A Life of Its Own

Excerpt from my book Machine Nature

“He wanted to dream a man: he wanted to dream him with minute integrity and insert him into reality.” This was the goal of the silent man who came from the South, in Jorge Luis Borges’s short story, “The Circular Ruins.” From Pygmalion, Frankenstein, and the Golem to Star Trek’s Lieutenant Commander Data, the dream of administering the breath of life has fascinated humankind since antiquity.

We’ve seen how human-made systems can be made to evolve, to learn, to adapt, and to develop, as well as to exhibit a host of other characteristics that are usually not associated with machines, but rather with living beings. Can our creations one day take a life of their own? This question moved from the realm of science fiction to that of science with the advent of the field known as artificial life. The term was coined by Christopher G. Langton, organizer of the first artificial life conference, which took place in Los Alamos in 1987.

“Artificial Life,” wrote Langton (in the proceedings of the second conference), “is a field of study devoted to understanding life by attempting to abstract the fundamental dynamical principles underlying biological phenomena, and recreating these dynamics in other physical media — such as computers — making them accessible to new kinds of experimental manipulation and testing.” While biological research is essentially analytic, trying to break down complex phenomena into their basic components, artificial life is synthetic, attempting to construct phenomena from their elemental units, as such adding powerful new tools to the scientific toolkit. This is, however, only part of the field’s mission. As put forward by Langton “In addition to providing new ways to study the biological phenomena associated with life here on Earth, life-as-we-know-it, Artificial Life allows us to extend our studies to the larger domain of the ‘bio-logic’ of possible life, life-as-it-could-be, whatever it might be made of and wherever it might be found in the universe.”

Before talking about artificial life, shouldn’t we try to define what life is? Well …    No. I’ll steer clear of this issue since it is in fact quite a controversy in science; as things stand today, there is no agreed-upon scientific definition of Life. For now, we’ll just have to accept its being one of those “you-know-it-when-you-see-it” qualities: Your dog is obviously alive, while your washing machine is obviously not. The question is, then, can we create something that is “obviously alive”?

This question seems reasonably clear, or is it now? You’d think that it’s the “life” part of “artificial life” that eludes our definition. Well, there’s a further subtlety: What exactly does the “artificial” part mean? If you look up “artificial” in the dictionary (Merriam-Webster online), you’ll find a number of definitions. So let’s see which one sits well with “artificial life.” Artificial might mean “lacking in natural or spontaneous quality  < an artificial smile >   < an artificial excitement > .” This can’t be it. An extraterrestrial might be unnatural and unspontaneous, and yet obviously alive; artificial life cannot be about life that lacks in natural or spontaneous quality. What about “imitation, sham  < artificial flavor >”? This is no good: By definition our putative “artificially alive” creature is going to be an imitation in some sense; the point is, in what sense, and how good an imitation (“That’s not a real dog? I never would’ve guessed in a million years!”). Saying that artificial life is synonymous with imitation life doesn’t get us very far. We’re obviously trying to imitate life, in the proverbial “imitation is the sincerest flattery” sense.

I’m not merely engaging here in armchair philosophy, but rather trying to arrive at the essence of what “artificial life” means. What seems to be missing in the two definitions of the previous paragraph is the creation aspect. So let’s try what is actually the first definition appearing under “artificial”: “man-made  < an artificial limb >   < artificial diamonds > .” Ah! now we’re cooking. This seems to be the right one. It accords perfectly with the definition given by Langton in the proceedings of the first artificial-life conference: “The study of man-made systems that exhibit behaviors characteristic of natural living systems.”

Artificial life is thus life created by humans rather than by Nature. Simple. Well ... I hate to be so fussy, but “human-made” can mean at least three different things. One way to create life is through the union of a male, known as “daddy, ” and a female, known as “mommy,” thus giving life to a male or a female known as “baby.” You might be frowning now, thinking to yourself that it’s rather silly of me to even mention this since this is quite obviously not artificial life. This is the natural way of creating life, whatever that may mean. But then again, what about artificial insemination? This involves the introduction of semen into the uterus or oviduct by other than natural means, yet no one would claim that this produces artificial babies. Nonetheless, there is a definite intervention by humans, thus rendering this process somewhat less than 100 percent natural.

We often invoke the term “human-made” when speaking of objects such as cars. This image of artificial life might involve some kind of production line, where heads, arms, feet, and torsos are assembled into complete beings, after which the proverbial switch is pulled, thus breathing life into them. (The assembly line need by no means produce but humanoid life; it could in fact produce a range of beings, from artificial bacteria to artificial whales.) This is the most common image where fiction is concerned (Victor Frankenstein creating a humanoid monster, for one).

There is yet a third way by which life may be created by humans: through the process of evolution, and most likely open-ended at that (as we discussed in Chapter 12). This raises an interesting question: While we may sow the seeds of life, setting off such an open-ended process, whatever emerges — numerous generations later — might be far removed from our original design; just how “human-made,” then, is this form of life?

My intention in the somewhat philosophical discussion above has been to show you just how intricate this seemingly simple term — artificial life — really is. The concept of “artificial” is quite elusive where life is concerned, and even if we agree on emphasizing the “creation” aspect, there are a number of fundamentally different modes of creation.

Artificial life might in fact be an oxymoron. After all, how can life be artificial? If something is truly alive — assuming we can somehow agree on this fact — then what’s artificial about it? Even if we take what could arguably be considered the most artificial route of creation, that of the assembly line, once we’re done, the creature is no longer artificially alive; it’s alive — period. This takes us right back to Langton’s definition of artificial life, life-as-it-could-be, “whatever it might be made of and wherever it might be found in the universe.” Whether flesh-and-blood, man-woman-made, or nuts-and-bolts, factory-made, life is life. Perhaps rather than speak of artificial life, which is somewhat problematic, we should talk about life created by humans. In fact, even “created” might be too strong a word (think of the evolutionary scenario for one). Let’s settle for human-induced life. This emphasizes the relevant difference between Nature and humans, namely, the manner by which life arrives on the scene; the end result though is — in both cases — bona fide life.

Life may be many things: perhaps “a tale told by an idiot, full of sound and fury, signifying nothing” (Shakespeare), or maybe “colour and warmth and light, and a striving evermore for these” (Julian Grenfell), or indeed “a glorious cycle of song, a medley of extemporanea” (Dorothy Parker). At the heart of artificial life research lies the belief that whatever life is, it is not about carbon; life is not about the medium but about the mediated. It is a process that we do not yet understand in full, but which we may nonetheless be able to create, or perhaps we should say re-create: After all, Nature has beaten us to it.

Let’s get down to earth now and consider some of the issues involved in inducing life. As I’ve discussed above there are at least three ways of going about this. We might imagine some far-future extension of current medical practice (such as artificial insemination) that will result in a new form of life. Since this involves many technical biological and medical details, I think I’ll leave it at that for the present discussion.

The second way to induce life is to produce a full-blown living being. As I briefly mentioned in Chapter 11, there is much ongoing research on mimicking Nature’s gadgets, building such devices as eyes, ears, and hearts. While many of these are intended to serve as prostheses for humans, some are also used in robots. Perhaps at some point in the future we’ll be in possession of enough parts to construct an entire being. This might in fact come sooner rather than later: While speaking of “inducing life” usually tends to evoke in us images of humanoid life, let’s not be Homo sapien chauvinists. As I’ve mentioned time and again, constructing the equivalent of even a single-celled organism would be a huge achievement (not to mention a beetle or a fly), and this might come about sooner than we expect. (John Wyndham’s short story Female of the Species provides an amusingly gruesome vision of this production-line scenario. When visited by two inspectors of the Society for the Suppression of the Maltreatment of Animals, Doctor Dixon — the Frankenstein-like protagonist — explains: “The crux of this is that I have not, as you are suspecting, either grafted, or readjusted, nor in any way distorted living forms. I have built them.”)

And then there’s the third way of inducing life, by creating the necessary conditions for open-ended evolution to take place. In Chapter 1 we noted that evolution rests on four principles:

• Individual organisms vary in their viability in the environments that they occupy.
• Individual variation is heritable.
• Individuals tend to produce more offspring than can survive on the limited resources available in the environment.
• Those individuals best adapted to the environment are the ones that will survive to reproduce in the ensuing struggle for survival.

The second and third principles — heritability and the production of offspring — conceal an even more fundamental property: self-replication. We already mentioned this in relation to the Tierra world (Chapter13), which was inoculated with an ancestral (computer-program) creature able to self-replicate, creating copies of itself in the computer’s memory. Self-replication was a necessary precursor to the appearance of life on Earth: The first self-replicating molecules had appeared about 3.5 billion years ago, a humble beginning that marked the onset of the evolutionary avalanche that gave rise to Life.

Tierra inventor Thomas Ray wrote, “I would consider a system to be living if it is self-replicating, and capable of open-ended evolution.” (The Tierran world was in fact set up to discover not how self-replication arrives on the scene, but what happens after it does, namely, how does a diverse ecosystem come to evolve.)

The study of self-replicating structures in human-made (or human-induced) systems began in the late 1940s, when John von Neumann — one of the twentieth century’s most eminent mathematicians and physicists — posed the question of whether a machine can self-replicate (produce copies of itself). He wrote that, “living organisms are very complicated aggregations of elementary parts, and by any reasonable theory of probability or thermodynamics highly improbable. That they should occur in the world at all is a miracle of the first magnitude; the only thing which removes, or mitigates, this miracle is that they reproduce themselves. Therefore, if by any peculiar accident there should ever be one of them, from there on the rules of probability do not apply, and there will be many of them, at least if the milieu is reasonable.”

Von Neumann was not interested in building an actual machine, but rather in studying the theoretical feasibility of self-replication from a mathematical point of view. He succeeded in proving (mathematically) that machines can self-replicate, laying down along the way a number of fundamental principles involved in this process. During the decade following his work (in the 1950s), when the basic genetic mechanisms had begun to unfold, it turned out that Nature had “adopted” von Neumann’s principles. (It is quite fascinating to see how his results predated the actual biological findings.)

The study of self-replication has been taking place now for more than half a century. Much of this work is in fact quite separate from artificial life and is motivated by the desire to understand the fundamental principles involved in this process. This research might better our understanding of self-replication in Nature, as well as find many technological applications. There is much talk today of nanotechnology, where self-replication is of vital import. You’d like to be able to build one tiny machine, which would than sally forth and multiply. For example, you’d inject a small nanomachine into your body to fight off some mean virus, and this nanomachine would be able to self-replicate, thereby increasing the size of your internal army. One of my favorite application examples is the self-replicating lunar factory, which is not drawn from some science-fiction novel but was actually proposed by NASA researchers in 1980. Imagine planting a “seed” factory on the moon that would then self-replicate to populate a large surface, using local lunar material. This multitude of factories could manufacture necessary products for lunar settlers or for shipping back to Earth. And all you have to do is plant the first one.

On our way to inducing life, self-replication is of crucial import. We know a bit more about this issue today than we did 50 years ago, though there is still no lack of unanswered questions, which is music to researchers’ ears. The next item on our life-inducing agenda is trying to come up with an open-ended context for our self-replicating critters (just as Ray set out to do with his Tierran world); this issue has both genotypic and phenotypic aspects (Chapter 12).

The phenotypic aspect of open-endedness concerns the environment. The grand challenges posed by an open-ended environment vis-à-vis its inhabitants are to be able to move around and to sense the surroundings to a degree sufficient to achieve the necessary maintenance of life and reproduction. What seems to us to be really difficult — as in playing chess — may in fact be quite easy once this essence of being and reacting is available. Remember, elephants don’t play chess (Chapter 11).

Chess is in fact quite an instructive example. It has been one of the holy grails in the field of artificial intelligence since the 1950s. In those early days a number of researchers had managed to come up with programs that were able to play a decent game, winning against average human players (though they were easily beaten by chess experts). The ruling opinion at the time was that very soon there would be a chess machine able to beat any human player. The problem, though, turned out to be harder than believed, demonstrating what is known as the fallacy of the first step: It’s easier to go from ignorance to mediocrity than it is to go from mediocrity to excellence (think of the difference between playing tennis and playing tennis well). Mediocre chess-playing computers were available as far back as the 1960s, though only very recently has a computer (IBM’s Deep Blue) been able to beat a world champion (Garry Kasparov).

It took 40 years to come up with a good chess-playing computer, and frankly — chess is easy! I’m not saying it doesn’t require a form of genius to excel at the game, nor am I belittling the arduous task faced by the designers of a chess-playing machine; I’m referring to the facileness of the chess environment; it is yet another illustrative example of non-open-endedness. Chess is defined by a very small number of well-known, fixed rules, and there’s really no dynamically changing environment to speak of (in this sense it is similar to our basketball environment of Chapter 12).

How do we increase the open-endedness of the environment? Thomas Ray took what is perhaps the first shot at providing an answer to this question with his simulated Tierra world. Another possibility is to subject our critter to the most complex environment known to date: ours. This is the route taken by adaptive-robotics researchers. In Chapter 4 we saw how real robots are subjected to a real-world environment (as opposed to simulated robots in a simulated computer environment); for this reason the approach is also known as situated or embodied robotics.

An argument that is often raised against embodied robotics is that it is too costly and too slow. You’d be much better off running the evolutionary process in a simulated environment within the computer, plucking out but the end result — the best simulated robot that has evolved — and implementing it in the real world. The problem is that often this does not work: When you go from the simulated to the real, the robot no longer functions properly. Our environment is full of many hidden complexities that often escape our notice, rendering it very hard to implement them in a computer; it’s just plain easier to use the real world.

Nature’s open-endedness manifests itself not only at the phenotypic level but also at the genotypic level; it can tinker with the genome so as to produce entirely novel designs, which give rise to new phenotypes better able to rough it. This point has also been receiving increased attention of late: How can we set up an evolutionary scenario in which fundamental genomic changes can occur? For example, in Chapter 4 we evolved only the behavior of the robots, their small, neural-network brains. Their body, on the other hand, did not change at all, which is nothing like natural evolution. Nature possesses the ability to bring about not only behavioral changes but also morphological modifications in her creatures. A number of researchers have recently begun looking into the possibility of doing this for robots as well, evolving both behavior and morphology. While quite rudimentary at the moment, this is yet another step toward increased open-endedness.

Next to the natural world a new universe has sprung up in the past few years, which is both complex and open-ended: the Internet. It is evolving at a breathtaking speed, already exhibiting enough complexity to merit the attention of scigineers. This is not surprising. The Internet’s evolution is mediated by self-proclaimed intelligent beings known as Homo sapiens. This process is more akin to Lamarckian evolution, where a beneficial survival trick can be immediately incorporated within the evolving population.

Will we someday see the rise of network life? Even as you read these lines, there are thousands and thousands of small programs — known as agents — roaming the network, seeking to find information that will appease their human masters. Currently they are quite limited, lacking in both intelligence and autonomy. Little by little, though, they might develop into more autonomous critters. This might come about by employing some of the techniques we discussed in this book, giving rise to what I call Egents, for Evolving Agents, and double AAgents, for Adaptive Agents. These agents will be denizens of the network universe, whereas we will not; it is they who will be in their element. We may have built the house, but we are not the ones living in it. I just hope those double AAgents will work for you, their master, and not for some unknown party behind the cyber curtain.

The borders between the living and the nonliving, between the Nature-made and the human-made appear to be constantly blurring.

As in dreams.

The silent man who came from the South eventually succeeded in dreaming a man and inserting him into reality. And what became of the dreamer? “With relief, with humiliation, with terror, he understood that he too was a mere appearance, dreamt by another.” 
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Sweet dreams.