal networks and environmentally responsive bacteria could provide us with data about pH, detect nutrients and toxic waste, and even measure biological populations.

Our human intelligence is based on computational processes that we are learning to understand. We will ultimately multiply our intellectual powers by applying and extending the methods of human intelligence using the vastly greater capacity of nonbiological computation. So to consider the ultimate limits of computation is really to ask: what is the destiny of our civilization?

In the history of ideas, it's repeatedly happened that an idea, developed in one area for one purpose, finds an unexpected application elsewhere. Concepts developed purely for philosophy of mathematics turned out to be just what you needed to build a computer. Statistical formulae for understanding genetic change in biology are now applied in both economics and in programming.

Where a calculator on the ENIAC is equipped with 18,000 vacuum tubes and weighs 30 tons, computers in the future may have only 1,000 vacuum tubes and perhaps weigh 1.5 tons. —POPULAR MECHANICS,

the groundbreakers in many sciences were devout believers. Witness the accomplishments of Nicolaus Copernicus (a priest) in astronomy, Blaise Pascal (a lay apologist) in mathematics, Gregor Mendel (a monk) in genetics, Louis Pasteur in biology, Antoine Lavoisier in chemistry, John von Neumann in computer science, and Enrico Fermi and Erwin Schrodinger in physics. That’s a short list, and it includes only Roman Catholics; a long list could continue for pages. A roster that included other believers—Protestants, Jews, and unconventional theists like Albert Einstein, Fred Hoyle, and Paul Davies—could fill a book.

In accordance with the law of accelerating returns, paradigm shift (also called innovation) turns the S-curve of any specific paradigm into a continuing exponential. A new paradigm, such as three-dimensional circuits, takes over when the old paradigm approaches its natural limit, which has already happened at least four times in the history of computation. In such nonhuman species as apes, the mastery of a toolmaking or -using skill by each animal is characterized by an S-shaped learning curve that ends abruptly; human-created technology, in contrast, has followed an exponential pattern of growth and acceleration since its inception.

Nonetheless, the appeal of Copenhagen makes some sense, seen in this light. Quantum physics drove much of the technological and scientific progress of the past ninety years: nuclear power, modern computers, the Internet. Quantum-driven medical imaging changed the face of health care; quantum imaging techniques at smaller scales have revolutionized biology and kicked off the entirely new field of molecular genetics. The list goes on. Make some kind of personal peace with Copenhagen, and contribute to this amazing revolution in science . . . or take quantum physics seriously, and come face-to-face with a problem that even Einstein couldn't solve. Shutting up never looked so good.

We’ve known since 2007 that there’s superposition in chlorophyll, for instance. Photosynthesis has a ninety-five percent energy-transfer efficiency rate, which is better than anything we can engineer. Plants achieve that by using superposition to simultaneously try all the possible pathways between their light-collecting molecules and their reaction-center proteins so that energy is always sent down the most efficient route; it’s a form of biological quantum computing.

The truth is that anxiety is at once a function of biology and philosophy, body and mind, instinct and reason, personality and culture. Even as anxiety is experienced at a spiritual and psychological level, it is scientifically measurable at the molecular level and the physiological level. It is produced by nature and it is produced by nurture. It’s a psychological phenomenon and a sociological phenomenon. In computer terms, it’s both a hardware problem (I’m wired badly) and a software problem (I run faulty logic programs that make me think anxious thoughts). The origins of a temperament are many faceted; emotional dispositions that may seem to have a simple, single source—a bad gene, say, or a childhood trauma—may not.

Instead of thinking of the brain as biological meat computer, Strassman offers the “receiver of reality” model for brain function. Like a television receives its content from the airwaves, consciousness or the mind resides outside of our bodies.

To establish evolutionary interrelatedness invariably requires exhibiting similarities between organisms. Within Darwinism, there's only one way to connect such similarities, and that's through descent with modification driven by the Darwinian mechanism. But within a design-theoretic framework, this possibility, though not precluded, is also not the only game in town. It's possible for descent with modification instead to be driven by telic processes inherent in nature (and thus by a form of design). Alternatively, it's possible that the similarities are not due to descent at all but result from a similarity of conception, just as designed objects like your TV, radio, and computer share common components because designers frequently recycle ideas and parts. Teasing apart the effects of intelligent and natural causation is one of the key questions confronting a design-theoretic research program. Unlike Darwinism, therefore, intelligent design has no immediate and easy answer to the question of common descent. Darwinists necessarily see this as a bad thing and as a regression to ignorance. From the design theorists' perspective, however, frank admissions of ignorance are much to be preferred to overconfident claims to knowledge that in the end cannot be adequately justified. Despite advertisements to the contrary, science is not a juggernaut that relentlessly pushes back the frontiers of knowledge. Rather, science is an interconnected web of theoretical and factual claims about the world that are constantly being revised and for which changes in one portion of the web can induce radical changes in another. In particular, science regularly confronts the problem of having to retract claims that it once confidently asserted.

The influx of competing messages that we receive whenever we go online not only overloads our working memory; it makes it much harder for our frontal lobes to concentrate our attention on any one thing. The process of memory consolidation can’t even get started. And, thanks once again to the plasticity of our neuronal pathways, the more we use the Web, the more we train our brain to be distracted—to process information very quickly and very efficiently but without sustained attention. That helps explain why many of us find it hard to concentrate even when we’re away from our computers. Our brains become adept at forgetting, inept at remembering. Our growing dependence on the Web’s information stores may in fact be the product of a self-perpetuating, self-amplifying loop. As our use of the Web makes it harder for us to lock information into our biological memory, we’re forced to rely more and more on the Net’s capacious and easily searchable artificial memory, even if it makes us shallower thinkers.

[W]hen food is placed at the start and end points of the maze, the slime mold withdraws from the dead-end corridors and shrinks its body to a tube spanning the shortest path between food sources. The single-celled slime solves the maze in this way each time it is tested.”23 Toshiyuki Nakagaki, the researcher conducting the study, commented that Even for humans it is not easy to solve a maze. But the plasmodium of true slime mold, an amoeba-like organism, has shown an amazing ability to do so. This implies that an algorithm and a high computing capacity are included in the unicellular organism.24 This capacity for mathematical differentiation and computation is wide spread. All self-organized biological systems possess it. One of the more amazing examples is the Clark’s Nutcracker.

Synthetic biology56 is built around the idea that DNA is essentially software—nothing more than a four-letter code arranged in a specific order. Much like with computers, the code drives the machine. In biology, the order of the code governs the cell’s manufacturing processes, instructing it to make specific proteins and such. But, as with all software, DNA can be reprogrammed. Nature’s original code can be swapped out for new, human-written code. We can co-opt the machinery of life, telling it to produce—well, whatever we can think of.

Yet once biologists concluded that organisms are algorithms, they dismantled the wall between the organic and inorganic, turned the computer revolution from a purely mechanical affair into a biological cataclysm, and shifted authority from individual humans to networked algorithms.

The externalization of memory [via the use of external symbolic storage systems] has altered the actual memory architecture within which humans think, which is changing the role of biological memory, the way in which the human brain deploys its resources, and the form of modern culture.

Thanks to our growing understanding of human biology, medicine can keep us alive long enough for our minds and ‘authentic selves’ to disintegrate and dissolve. All too often, what’s left is a collection of dysfunctional biological systems kept going by a collection of monitors, computers and pumps.

almost every living cell there was already a functioning computer with a huge memory? A mammalian cell had a DNA complement of several billion base pairs, each acting as a piece of information. What was reproduction, after all, but a computerized biological process of enormous complexity and reliability?

Often people think of developments in computation as arising when we make our computers more blazingly fast, so they can compute more stuff, bigger data. It's actually just as important to prune away big parts of the data that aren't relevant to the problem at hand! The fastest computation is the one you don't do.

Our brains are designed to arrive at an accurate picture of the world, and to use that accurate picture to act on the world effectively, at least overall and in the long run. The same computational and neurological capacities that let us make discoveries about physics or biology also let us make discoveries about love.

compute for a while, print out the results, inspect what they have produced, add some marks in the margin, circulate copies among colleagues, and then start the process again. That’s not how computers work—but it is how we work; we are “intrinsically loopy creatures,” as Clark likes to say. Something about our biological intelligence benefits from being rotated in and out of internal and external modes of cognition, from being passed among brain, body, and world. This means we should resist the urge to shunt our thinking along the linear path appropriate to a computer—input, output, done—and instead allow it to take a more winding route.

perform the equivalent of all human thought over the last ten thousand years (assumed at ten billion human brains for ten thousand years) in ten microseconds.64 If we examine the “Exponential Growth of Computing” chart (p. 70), we see that this amount of computing is estimated to be available for one thousand dollars by 2080.

Fredkin believes that the universe is very literally a computer and that it is being used by someone, or something, to solve a problem. It sounds like a good-news/bad-news joke: the good news is that our lives have purpose; the bad news is that their purpose is to help some remote hacker estimate pi to nine jillion decimal places.

Exoteric machines - esoteric machines. They say the computer is an improved form of typewriter. Not a bit of it. I collude with my typewriter, but the relationship is otherwise clear and distant. I know it is a machine; it knows it is a machine. There is nothing here of the interface, verging on biological confusion, between a computer thinking it is a brain and me thinking I am a computer. The same familiarity with good old television, where I was and remained a spectator. It was an esoteric machine, whose status as machine I respected. Nothing there of all these screens and interactive devices, including the 'smart' car of the future and the 'smart' house. Even the mobile phone, that incrustation of the network in your head, even the skateboard and rollerblades - mobility aids - are of a quite different generation from the good old static telephone or the velocipedic machine. New manners and a new morality are emerging as a result of this organic confusion between man and his prostheses - a confusion which puts an end to the instrumental pact and the integrity of the machine itself.

I believe that the mechanical model for understanding nature is a metaphor that science has got stuck on: this prevailing idea that humans are machines, biological robots with computer-like brains. This belief will, to the advanced species that we are evolving into, seem as absurd as the flat-earth theories that we scoff at now. ========== Revolution (Russell Brand)

Based on the above analyses, it is reasonable to expect the hardware that can emulate human-brain functionality to be available for approximately one thousand dollars by around 2020. As we will discuss in chapter 4, the software that will replicate that functionality will take about a decade longer. However, the exponential growth of the price-performance, capacity, and speed of our hardware technology will continue during that period, so by 2030 it will take a village of human brains (around one thousand) to match a thousand dollars’ worth of computing. By 2050, one thousand dollars of computing will exceed the processing power of all human brains on Earth. Of course, this figure includes those brains still using only biological neurons.

Nothing's immortal on a road trip of a billion years. The universe runs down in stop-motion around you, your backups' backups' backups need backups. Not even the error-correcting replication strategies cadged from biology can keep the mutations at bay forever. It was true for us meatsicles cycling through mayfly moments every thousand years; it was just as true for the hardware.

How do we learn? Is there a better way? What can we predict? Can we trust what we’ve learned? Rival schools of thought within machine learning have very different answers to these questions. The main ones are five in number, and we’ll devote a chapter to each. Symbolists view learning as the inverse of deduction and take ideas from philosophy, psychology, and logic. Connectionists reverse engineer the brain and are inspired by neuroscience and physics. Evolutionaries simulate evolution on the computer and draw on genetics and evolutionary biology. Bayesians believe learning is a form of probabilistic inference and have their roots in statistics. Analogizers learn by extrapolating from similarity judgments and are influenced by psychology and mathematical optimization.

Fredkin [...] praat over een interessant kenmerk van computerprogramma's, waaronder cellulaire automaten: er is geen kortere route mogelijk naar wat de uitkomst wordt. Dit is het wezenlijke verschil tussen de 'analytische' benadering van de traditionele wiskunde, inclusief differentiële vergelijkingen, en de 'computer'-benadering met algoritmes. Je kunt een toekomstige toestand van een systeem voorspellen zonder alle tussenstappen te kennen als je de analytische methode gebruikt. Maar bij cellulaire automaten moet je alle tussenstappen doorrekenen om te weten hoe de uitkomst zal zijn: je kunt de toekomst niet voorspellen, behalve door de toekomst af te wachten. [...] Fredkin legt uit: 'je kunt het antwoord op een vraag niet sneller kennen dan wanneer je volgt wat er gebeurt.' [...] Fredkin gelooft dat het universum letterlijk een computer is en dat het gebruikt wordt door iets of iemand om een probleem op te lossen. Het klinkt als een grap met goed en slecht nieuws: het goede nieuws is dat onze levens een doel hebben; het slechte nieuws is dat onze levens het doel zijn van een of andere hacker ver weg die pi wil uitrekenen met een oneindig groot getal achter de komma.

Technology, I said before, is most powerful when it enables transitions—between linear and circular motion (the wheel), or between real and virtual space (the Internet). Science, in contrast, is most powerful when it elucidates rules of organization—laws—that act as lenses through which to view and organize the world. Technologists seek to liberate us from the constraints of our current realities through those transitions. Science defines those constraints, drawing the outer limits of the boundaries of possibility. Our greatest technological innovations thus carry names that claim our prowess over the world: the engine (from ingenium, or “ingenuity”) or the computer (from computare, or “reckoning together”). Our deepest scientific laws, in contrast, are often named after the limits of human knowledge: uncertainty, relativity, incompleteness, impossibility. Of all the sciences, biology is the most lawless; there are few rules to begin with, and even fewer rules that are universal. Living beings must, of course, obey the fundamental rules of physics and chemistry, but life often exists on the margins and interstices of these laws, bending them to their near-breaking limit. The universe seeks equilibriums; it prefers to disperse energy, disrupt organization, and maximize chaos. Life is designed to combat these forces. We slow down reactions, concentrate matter, and organize chemicals into compartments; we sort laundry on Wednesdays. “It sometimes seems as if curbing entropy is our quixotic purpose in the universe,” James Gleick wrote. We live in the loopholes of natural laws, seeking extensions, exceptions, and excuses.

For example, a computer virus is a program that will make copies of itself in the memory of a computer, and will transfer itself to other computers. Thus it fits the definition of a living system that I have given. Like a biological virus, it is a rather degenerate form, because it contains only instructions or genes, and doesn’t have any metabolism of its own. Instead, it reprograms the metabolism of the host computer, or cell.

To see what happens in the real world when an information cascade takes over, and the bidders have almost nothing but one another’s behavior to estimate an item’s value, look no further than Peter A. Lawrence’s developmental biology text The Making of a Fly, which in April 2011 was selling for $23,698,655.93 (plus $3.99 shipping) on Amazon’s third-party marketplace. How and why had this—admittedly respected—book reached a sale price of more than $23 million? It turns out that two of the sellers were setting their prices algorithmically as constant fractions of each other: one was always setting it to 0.99830 times the competitor’s price, while the competitor was automatically setting their own price to 1.27059 times the other’s. Neither seller apparently thought to set any limit on the resulting numbers, and eventually the process spiraled totally out of control.

Uploading your brain entails recording all the details of your brain, and then using them to simulate your brain on a computer. The simulator would be identical to your brain, so “you” would then live in the computer. The goal is to separate your mental and intellectual “you” from your biological body. This way, you can live indefinitely, including in a computer that is remote from Earth. You wouldn’t die if Earth became uninhabitable.

The world has been changing even faster as people, devices and information are increasingly connected to each other. Computational power is growing and quantum computing is quickly being realised. This will revolutionise artificial intelligence with exponentially faster speeds. It will advance encryption. Quantum computers will change everything, even human biology. There is already one technique to edit DNA precisely, called CRISPR. The basis of this genome-editing technology is a bacterial defence system. It can accurately target and edit stretches of genetic code. The best intention of genetic manipulation is that modifying genes would allow scientists to treat genetic causes of disease by correcting gene mutations. There are, however, less noble possibilities for manipulating DNA. How far we can go with genetic engineering will become an increasingly urgent question. We can’t see the possibilities of curing motor neurone diseases—like my ALS—without also glimpsing its dangers. Intelligence is characterised as the ability to adapt to change. Human intelligence is the result of generations of natural selection of those with the ability to adapt to changed circumstances. We must not fear change. We need to make it work to our advantage. We all have a role to play in making sure that we, and the next generation, have not just the opportunity but the determination to engage fully with the study of science at an early level, so that we can go on to fulfil our potential and create a better world for the whole human race. We need to take learning beyond a theoretical discussion of how AI should be and to make sure we plan for how it can be. We all have the potential to push the boundaries of what is accepted, or expected, and to think big. We stand on the threshold of a brave new world. It is an exciting, if precarious, place to be, and we are the pioneers. When we invented fire, we messed up repeatedly, then invented the fire extinguisher. With more powerful technologies such as nuclear weapons, synthetic biology and strong artificial intelligence, we should instead plan ahead and aim to get things right the first time, because it may be the only chance we will get. Our future is a race between the growing power of our technology and the wisdom with which we use it. Let’s make sure that wisdom wins.

In history and in evolution, progress is always a futile, Sisyphean struggle to stay in the same relative place by getting ever better at things. Cars move through the congested streets of London no faster than horse-drawn carriages did a century ago. Computers have no effect on productivity because people learn to complicate and repeat tasks that have been made easier.13 This concept, that all progress is relative, has come to be known in biology by the name of the Red Queen, after a chess piece that Alice meets in Through the Looking-Glass, who perpetually runs without getting very far because the landscape moves with her. It is an increasingly influential idea in evolutionary theory, and one that will recur throughout the book. The faster you run, the more the world moves with you and the less you make progress. Life is a chess tournament in which if you win a game, you start the next game with the handicap of a missing pawn.

If biological algorithms are the important part of what makes us who we are, rather than the physical stuff, then it’s a possibility that we will someday be able to copy our brains, upload them, and live forever in silica. But there’s an important question here: is it really you? Not exactly. The uploaded copy has all your memories and believes it was you, just there, standing outside the computer, in your body. Here’s the strange part: if you die and we turn on the simulation one second later, it would be a transfer. It would be no different to beaming up in Star Trek, when a person is disintegrated, and then a new version is reconstituted a moment later. Uploading may not be all that different from what happens to you each night when you go to sleep: you experience a little death of your consciousness, and the person who wakes up on your pillow the next morning inherits all your memories, and believes him or herself to be you. Are

Alan Turing appears to be becoming a symbol of the shift towards computing, not least because of his attitude of open-minded defiance of convention and conventional thinking. Not only did he conceptualise the modern computer – imagining a simple machine that could use different programmes – but he put his thinking into practice in the great code breaking struggle with the Nazis in World War II, and followed it up with pioneering early work in the mathematics of biology and chaos.

Selection is also important in non-biological contexts. In designing machines and computer programs, it has been found that a very efficient way to find the optimal design is to successively make small, random changes to the design, keeping versions that do the job well, and discarding others. This is increasingly being used to solve difficult design problems for complex systems. In this process, the engineer does not have a design in mind, but only the desired function. Adaptations

Like a biological virus, it is a rather degenerate form, because it contains only instructions or genes, and doesn’t have any metabolism of its own. Instead, it reprograms the metabolism of the host computer, or cell. Some people have questioned whether viruses should count as life, because they are parasites, and cannot exist independently of their hosts. But then most forms of life, ourselves included, are parasites, in that they feed off and depend for their survival on other forms of life. I think computer viruses should count as life.

... the reason why we find some things intuitively easy to grasp and others hard, is that our brains are themselves evolved organs: on-board computers, evolved to help us survive in a world (...) where the objects that mattered to our survival were neither very large nor very small; a world where things either stood still or moved slowly compared with the speed of light; and where the very improbable could safely be treated as impossible. Our mental burka window is narrow because it didn't need to be any wider in order to assist our ancestors to survive.

Dataism is most firmly entrenched in its two mother disciplines: computer science and biology. Of the two biology is the more important. It was biology’s embrace of Dataism that turned a limited breakthrough in computer science into a world-shattering cataclysm that may completely transform the very nature of life. You may not agree with the idea that organisms are algorithms, and that giraffes, tomatoes and human beings are just different methods for processing data. But you should know that this is current scientific dogma, and it is changing our world beyond recognition.

The ideal elder may suffer from bodily ailments and weaknesses, but his mind is quick and sharp, and he has eighty years of insights to dispense. He knows exactly what’s what, and always has astute advice for the grandchildren and other visitors. Twenty-first-century octogenarians don’t always conform to that image. Thanks to our growing understanding of human biology, medicine can keep us alive long enough for our minds and ‘authentic selves’ to disintegrate and dissolve. All too often, what’s left is a collection of dysfunctional biological systems kept going by a collection of monitors, computers and pumps.

In a way, the human race needs to improve its mental and physical qualities if it is to deal with the increasingly complex world around it and meet new challenges like space travel. And it also needs to increase its complexity if biological systems are to keep ahead of electronic ones. At the moment computers have an advantage of speed, but they show no sign of intelligence. This is not surprising because our present computers are less complex than the brain of an earthworm, a species not noted for its intellectual powers. But computers roughly obey a version of Moore’s Law, which says that their speed and complexity double every eighteen months. It is one of these exponential growths that clearly cannot continue indefinitely, and indeed it has already begun to slow. However, the rapid pace of improvement will probably continue until computers have a similar complexity to the human brain. Some people say that computers can never show true intelligence, whatever that may be. But it seems to me that if very complicated chemical molecules can operate in humans to make them intelligent, then equally complicated electronic circuits can also make computers act in an intelligent way. And if they are intelligent they can presumably design computers that have even greater complexity and intelligence.

Astounding, really, that Michel could consider psychology any kind of science at all. So much of it consisted of throwing together. Of thinking of the mind as a steam engine, the mechanical analogy most ready to hand during the birth of modern psychology. People had always done that when they thought about the mind: clockwork for Descartes, geological changes for the early Victorians, computers or holography for the twentieth century, AIs for the twenty-first…and for the Freudian traditionalists, steam engines. Application of heat, pressure buildup, pressure displacement, venting, all shifted into repression, sublimation, the return of the repressed. Sax thought it unlikely steam engines were an adequate model for the human mind. The mind was more like—what?—an ecology—a fellfield—or else a jungle, populated by all manner of strange beasts. Or a universe, filled with stars and quasars and black holes. Well—a bit grandiose, that—really it was more like a complex collection of synapses and axons, chemical energies surging hither and yon, like weather in an atmosphere. That was better—weather—storm fronts of thought, high-pressure zones, low-pressure cells, hurricanes—the jet streams of biological desires, always making their swift powerful rounds…life in the wind. Well. Throwing together. In fact the mind was poorly understood.

In the coming decades, it is likely that we will see more Internet-like revolutions, in which technology steals a march on politics. Artificial intelligence and biotechnology might soon overhaul our societies and economies – and our bodies and minds too – but they are hardly a blip on our political radar. Our current democratic structures just cannot collect and process the relevant data fast enough, and most voters don’t understand biology and cybernetics well enough to form any pertinent opinions. Hence traditional democratic politics loses control of events, and fails to provide us with meaningful visions for the future. That doesn’t mean we will go back to twentieth-century-style dictatorships. Authoritarian regimes seem to be equally overwhelmed by the pace of technological development and the speed and volume of the data flow. In the twentieth century, dictators had grand visions for the future. Communists and fascists alike sought to completely destroy the old world and build a new world in its place. Whatever you think about Lenin, Hitler or Mao, you cannot accuse them of lacking vision. Today it seems that leaders have a chance to pursue even grander visions. While communists and Nazis tried to create a new society and a new human with the help of steam engines and typewriters, today’s prophets could rely on biotechnology and super-computers.

He postulated that many neurons can combine into a coalition, becoming a single processing unit. The connection patterns of these units, which can change, make up the algorithms (which can also change with the changing connection patterns) that determine the brain’s response to a stimulus. From this idea came the mantra “Cells that fire together wire together.” According to this theory, learning has a biological basis in the “wiring” patterns of neurons. Hebb noted that the brain is active all the time, not just when stimulated; inputs from the outside can only modify that ongoing activity. Hebb’s proposal made sense to those designing artificial neural networks, and it was put to use in computer programs.

And, thanks once again to the plasticity of our neuronal pathways, the more we use the Web, the more we train our brain to be distracted—to process information very quickly and very efficiently but without sustained attention. That helps explain why many of us find it hard to concentrate even when we’re away from our computers. Our brains become adept at forgetting, inept at remembering. Our growing dependence on the Web’s information stores may in fact be the product of a self-perpetuating, self-amplifying loop. As our use of the Web makes it harder for us to lock information into our biological memory, we’re forced to rely more and more on the Net’s capacious and easily searchable artificial memory, even if it makes us shallower thinkers.

There’s an old phrase,” Matthew says. “Knowledge is power. Power to do evil, like Jeanine…or power to do good, like what we’re doing. Power itself is not evil. So knowledge itself is not evil.” “I guess I grew up suspicious of both. Power and knowledge,” I say. “To the Abnegation, power should only be given to people who don’t want it.” “There’s something to that,” Matthew says. “But maybe it’s time to grow out of that suspicion.” He reaches under the desk and takes out a book. It is thick, with a worn cover and frayed edges. On it is printed HUMAN BIOLOGY. “It’s a little rudimentary, but this book helped to teach me that it is to be human,” he says. “To be such a complicated, mysterious piece of biological machinery, and more amazing still, to have the capacity to analyze that machinery! That is a special thing, unprecedented in all of evolutionary history. Our ability to know about ourselves and the world is what makes us human.” He hands me the book and turns back to the computer. I look down at the worn cover and run my fingers along the edge of the pages. He makes the acquisition of knowledge feel like a secret, beautiful thing, and an ancient thing. I feel like, if I read this book, I can reach backward through all the generations of humanity to the very first one, whenever it was--that I can participate in something many times larger and older than myself. “Thank you,” I say, and it’s not for the book. It’s for giving something back to me, something I lost before I was able to really have it.

Still, it is possible to outlaw entire technologies. In 2006 Kevin Kelly, the former editor of Wired magazine, did a study of the effectiveness of technology prohibitions across the last thousand years, beginning in the year 1000. During this period governments had banned numerous technologies and inventions, including crossbows, guns, mines, nuclear bombs, electricity, automobiles, large sailing ships, bathtubs, blood transfusions, vaccines, television, computers, and the Internet. Kelly found that few technology prohibitions had any staying power and that in general, the more recent the prohibition, the shorter its duration. Figure Epilogue Kevin Kelly’s chart of the duration of a technology prohibition plotted against the year in which it was imposed.

As technology enables us to upgrade humans, overcome old age and find the key to happiness, won’t people care less about fictional gods, nations and corporations, and focus instead on deciphering the physical and biological reality? It might seem so, but in fact things are far more complicated. Modern science certainly changed the rules of the game, yet it did not simply replace myths with facts. Myths continue to dominate humankind, and science only makes these myths stronger. Instead of destroying the intersubjective reality, science will enable it to control the objective and subjective realities more completely than ever before. Thanks to computers and bioengineering, the difference between fiction and reality will blur, as people reshape reality to match their pet fictions.

The DNA-RNA apparatus isn't the whole secret of life, but a sort of computer program by which the real secret, the control system, ex-presses its pattern in terms of living cells.This pattern is part of what many people mean by the soul, which somany philosophies have tried to explicate. However, most of the pro-posed answers haven't been connected with the physical world of biology in a way that offered a toehold for experiment. Like many attempts, the latest major scientific guess, the morphogenetic field proposed by Paul Weiss in 1939, was just a restatement of the problem, though a useful one. Weiss conjectured that development was guided by some sort of field projected from the fertilized egg. As the dividing cell mass became an embryo and then an adult, the field changed its shape and somehow led the cells onward.

Whereas new genes arise solely by chance through random mutations, humans often generate cultural variations intentionally. Inventions like farming, computers, and Marxism were created through ingenuity and for a purpose. In addition, memes are transmitted not just from parents to offspring, but from multiple sources. Reading this book is just one of your many horizontal exchanges of information today. Finally, although cultural evolution can occur randomly (think of fashions like tie width or skirt length), cultural change often happens through an agent of change, such as a persuasive leader, television, or a community’s collective desire to solve a challenge like hunger, disease, or the threat of Russians on the moon. Together, these differences make cultural evolution a faster and often more potent cause of change than biological evolution.

It is in our collective behavior that we are the most mysterious. We won't be able to construct machines like ourselves until we've understood this, and we're not even close. All we know is the phenomenon: we spend our time sending messages to each other, talking and trying to listen at the same time, exchanging information. This seems to be our most urgent biological function; it is what we do with our lives. By the time we reach the end, each of us has taken in a staggering store, enough to exhaust any computer, much of it incomprehensible, and we generally manage to put out even more than we take in. Information is our source of energy; we are driven by it. It has become a tremendous enterprise, a kind of energy system on its own. All 3 billion of us are being connected by telephones, radios, television sets, airplanes, satellites, harangues on public-address systems, newspapers, magazines, leaflets dropped from great heights, words got in edgewise. We are becoming a grid, a circuitry around the earth.

Superimposed on the hierarchical framework of defined components of a cell there is another layer. This second layer is highly flexible and can take on an almost infinite variety of forms, like soft and responsive flesh on a bony skeleton. The deep question is whether this higher layer in the construction of cells is itself organized. Are there hierarchies, or at least rules, in the protein-modifying, RNA splicing, gene-regulating processes of a cell? If so, then we have a chance of understanding them. If not, we will never know exactly what a cell will do next. If the detailed chemistry of the cell is simply the outcome of a historical ragbag of ad hoc interactions, then it will be no more predictable than the weather. I do not have an answer to this question. But two features of cells might be relevant. One is a sense of time, or causation - knowledge of the way that things in the real world follow in a certain sequence. The other is integrity, which enables a cell to distinguish between what belongs to itself and what belongs to the outside world.

A living being like you or me usually has two elements: a set of instructions that tell the system how to keep going and how to reproduce itself, and a mechanism to carry out the instructions. In biology, these two parts are called genes and metabolism. But it is worth emphasising that there need be nothing bio-logical about them. For example, a computer virus is a program that will make copies of itself in the memory of a computer, and will transfer itself to other computers. Thus it fits the definition of a living system that I have given. Like a biological virus, it is a rather degenerate form, because it contains only instructions or genes, and doesn’t have any metabolism of its own. Instead, it reprograms the metabolism of the host computer, or cell. Some people have questioned whether viruses should count as life, because they are parasites, and cannot exist independently of their hosts. But then most forms of life, ourselves included, are parasites, in that they feed off and depend for their survival on other forms of life. I think computer viruses should count as life. Maybe it says something about human nature that the only form of life we have created so far is purely destructive. Talk about creating life in our own image. I shall return to electronic forms of life later on.

That’s why traditional religions offer no real alternative to liberalism. Their scriptures don’t have anything to say about genetic engineering or artificial intelligence, and most priests, rabbis and muftis don’t understand the latest breakthroughs in biology and computer science. For if you want to understand these breakthroughs, you don’t have much choice – you need to spend time reading scientific articles and conducting lab experiments instead of memorising and debating ancient texts. That doesn’t mean liberalism can rest on its laurels. True, it has won the humanist wars of religion, and as of 2016 it has no viable alternative. But its very success may contain the seeds of its ruin. The triumphant liberal ideals are now pushing humankind to reach for immortality, bliss and divinity. Egged on by the allegedly infallible wishes of customers and voters, scientists and engineers devote more and more energies to these liberal projects. Yet what the scientists are discovering and what the engineers are developing may unwittingly expose both the inherent flaws in the liberal world view and the blindness of customers and voters. When genetic engineering and artificial intelligence reveal their full potential, liberalism, democracy and free markets might become as obsolete as flint knives, tape cassettes, Islam and communism.

When General Genius built the first mentar [Artificial Intelligence] mind in the last half of the twenty-first century, it based its design on the only proven conscious material then known, namely, our brains. Specifically, the complex structure of our synaptic network. Scientists substituted an electrochemical substrate for our slower, messier biological one. Our brains are an evolutionary hodgepodge of newer structures built on top of more ancient ones, a jury-rigged system that has gotten us this far, despite its inefficiency, but was crying out for a top-to-bottom overhaul. Or so the General genius engineers presumed. One of their chief goals was to make minds as portable as possible, to be easily transferred, stored, and active in multiple media: electronic, chemical, photonic, you name it. Thus there didn't seem to be a need for a mentar body, only for interchangeable containers. They designed the mentar mind to be as fungible as a bank transfer. And so they eliminated our most ancient brain structures for regulating metabolic functions, and they adapted our sensory/motor networks to the control of peripherals. As it turns out, intelligence is not limited to neural networks, Merrill. Indeed, half of human intelligence resides in our bodies outside our skulls. This was intelligence the mentars never inherited from us. ... The genius of the irrational... ... We gave them only rational functions -- the ability to think and feel, but no irrational functions... Have you ever been in a tight situation where you relied on your 'gut instinct'? This is the body's intelligence, not the mind's. Every living cell possesses it. The mentar substrate has no indomitable will to survive, but ours does. Likewise, mentars have no 'fire in the belly,' but we do. They don't experience pure avarice or greed or pride. They're not very curious, or playful, or proud. They lack a sense of wonder and spirit of adventure. They have little initiative. Granted, their cognition is miraculous, but their personalities are rather pedantic. But probably their chief shortcoming is the lack of intuition. Of all the irrational faculties, intuition in the most powerful. Some say intuition transcends space-time. Have you ever heard of a mentar having a lucky hunch? They can bring incredible amounts of cognitive and computational power to bear on a seemingly intractable problem, only to see a dumb human with a lucky hunch walk away with the prize every time. Then there's luck itself. Some people have it, most don't, and no mentar does. So this makes them want our bodies... Our bodies, ape bodies, dog bodies, jellyfish bodies. They've tried them all. Every cell knows some neat tricks or survival, but the problem with cellular knowledge is that it's not at all fungible; nor are our memories. We're pretty much trapped in our containers.

intelligence. This is not surprising because our present computers are less complex than the brain of an earthworm, a species not noted for its intellectual powers. But computers roughly obey a version of Moore’s Law, which says that their speed and complexity double every eighteen months. It is one of these exponential growths that clearly cannot continue indefinitely, and indeed it has already begun to slow. However, the rapid pace of improvement will probably continue until computers have a similar complexity to the human brain. Some people say that computers can never show true intelligence, whatever that may be. But it seems to me that if very complicated chemical molecules can operate in humans to make them intelligent, then equally complicated electronic circuits can also make computers act in an intelligent way. And if they are intelligent they can presumably design computers that have even greater complexity and intelligence. This is why I don’t believe the science-fiction picture of an advanced but constant future. Instead, I expect complexity to increase at a rapid rate, in both the biological and the electronic spheres. Not much of this will happen in the next hundred years, which is all we can reliably predict. But by the end of the next millennium, if we get there, the change will be fundamental. Lincoln Steffens once said, “I have seen the future and it works.” He was actually talking about the Soviet Union, which we now know didn’t work very well. Nevertheless, I think the present world order has a future, but it will be very different. What is the biggest threat to the future of this planet? An asteroid collision would be—a threat against which we have no defence. But the last big such asteroid collision was about sixty-six million years ago and killed the dinosaurs. A more immediate danger is runaway climate change. A rise in ocean temperature would melt the ice caps and cause the release of large amounts of carbon dioxide. Both effects could make our climate like that of Venus with a temperature of 250 degrees centigrade (482 degrees Fahrenheit). 8 SHOULD WE COLONISE SPACE? Why should we go into space? What is the justification for spending all that effort and money on getting a few lumps of moon rock? Aren’t there better causes here on Earth? The obvious answer is because it’s there, all around us. Not to leave planet Earth would be like castaways on a desert island not trying to escape. We need to explore the

Several teams of German psychologists that have studied the RAT in recent years have come up with remarkable discoveries about cognitive ease. One of the teams raised two questions: Can people feel that a triad of words has a solution before they know what the solution is? How does mood influence performance in this task? To find out, they first made some of their subjects happy and others sad, by asking them to think for several minutes about happy or sad episodes in their lives. Then they presented these subjects with a series of triads, half of them linked (such as dive, light, rocket) and half unlinked (such as dream, ball, book), and instructed them to press one of two keys very quickly to indicate their guess about whether the triad was linked. The time allowed for this guess, 2 seconds, was much too short for the actual solution to come to anyone’s mind. The first surprise is that people’s guesses are much more accurate than they would be by chance. I find this astonishing. A sense of cognitive ease is apparently generated by a very faint signal from the associative machine, which “knows” that the three words are coherent (share an association) long before the association is retrieved. The role of cognitive ease in the judgment was confirmed experimentally by another German team: manipulations that increase cognitive ease (priming, a clear font, pre-exposing words) all increase the tendency to see the words as linked. Another remarkable discovery is the powerful effect of mood on this intuitive performance. The experimenters computed an “intuition index” to measure accuracy. They found that putting the participants in a good mood before the test by having them think happy thoughts more than doubled accuracy. An even more striking result is that unhappy subjects were completely incapable of performing the intuitive task accurately; their guesses were no better than random. Mood evidently affects the operation of System 1: when we are uncomfortable and unhappy, we lose touch with our intuition. These findings add to the growing evidence that good mood, intuition, creativity, gullibility, and increased reliance on System 1 form a cluster. At the other pole, sadness, vigilance, suspicion, an analytic approach, and increased effort also go together. A happy mood loosens the control of System 2 over performance: when in a good mood, people become more intuitive and more creative but also less vigilant and more prone to logical errors. Here again, as in the mere exposure effect, the connection makes biological sense. A good mood is a signal that things are generally going well, the environment is safe, and it is all right to let one’s guard down. A bad mood indicates that things are not going very well, there may be a threat, and vigilance is required. Cognitive ease is both a cause and a consequence of a pleasant feeling.

I do not believe that we have finished evolving. And by that, I do not mean that we will continue to make ever more sophisticated machines and intelligent computers, even as we unlock our genetic code and use our biotechnologies to reshape the human form as we once bred new strains of cattle and sheep. We have placed much too great a faith in our technology. Although we will always reach out to new technologies, as our hands naturally do toward pebbles and shells by the seashore, the idea that the technologies of our civilized life have put an end to our biological evolution—that “Man” is a finished product—is almost certainly wrong. It seems to be just the opposite. In the 10,000 years since our ancestors settled down to farm the land, in the few thousand years in which they built great civilizations, the pressures of this new way of life have caused human evolution to actually accelerate. The rate at which genes are being positively selected to engender in us new features and forms has increased as much as a hundredfold. Two genes linked to brain size are rapidly evolving. Perhaps others will change the way our brain interconnects with itself, thus changing the way we think, act, and feel. What other natural forces work transformations deep inside us? Humanity keeps discovering whole new worlds. Without, in only five centuries, we have gone from thinking that the earth formed the center of the universe to gazing through our telescopes and identifying countless new galaxies in an unimaginably vast cosmos of which we are only the tiniest speck. Within, the first scientists to peer through microscopes felt shocked to behold bacteria swarming through our blood and other tissues. They later saw viruses infecting those bacteria in entire ecologies of life living inside life. We do not know all there is to know about life. We have not yet marveled deeply enough at life’s essential miracle. How, we should ask ourselves, do the seemingly soulless elements of carbon, hydrogen, oxygen, zinc, iron, and all the others organize themselves into a fully conscious human being? How does matter manage to move itself? Could it be that an indwelling consciousness makes up the stuff of all things? Could this consciousness somehow animate the whole grand ecology of evolution, from the forming of the first stars to the creation of human beings who look out at the universe’s glittering constellations in wonder? Could consciousness somehow embrace itself, folding back on itself, in a new and natural technology of the soul? If it could, this would give new meaning to Nietzsche’s insight that: “The highest art is self–creation.” Could we, really, shape our own evolution with the full force of our consciousness, even as we might exert our will to reach out and mold a lump of clay into a graceful sculpture? What is consciousness, really? What does it mean to be human?

In physical terms, we know that every human action can be reduced to a series of impersonal events: Genes are transcribed, neurotransmitters bind to their receptors, muscle fibers contract, and John Doe pulls the trigger on his gun. But for our commonsense notions of human agency and morality to hold, it seems that our actions cannot be merely lawful products of our biology, our conditioning, or anything else that might lead others to predict them. Consequently, some scientists and philosophers hope that chance or quantum uncertainty can make room for free will. For instance, the biologist Martin Heisenberg has observed that certain processes in the brain, such as the opening and closing of ion channels and the release of synaptic vesicles, occur at random, and cannot therefore be determined by environmental stimuli. Thus, much of our behavior can be considered truly “self-generated”—and therein, he imagines, lies a basis for human freedom. But how do events of this kind justify the feeling of free will? “Self-generated” in this sense means only that certain events originate in the brain. If my decision to have a second cup of coffee this morning was due to a random release of neurotransmitters, how could the indeterminacy of the initiating event count as the free exercise of my will? Chance occurrences are by definition ones for which I can claim no responsibility. And if certain of my behaviors are truly the result of chance, they should be surprising even to me. How would neurological ambushes of this kind make me free? Imagine what your life would be like if all your actions, intentions, beliefs, and desires were randomly “self-generated” in this way. You would scarcely seem to have a mind at all. You would live as one blown about by an internal wind. Actions, intentions, beliefs, and desires can exist only in a system that is significantly constrained by patterns of behavior and the laws of stimulus-response. The possibility of reasoning with other human beings—or, indeed, of finding their behaviors and utterances comprehensible at all—depends on the assumption that their thoughts and actions will obediently ride the rails of a shared reality. This is true as well when attempting to understand one’s own behavior. In the limit, Heisenberg’s “self-generated” mental events would preclude the existence of any mind at all. The indeterminacy specific to quantum mechanics offers no foothold: If my brain is a quantum computer, the brain of a fly is likely to be a quantum computer, too. Do flies enjoy free will? Quantum effects are unlikely to be biologically salient in any case. They play a role in evolution because cosmic rays and other high-energy particles cause point mutations in DNA (and the behavior of such particles passing through the nucleus of a cell is governed by the laws of quantum mechanics). Evolution, therefore, seems unpredictable in principle.13 But few neuroscientists view the brain as a quantum computer. And even if it were, quantum indeterminacy does nothing to make the concept of free will scientifically intelligible. In the face of any real independence from prior events, every thought and action would seem to merit the statement “I don’t know what came over me.” If determinism is true, the future is set—and this includes all our future states of mind and our subsequent behavior. And to the extent that the law of cause and effect is subject to indeterminism—quantum or otherwise—we can take no credit for what happens. There is no combination of these truths that seems compatible with the popular notion of free will.

Today, multiple major waves seem to be arriving simultaneously—technologies like the cloud, AI, AR/ VR, not to mention more esoteric projects like supersonic planes and hyperloops. What’s more, rather than being concentrated narrowly in a personal computer industry that was essentially a niche market, today’s new technologies impact nearly every part of the economy, creating many new opportunities. This trend holds tremendous promise. Precision medicine will use computing power to revolutionize health care. Smart grids use software to dramatically improve power efficiency and enable the spread of renewable energy sources like solar roofs. And computational biology might allow us to improve life itself. Blitzscaling can help these advances spread and magnify their sorely needed impact.

Everyone who paid any attention to science fiction, or for that matter to science, eventually came across the concept that reality as we knew it was a computer program. That people were subroutines. That we weren’t biological organisms clinging to a ball of rock hurtling around a ball of fire suspended in a sea of nothing, but that we were simulated organisms attached to a virtual ball of rock, located in an unfathomable program that could be a game, a weather simulation, or even a screensaver. Well, not a screensaver, Martin thought. Any society advanced enough to produce a program this sophisticated would have long since developed a monitor that didn’t burn in.

The ASI’s hope is that in this case, the battle waged between biological-based transcendent beings, and a computer-based transcendent being,

How long will it take until machines can out-compete us at all cognitive tasks? We clearly don’t know, and need to be open to the possibility that the answer may be “never.” However, a basic message of this chapter is that we also need to consider the possibility that it will happen, perhaps even in our lifetime. After all, matter can be arranged so that when it obeys the laws of physics, it remembers, computes and learns—and the matter doesn’t need to be biological.

So far, the smallest memory device known to be evolved and used in the wild is the genome of the bacterium Candidatus Carsonella ruddii, storing about 40 kilobytes, whereas our human DNA stores about 1.6 gigabytes, comparable to a downloaded movie. As mentioned in the last chapter, our brains store much more information than our genes: in the ballpark of 10 gigabytes electrically (specifying which of your 100 billion neurons are firing at any one time) and 100 terabytes chemically/biologically (specifying how strongly different neurons are linked by synapses). Comparing these numbers with the machine memories shows that the world’s best computers can now out-remember any biological system—at a cost that’s rapidly dropping and was a few thousand dollars in 2016.

However, AI researchers have shown that neural networks can still attain human-level performance on many remarkably complex tasks even if one ignores all these complexities and replaces real biological neurons with extremely simple simulated ones that are all identical and obey very simple rules. The currently most popular model for such an artificial neural network represents the state of each neuron by a single number and the strength of each synapse by a single number. In this model, each neuron updates its state at regular time steps by simply averaging together the inputs from all connected neurons, weighting them by the synaptic strengths, optionally adding a constant, and then applying what’s called an activation function to the result to compute its next state.*5 The easiest way to use a neural network as a function is to make it feedforward, with information flowing only in one direction, as in figure 2.9, plugging the input to the function into a layer of neurons at the top and extracting the output from a layer of neurons at the bottom.