On the "inevitable singularity"

Unfortunately I do not have much time to write this month, as I am quite busy with other things. Today, though, I have an essay I would like to share: 

A recurrent theme in modern literature and philosophy is concern about the effects of technology on our humanity, a concern that has existed since the rate at which technology increases became too rapid to contemplate. Wallace Stegner expresses this concern in his essay “The Wilderness Idea,” in which he says that without another frontier humankind will be committed to a world defined and controlled by technology. Stegner is quite correct in stating that the concept of the frontier is behind us, and that technology will ultimately determine our way of life. Technological increase has been proven to be exponential and is inherently anti-individualistic, and technology naturally breeds dependence. Furthermore, the only frontier remaining is one that destroys individuality rather than promoting a self-sufficient pioneer lifestyle.

As any scientist will confirm, technology increases at a torrent pace and will only increase faster as time goes on. This has been proven in almost all fields of science, and most intellectuals regard the “technological singularity” as an inevitable conclusion. For example, in computer science, a theory known as Moore’s Law holds that scientists will be able to double a microchip’s computing power every two years until computers are capable of performing any calculation infinitely quickly. This inevitable increase helps to prove Stenger’s thesis, as it signifies that technology is impossible to supplant or remove from society. 

More importantly, technology naturally breeds dependence. Consider all of the major industries that define people’s lifestyles in today’s world: agriculture, transportation, and consumer goods. All of these industries are highly dependent on technology and will continue to utilize new technology as it is invented and it is completely inconceivable that any of these industries will abandon the technology on which they are based. This principle, combined with the fact that technology will continue to increase, yield only one conclusion: technology is and always will be a part of our lifestyles and society, proving that Stenger’s is correct in stating that a “Brave New World” scenario is unavoidable.

Stegner’s main point is that without a frontier or wilderness, mankind is committed to this dependence on technology. Stegner is quite correct in this assertion—the only frontier open to mankind is, as science fiction tells, us, outer space. However, this is not true wilderness in the sense that Stegner would like it to be—rather than promoting individualism as previous frontiers have been, space exploration encourages federalism and dependence on technology. Since sophisticated equipment is required for space exploration, the common man is no longer able to become a self-sufficient pioneer. Instead, only strong, central governments have the ability to perform the necessary research and build the equipment needed for space travel. Thus, no “wilderness” can save us from our inevitable fate—we are indeed committed to a society defined by our technology. However, Stegner is far too pessimistic about his conclusion—he forgets that technology has the capacity to meet all of our needs, destroying our individuality and self-sufficiency but creating a world without hardship. 

Technology vs. overpopulation

I’ve said it many times before: the crisis that will come determine the survival of the human race is the overpopulation crisis. The Earth has a finite “carrying capacity,” which we are coming closer and closer to with each passing day. Experts predict that in 2030 the world population will be 8.3 billion, and we are going to see serious shortages of food, water, and energy. Unless we can somehow manage to figure out how to more efficiently manage our resources or find more efficient ways of obtaining the resources we need, these shortages may result in complete economic and social collapse, possibly even the death of our race. What scares me (and many other people) most is the fact that 2030, when we will really have to face this crisis, is only 20 years away. In two decades—the blink of an eye, really—we will be faced with a crisis that could have disastrous results if mishandled.

But, strangely, a few people are incredibly confident about the whole thing. Why? They hold that though population increasing exponentially, so is technology. Soon, these optimists hold, technologies will be available that can solve the population crisis and increase the Earth’s carrying capacity. But is this simply misguided optimism? After all, since WWI we have seen that technology is often the cause of many problems, not the solution. Besides, is 20 years really enough time to solve a problem of such scope?

My answer is a very definite “sort of.” I suspect that technology will soften the blow, especially because technologies that will help us will be promoted over the next 20 years as the threat of food riots and economic collapse looms overhead. But I doubt that technology will not come close to fully solving the problem, for technological reasons, social ones, and economic ones.

The technological reason is simple: there just isn’t enough time. Granted, technological increase is exponential. But can we really find an unlimited source of food, an easier method of desalination, cheap energy, and a solution to air pollution in a mere 20 years, let alone implement these ideas in time? In order to develop the necessary technology, lots and lost of government-sponsored research is needed—and let’s face it, with the economy less and less of that is happening. Even if there is a space race-like surge in research, there is no guarantee that it will pay off.

Next, remember that the technology not only has to be available, it has to be cheap. For example, mass exodus to a moon colony is possible but wildly impractical because of the exorbitant cost. The same can be said for concepts such as vertical farming (farming in buildings) or similar urban farming projects. Water desalination is also economically unfeasible—we have the facilities and technology to distill more than enough seawater to meet our needs, but we cannot do it cheaply enough to make it economically viable.

Lastly, there is a social dimension to this crisis that could hinder efforts to resolve it. For example, environmentalists are opposed to genetically manipulated crops, which could prevent their widespread use. This social dimension is hard to measure, but until the populace realizes how dire the situation is I believe it will hinder efforts to solve the crisis. 

The final word is this: the crisis is coming. Technology can help us, but it won’t solve all of our problems. 

Beyond Turing-completeness

Today I read an article in the science magazine “Discover” about a new kind of computer called Darwin 7. The article was in the form of an interview with computer scientist Gerald Edelman. Edelman explains that in the biological world, there are obvious advantages to consciousness, particularly the higher-order consciousness human beings have. Conscious beings are able to adapt to different scenarios and learn, making them more adaptable. Therefore, says Eldelman, it would be advantageous to create computers that are based around a model of a brain rather than being programmed. Edelman and his colleagues have done just that: The device is called Darwin 7, and it is, as Edelman says, a computerized brain.

Before I discuss the implications of this it is important to explain the difference between a computer program and a BBD, or brain-based device (like Darwin 7). A computer program consists of a series of instructions typed in computer code. In my post on the Chinese Room, I explored John Searle’s proof that a computer program cannot truly have understanding because it has syntax but no semantics. But a BBD is very different—its “brain” is not encoded but instead is an physical object. It simulates the neurons of an organic brain in order to “think.” In other words, a BBD is not Turing-complete; it is something different entirely. Searle’s proof does not apply; a BBD is capable of true understanding and learning.

The latter has already been tested, says Edelman: Versions of Darwin 7 have been taught to perform various tasks, and the advantages of a machine that can learn are very clear. In one test, robots controlled by a BBD played soccer against robots controlled by an AI program. The BBDs won 5 games out of 5, since they were able to adapt to every situation, while the AI-controlled robots did not have conditionals for every scenario.

Furthermore, Edelman says that the future of BBDs is bright. Edelman and a colleague have created a BBD that is about as complex as a cat brain, and it is very close to what he calls a “conscious artifact.” This BBD is so complex that it runs continuously like a real brain (simpler BBDs only react when they receive input), but it lapses into a “rest state,” similar to the state people’s brains are in when they are not thinking of anything. The point it, sooner or later BBDs are going to surpass AI because of their ability to learn. 

In my mind, the concept of super-smart a BBD re-raises the question of computers in relation to the future of humanity. Science fiction sends us conflicting messages about how computers will affect our chances for survival as a race—some SF preaches an optimistic message, while other works warn us that computers will be our downfall. Today, though this fear is somewhat present in our culture, most computer scientists hold that there is nothing to fear from AI since they are simply a collection of conditionals. They still follow Searle’s Chinese Room, so they are incapable of though are therefore cannot consciously act to destroy humanity. But BBDs are different. Though I know little about the subject, it appears that BBDs are far more likely to “betray” humanity than a lifeless computer program. The more complex a BBD, it seems, the more intelligent it is and the more likely it is be irrational. Additionally, remember that BBDs are modeled after human brains—and human brains are not exactly the most efficient or rational thinking machines in existence; far from it. So, while I have few qualms with letting a computer program run the world, a BBD is a different matter. Before we use these new devices, we need a far better understanding of them. Hopefully BBDs will facilitate the study the brain, which in turn will allows to create better, more stable BBDs. For now, though, all they do is play soccer, so I am not worried just yet.

On a different note: I would like to end with an amusing hypothetical situation involving Turing-completeness. Recall that even analog computers are Turing-complete, since they can technically be programmed for every task. In a comic strip (link), Randal Monroe envisions a new kind of computer, which is technically Turing-complete. I find his idea both hilarious and fascinating, if somewhat impractical. Even funnier, it is a philosophical stance that technically cannot be disproven. So I guess we could be just a bunch of rocks. 

Musings on the Turing Test (part 2)

Happy New Year to all! I hope that 2009 is a better year for all than 2008. Sadly, the Gaza crisis is still going on, but I hope that it will soon be resolved. However, I will not be addressing that particular issue today, as I would like to talk more about the Turing test.

The Loebner Prize is a contest held every year, in which contestants try to program a computer to pass the current year’s version of the Turing test. The winner is the program that manages to appear “human” to the greatest number of examiners. In 1991, there was some controversy over the winner; the computer program considered “most convincing” fooled many examiners because it was programmed to make typing errors. Since then, the Loebner Prize has focused on “chatterbots”—computer programs that simulate a conversation (typed of course).

This brings me to the point I would like to discuss today: the so-called concept of “artificial stupidity.” This is the idea that computer programs must be made to make errors in order to appear human. This idea is not something new; even Alan Turing in 1948 realized that a computer that appears perfect cannot pass as human:

“It is claimed that the interrogator could distinguish the machine from the man simply by setting them a number of problems in arithmetic. The machine would be unmasked because of its deadly accuracy.”

Turing’s point is clear: to appear human, machines cannot be perfect.  This is evident in the Loebner Prize winners of both 1991 and 2008. In fact, after looking at the 2008 transcripts, I realized that all of the top 5 programs committed errors on purpose. (These transcripts are available here). Also, many of the more successful ones delayed their responses by an amount of time proportional to the number of words they “typed,” as an instantaneous response is suspicious. This, too, is a form of “artificial stupidity.”

What does this mean for us? For the layman, very little. For the computer scientist, though, it more clearly defines the challenge of making computers seem human. This challenge no longer consists of simply making computers smarter, as it did 30 or 40 years ago; now, it consists of making computers imitate all the nuances of human beings. This is probably a much harder task, but I have no doubt that computers will eventually get there. When we reach that point, we are going to have to ask ourselves some serious questions about our humanity. Until then, all we can do is wait.

**As a side note: Last year’s winner of the Loebner Prize, a program called Elbot, can be “talked to” on the creator’s website. I conducted a half-hour conversation with it, and what I found was startling—the program is able to have a perfectly normal-sounding dialogue on almost every subject. I strongly recommend trying it out for yourself; the link can be found here.  

Exploring the Chinese Room

Monday, in my post about the Turing test, I briefly explored John Searle’s thought-experiment “The Chinese Room.” Today, I would like to delve further into this interesting topic.

First, I would like to better explain the argument itself—I feel did something of a shoddy job of doing so in Monday’s post.  Rather than explain it myself, I will quote Searle’s description of the thought-experiment from his paper, “Minds, Brains, and Programs.” Unfortunately his description is a bit lengthy:

“Suppose that I'm locked in a room and given a large batch of Chinese writing. Suppose furthermore (as is indeed the case) that I know no Chinese, either written or spoken, and that I'm not even confident that I could recognize Chinese writing as Chinese writing distinct from, say, Japanese writing or meaningless squiggles. To me, Chinese writing is just so many meaningless squiggles.

Now suppose further that after this first batch of Chinese writing I am given a second batch of Chinese script together with a set of rules for correlating the second batch with the first batch. The rules are in English, and I understand these rules as well as any other native speaker of English. They enable me to correlate one set of formal symbols with another set of formal symbols, and all that 'formal' means here is that I can identify the symbols entirely by their shapes. Now suppose also that I am given a third batch of Chinese symbols together with some instructions, again in English, that enable me to correlate elements of this third batch with the first two batches, and these rules instruct me how to give back certain Chinese symbols with certain sorts of shapes in response to certain sorts of shapes given me in the third batch. Unknown to me, the people who are giving me all of these symbols call the first batch "a script," they call the second batch a "story. ' and they call the third batch "questions." Furthermore, they call the symbols I give them back in response to the third batch "answers to the questions." and the set of rules in English that they gave me, they call "the program."

Now just to complicate the story a little, imagine that these people also give me stories in English, which I understand, and they then ask me questions in English about these stories, and I give them back answers in English. Suppose also that after a while I get so good at following the instructions for manipulating the Chinese symbols and the programmers get so good at writing the programs that from the external point of view that is, from the point of view of somebody outside the room in which I am locked -- my answers to the questions are absolutely indistinguishable from those of native Chinese speakers. Nobody just looking at my answers can tell that I don't speak a word of Chinese.

Let us also suppose that my answers to the English questions are, as they no doubt would be, indistinguishable from those of other native English speakers, for the simple reason that I am a native English speaker. From the external point of view -- from the point of view of someone reading my "answers" -- the answers to the Chinese questions and the English questions are equally good. But in the Chinese case, unlike the English case, I produce the answers by manipulating uninterpreted formal symbols. As far as the Chinese is concerned, I simply behave like a computer; I perform computational operations on formally specified elements. For the purposes of the Chinese, I am simply an instantiation of the computer program.”

Searle’s point is obvious: In the proof, he is manipulating Chinese symbols without true semantic understanding of what they mean. This, he argues, is what computers do: they simply carry out “the program” without having true understanding of what they are doing. It is important to note that Searle is not a dualist—he does not believe the human mind has any kind of non-physical component. He concedes that the human brain is simply a biological “machine,” and that an artificial mind could hypothetically be constructed. Searle is trying to prove that a computer program can never create a true “mind” because computer programs are in scripts that have syntax but no semantics. Essentially, Searle is challenging the computational theory of the mind: the idea that human beings cannot be explained in terms of input/output (note how similar this is to philosophical determinism).  

Also, I should mention that though I had never heard of the Chinese Room argument until the other day, it is one of the most important issues in cognitive science and philosophy today. In fact, the influential computer scientist Patrick Hays even joked that cognitive science should be renamed “the ongoing research program of showing Searle's Chinese Room Argument to be false.” There are an enormous number of responses to the argument, and unfortunately I do not have time to cover them all today. However, I would like to look at the implications of Searle’s argument and at some of the more convincing responses. 

Many philosophers and scientists have looked at what the Chinese Room thought-experiment implies, including John Searle himself. Searle created the following proof from his thought-experiment:

Axiom 1: Computer programs are formal and syntactic.

Axiom 2: Minds have mental, semantic contents.

Axiom 3: Syntax is not enough to create a semantic mind.

Conclusion: Programs are “neither constitutive of nor sufficient for minds.”

Searle’s conclusion is intuitive enough, given the data he is starting with. Axioms one and two are pretty obvious—1 states that computers have no true understanding of things, and 2 states that human minds do. Axiom 3 is what the Chinese Room proves—the fact that a computer can pass a Turing test without true understanding (at least, according to Searle). However, as I mentioned, the Chinese Room has attracted thousands of intellectual critics, and there are a multitude of responses to the proof from various areas of science. These responses attack Searle’s axioms, his conclusion, and the validity of the thought-experiment itself. I would like to take a few moments to explore some of these claims. 

The first is the “systems” response. This states that even though the man in the room does not understand Chinese, the man, the room, and the program as a system do. However, Searle’s reply is that it is possible for the man to memorize the program, making him the entire system even though he still has no understanding of Chinese characters. The “systems” reply is that the mind is virtual mind, which has a variable physical component. (For example, the software of a computer is a virtual machine) Thus, there is an “implementation independent” virtual mind at work. Searle, however, would maintain that such a virtual mind is still a syntactic simulation incapable of cognitive understanding.

Other responses are related to so-called appeals to reason. For example, a “program” to do what Searle is suggesting would be enormously complex, and it may require a whole new kind of programming. However, I will not even address these because they are insignificant—the Chinese room is a hypothetical case, after all. 

So, what is the final verdict on Searle’s Chinese Room? I don’t have one. Searle’s proof seems legitimate, but several of its aspects remain unproven, as many of the responses show. I promise to revisit the Chinese Room soon, since it is such an important and influential argument. For now, all I can say is that since the Chinese Room resides in the grey area between science and philosophy, someday either experimentation or logic may yield the answer. 

Musings on the Turing test (part 1)

In 1950, philosopher and computer scientist Alan Turing began to explore the philosophic implications of computers, specifically the problem of machine “intelligence.” Turing asked whether machines can ever obtain true intelligence or consciousness, and if they can, how do they differ from human beings (besides physically)? Turing published the following in a paper:

“It is not difficult to devise a paper machine [computer] which will play a not very bad game of chess. Now get three men as subjects for the experiment. A, B and C. A and C are to be rather poor chess players, B is the operator who works the paper machine. Two rooms are used with some arrangement for communicating moves, and a game is played between C and either A or the paper machine. C may find it quite difficult to tell which he is playing.”

What Turing is saying is that in this case a computer is indistinguishable from a human. To solve this problem, Turing developed the Turing test (named after himself), which is a hypothetical written test that can distinguish between a human being and a computer. Many versions of the test have been created, covering a variety of subjects. In fact, contests have been held, in which programmers attempt to create computer programs that can pass the Turing test (or at least appear to pass it according to a certain percent of judges).

Despite its popularity, the Turing test is often criticized. One of the most compelling arguments against it is the thought-experiment “the Chinese Room,” devised by John Searle in 1980. Searle argues that a computer could answer all of the questions correctly but still not have true intelligence, which is what the test is really meant to discover. In other words, the computer could answer the question simply by using a complex series of decision algorithms (to anyone who knows Java, think nested “if” statements). Thus, the computer is simply manipulating ideas in the way a non-Chinese speaking person can manipulate Chinese letters—they can answer a question in written Chinese without actually understanding what they are saying. This brings up a slew of complicated questions, including determinism, philosophy of mind, and the problem of consciousness.

First, determinism and the computational theory of the mind. This essentially means that human minds are computers in that we just take in data and process it in the same way computers do, and we have no “understanding” of concepts more than computers do. If this true, computers will eventually be able to pass the Turing test; all they have to do is mimic the algorithms the human mind uses. However, many philosophers believe in dualism, the idea that the mind has a non-physical component, or something like a soul. In this case, computers will never be able to pass the Turing test, as a non-physical mind would truly have free will, which a computer cannot mimic.

The problem of consciousness also comes into play, since this is another aspect of the human mind a computer may or may not be able to copy. This depends on the nature of consciousness—if it simply stems from the human brain having a huge number of neurons, there is hope for computer consciousness yet. But if it comes from a non-physical source such as the soul, computers will never be able to achieve consciousness as we know it. Also, the relationship between consciousness and self-awareness come into play here: Unless consciousness is defined as simply self-awareness, computers may be able to achieve self-awareness without achieving true consciousness.

If we ignore these philosophical problems for a moment, though, as follow the “Chinese room” theory that computers may be able to pass the Turing test even if they are truly “intelligent,” we can examine the problem more practically. Many computer scientists have predicted that computers will soon be able to pass the Turing test because of future advances in computing power. Moore’s Law holds that the number of transistors in a integrated circuit will double every two years, which means an exponential increase in computing power. So far, computer science has followed this pattern, However, many intellectuals argue that eventually this will break down because there is a point at which it is almost impossible to make smaller transistors. Moore himself stated that he doubts that the law will continue forever. Though some believe that quantum computers will be developed enough to replace circuits by the time this happens, this will also mean that Moore’s law no longer holds true because it only applies to integrated circuits.

However, it is clear that computers are going to undergo huge increase in processing power, whether they follow Moore’s Law or not. If quantum computers eventually become a reality, the amount of computing power available is going to be enormous. With all this “intelligence” at a computer’s fingertips, the Turing test as we know it will soon become obsolete, as computers will be able to immediately determine the “human” answer to any Turing test question with a low probability of error.

This aspect of the implications of the Turing test is a popular subject of debate among intellectuals. Two prominent philosopher/futurists, Mitch Kapor and Raymond Kurzweil, have placed a $10,000 bet on whether computers will be able to pass a Turing test by 2029. Check out this link for their arguments and the conditions of the bet. 

Another time, perhaps, I will review Kapor and Kurzweil’s arguments. I have barely scratched the surface on this topic, so I will almost certainly discuss it again. 

What computers can teach us

Philosophers and even computer scientists will often argue that computers can never achieve our “thinking power,” and that they definitely cannot surpass us in terms of cognitive ability. However, I strongly disagree with this, for both a philosophical reason and a practical one.

First, the “practical” reason: Simply, computer science in increasing at a terrifying rate (an exponential rate, if you believe in the technological singularity). Twenty years ago, people believed computers would never be able to solve the “salesman problem” for only 50 or so cities—today, we have solved it for thousands, according to this New York Times article.             

The fact is, unpredictable advances in the way we understand computers will probably allow them to do some serious number-crunching, making them far better and faster at mathematics and science than we are. Furthermore, computers will soon have the ability to improve themselves, thus increasing the rate that artificial intelligence, or AI, increases.

Next, the “moral” argument I mentioned. The point that skeptics of AI often mention is that AI will never be truly human, since a computer is simply a complex series of pre-programmed responses. However, I have to ask: what, then, are we? Isn’t a human being very similar—just a very complex series of responses programmed into our brain? Granted, we are affected by our environment, but computers can also learn from experience—the ability to learn is nothing special. As any computer programmer knows, with enough “if” “else” and “while” statements, computers can learn and adapt to their environment no matter what the circumstances are. Thus, human beings as computers are not so different after all, and artificial intelligence might not be as impossible as some people like to think. Though this sounds deterministic, this is the most salient argument for AI.

The fact is, computers are already on of the most important inventions of the modern world, and the development of true AI is implacable. The important thing, though, is how we deal with the fact that computers will still be far smarter than human beings. I do not agree with those who would ban computers or put a moratorium on computer research—the answer to the problem of computers must be one of wisdom, not deliberate ignorance. We must not simply succumb to the inevitable—we must ride the crest of this wave, using the enormous potential of AI to help us in a way that will not infringe on our humanity. 

On “The Last Question”

Inspired by Asimov’s The Last Answer, I have decided to talk about another of his famous short stories, The Last Question. In this story, a computer called AC ponders whether entropy can be reversed. However, it does not come up with the answer until after the universe undergoes heat death. At the end, the computer discovers the answer and decides to demonstrate it:

“And AC said, ‘LET THERE BE LIGHT!’ And there was light—”

Of course, this brings up some interesting questions. First of all, Asimov is referencing the concept of the technological singularity, the idea that technology increases at an exponential rate, and that it will eventually increase infinitely fast so that it encompasses everything. However, I have some doubts about this. If the world were to have a nuclear war or fall into a worldwide depression (both somewhat realistic!), wouldn’t the rate technology is being invented at decrease? After all, technology is probably dependent on the economy (and certainly on the world population). If such an event were to occur, we may never reach this technological singularity.

Asimov is also making an amusing statement about the creation story. (A devout atheist, he often derides religion in his writing.) In The Last Question, he is toying with the definition of God by exploring how an omniscient computer could possible “become” God. If the concept of the technological singularity is true, this is possible—an intriguing yet frightening thought.

But don’t look for this in your lifetime—one thing Asimov hammers home in this story is the stretched-out timeline. If it happens at all, the technological singularity will not happen for billions of years, and our moral, ephemeral bodies simply won’t last that long. 

Heinlein’s moon colony (part 1)

As I have mentioned before, my favorite book is Robert A. Heinlein’s science fiction novel The Moon is a Harsh Mistress. I have begun rereading it again, which I do about once every year. In this novel, revolutionaries on a lunar colony carry out a revolution against Earth, which owns the colony. In the story, the original purpose of the lunar colony is to grow wheat to export to Earth, which is suffering from serious overpopulation problems. After reading about half of it, I began to wonder: could this be a practical program for the future? Could the moon be exploited in this way?

This question is multi-faceted and deserves a careful analysis. Firstly, is this technologically possible? As far as I can tell, the answer is yes. In the book, wheat is farmed in tunnels using hydroponics and ultraviolet light. Both of these are widespread today, and hydroponics is becoming very popular. The technology required to transport whatever materials are need to the moon certainly exist, as does the equipment needed to drill tunnels and make them airtight. The biosphere has been perfected over several decades, so it would also be safe to say that the technology exists to support the “farmers” and their crops on the moon. In order to ship food down, Heinlein suggests a magnetic “catapult” to launch barges of grain down to Earth. This is by no means pure fantasy—MagLev trains illustrate the potential of electromagnetism, and I have no doubt that such a catapult could be developed. Also, remember that the moon sits on top of Earth’s gravity well—with a small push, an object can simply “fall” down to Earth, and land safely with simple retro rockets and/or parachutes.

The second part of the question is: Is this practical and/or feasible? I believe the answer is yes, if we look at the project as a long term investment. The initial cost is going to be very high—in the beginning, fuel, personnel, seeds, and many truckloads worth of equipment must be shuttled up to the moon. Once we get past this initial setback, though, the cost of maintaining the project is much lower. Lunar metal can be used to create more drilling equipment, and lunar ice can support more farms. The most expensive parts of the project from here on in are shipping up of chemicals and whatever supplies cannot be produced on the moon, and the creation of the “catapult” to ship food down to Earth. Eventually, though, the returns will be enormous—food, particularly grain, can be shipped to Earth at any time of year, and it can “land” in any part of the world. If food prices continue to rise as the world population increases, grain will become a very valuable commodity, and it will fetch a very high price.  

But what are the implications of such a project, and is it in fact worth it? As I read more, I’ll continue to think about it and write another post about it. I will also do some research and get some numbers—I’m interested to see if this is actually mathematically feasible.