Prizes like the Nobel Prize, Fields Medal, and the X-Prize are given to individuals who contribute knowledge or technology that is deemed to be of value to others in society. Governments award contracts to individuals and firms to provide services for their constituents. We generally view people with money as more successful, more productive, and more important. They are the ones who have done something that society judged to be meaningful.

Now, why give these game-changers money in the first place? First, the obvious answer - incentive. Setting up rewards for those who make life better for everyone else is a great way to convince more people to do the same. Second, and less obviously - empowerment. Those who do something beneficial to society are likely both to (a) have more ideas and (b) be successful in implementing them. Viewing dollars as “economic votes” capable of redirecting human activity, rewarding those who have done something beneficial to society with money (economic power) is a great way to empower them to make bigger and better changes in the future.

The Failure of Money
So what’s the issue? Our economy is not rewarding those individuals. This problem has always existed in some form, but two features of today’s economy have magnified this little inefficiency to intolerable proportions - information and altruism. I’ll discuss them first to frame the rest of our discussion on money.

The two features closely related. As has been pointed out by many others before me, today’s economy does mostly in information. A unique feature of information that has been baffling economists and business leaders for at least the last two decades is that it is infinite in supply. The world does not have a finite number of Bach’s Double Violin Concerto. I can listen to it 1000 times in a row and it won’t stop anyone else in the world from enjoying it themselves. Unlike oil, land, or iPods, the world does not run out of Bach. Information products create atmospheres of sharing. Since my giving you a copy of a Bach album does not reduce my enjoyment of it, I have no qualms sharing my Bach. Information economies beget altruism. Again, this isn’t because information economies are noble or godly in some way; they just don’t erect barriers to sharing.

Why is this important to money? Altruistic sharers don’t expect monetary compensation and we don’t plan on giving it to them. Information exchanges occur, for the most part, without exchange of money or the expectation of such an exchange. Wikipedia, Napster, and the blogosphere have convinced us that we no longer need to pay for information.

Now part of this is great. Self-motivated learners can now independently pursue any topic of their desire without the help of a university. Environmentalists can learn how to compost, garden, and get off the grid all using freely available information online. We’re flattening the playing field and giving anyone with passion and an internet connection the chance to benefit from the centuries of society’s information aggregation. This is undoubtedly a good thing for the future of humanity.

But now we have a problem. More people are creating and sharing valuable information than ever, but we’re not rewarding them. There is no money for the thousands of Wikipedians, forum gurus, and bloggers (and once society gets something for free, don’t think you’ll ever convince them to start paying for it). The best we’ve come up with so far is advertising - a lame and oft bemoaned model for monetization.

The Symmetric Transaction and the Law of Conservation of Money
Now most of what I’ve said so far, you are likely familiar with. I hopefully have explained it a somewhat unique way so that you learned to see the issue in a richer way, but now I offer a way to view the problem that might be helpful in finding a workable solution.

The ultimate problem lies in what I call the “law of conservation of money”. That is, for any transaction to occur, we require the buyer to pay the same amount that the seller receives. The transaction is symmetric. If I want your Big Mac, I pay $5 and you receive $5.

The exchange of information, per our discussion so far, does not lend itself to such a transaction. By the infinite supply of information and the great societal benefit of its availability, we do not expect users to pay for it. Yet, by that same great societal benefit, we want producers to be paid.

What we really want then is an asymmetric transaction. We want to break the law of conservation of money.

Towards a New Currency
Now, how do we do this? There are a few key issues: the degree of asymmetry, how that asymmetry is bridged, and with what type of compensation.

First, the degree of asymmetry. We could entirely eliminate the cost for the user entirely or simply allow the user pay a smaller amount of money than the producer receives. In both cases though, we have to bridge that gap.

The bridging of this gap is essentially the role of the government. Governments are set up to invest in projects that are beneficial to everyone but that individuals alone likely won’t pursue. Now, we are seeing some individuals like Jimmy Wales (founder of Wikipedia) pursue such projects, but there are certainly many more ideas that never get off the ground because the people behind them are too busy making money in other ways. If they could make money in this way though, there’d be many more great works out there.

But how to compensate these people? With the same money we’ve been using all along? Or with something new? Remember our discussion earlier. One major goal of rewarding these people is to empower them to do even more.

The Failure of Monocurrency and the Rise of Multicurrency
Flexibility of currency is usually seen as its greatest advantage. But there’s a problem here. Drug lords and porn kings earn a lot of money because they exploit neuroanatomy and a biological human instinct for sex respectively. Bill Gates made a lot of money because he created something that changed the world and facilitated the flow of information and ideas across the globe. These are two very different kinds of activity yet we incentivize them with same currency. We reward Bill Gates and porn kings with same thing. That doesn’t seem right at all!

We need multiple systems of reward. A single “monocurrency” can do lots of things. It can purchase entertainment, the power to start new ventures, and political power. We want to dividde those things. We want to give the porn king money to purchase entertainment and happiness for himself. We want to give Bill Gates the same, but also the power to start new ventures and realize more ideas as well.

Muhammad Yunus has called for something similar to reward what he calls a social business. However you phrase it, society needs new currencies; we need to review the broad types of activities that merit compensation, determine the distinct types of compensation that those activities merit, and redesign the economy to reward human productivity accordingly.

*Note: Much of the mind fuel for this post came from a conference call with Shane Lofgren, Daniel Bachhuber, and Max Marmer. They may have more to say.

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Until a few years ago, I would have agreed. Then one serendipitous day, I met TED.com and watched my virgin TED Talk - Barry Schwarz’s “Paradox of Choice“. His point was clear. Our cognitive faculties evolved in an era with far fewer decisions and are poorly suited to deal with today’s glut of information and decisions.

A recent podcast from WNYC Radiolab (best podcast production values this side of the YouTube era) and a recent conversation with Shane Lofgren and Daniel Bachhuber on the cognitive surplus and wasted “cognitive cycles” caused me to revisit the issue. In the podcast, British neurologist and popular author Oliver Sacks describes his practice of purchasing the same, one-week supply of groceries every Sunday in an effort to reduce the cognitive cycles he spends on food decisions. Sacks points out that he feels no less joy with the same meals every week. In fact, by avoiding the slight amount of stress and regret that can go into eating decisions, he believes he’s actually happier with less choice.

Now of course Sacks made the choice to adopt this strategy in the first place and made the initial choice of which foods we would purchase each week, but the key idea still emerges. Not all choices are better served by more options and more freedom. Our time is valuable and there are choices we want to spend time making and choices we don’t.

the four shades of choice

I like to think of choices as existing on a Cartesian Choice Plane with two parameters: Significance and Novelty.

Novel, significant choices are those requiring the most time input. You’ve never encountered them before, but their consequences are meaningful to you. You’ll need to invest your time and mental effort to evaluate a series of possible decisions and select the “best” one based on your predictions of their effects. These vary by person but range from choosing a job and spouse to purchasing Christmas gifts.

Novel, insignificant choices are the most distracting and misleading. You’ve never encountered them before so their novelty grasps your attention. Yet, at the same time, they’re not especially important to you and have few significant consequences for your life. You’ll want to make these with little investigation of time investment, perhaps based on friends’ recommendations or initial reactions. These likely include purchase of a case for your new iPod, ordering of food at a foreign restaurant, or choice of wrapping paper.

Familiar, significant choices are also very important. You encounter them often but each time, their consequences are meaningful to you. They are the daily decisions that you hope to develop as “good habits.” You might invest the time to make these decisions once and from that point on, react in the same way each time, periodically re-evaluating whether this is still the “best” choice. These choices include exercise and healthy eating.

Familiar, insignificant choices are pretty uninteresting. You’ve seen them before and you really don’t care much about their outcome. You might choose to respond in the same way every time (eliminating the time burden this choice places on you at all) or you might choose a “randomly selected” response each time to mix it up. The key is not to invest too much time here. These choices include which pen to use to write a letter, which mug to use for your coffee, and which brand of kidney beans to select at the grocery store.

So which decisions do you prioritize?

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A lost gem among the wonderful flood of books merging biology, mathematics, and computers following Norbert Weiner’s “Cybernetics” in the 1960s. The only reason I discovered it is because the author is a professor at my university.

I suspect that the very reason I gave this book 4 stars will be the reason that many will give it 2 or avoid it all together - its heavy on mathematical notation. Assuming you’ve got some set theory and a hearty constitution for exploring forests of equations, this is a stellar little handbook covering automata, neural nets, perceptrons, communication theory, and error-correction - the heart of the early attempts at mathematical models of the brain. Computational neuroscience has moved into many other areas today but this is still a great place to start if you’re interested in the subject matter.

The clincher for me (and the fourth star above) was Arbib’s clear and concise presentation of recursive logics and Godel’s Incompleteness Theorem. Perhaps other books have filled this role since, but I’ve never found such an accessible presentation of it. I was literally trembling page-by-page as I entered the world of recursively enumerable sets and arithmetical logics somewhere over the airspace of Dallas, TX, emerging in a daze of sheer amazement at the airport.

I credit this book with making me comfortable with a great deal set theory and functional notation that has recently come in handy tackling modern algebra and the works of Rene Thom.

My biggest criticism is that this book does not convey the excitement of the author at all. The book reads exactly like a textbook. Profound and interesting conclusions are followed with sentences like, “The reader may be interested in learning more among the literature [see ref. 1 and 2:].” Also, while I appreciated the mathematical rigor, I believe well-placed analogy and colloquialisms would have served this book well. I suppose the style was a product of both the era and the author’s country of origin (Australia). In any case, this book still christened one of the more memorable plane rides I’ve ever had.

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Thoughts on accelerated change, the singularity, neuroscience, evolution, and more from a man who refers to the last decade of the 19th century as “the nineties”.

This book is the forerunner to a line of fantastic (yet, at times, exaggerated) works straddling mathematics, machines, and biology, known as the “cybernetics” movement. At times, this book suffers from the same affliction that Akira Kirosawa’s films do - they seem cliched and unoriginal to the modern reader/viewer who has grown up in a creative world molded by their influence. Nevertheless, it is certainly worth a look for both its historical importance and Wiener’s unique interweaving of disparate scientific fields.

Wiener is the first instance I’ve encountered of a writer adopting contemporary technology as a new framework through which to view the world. (I assume that there were others before him, but I suspect they would have been almost nonexistent before the first Industrial Revolution. New paradigms based on technology require huge technological leaps that occur within a generation for inspiration and I’m not sure there were any before then that qualify.) Today, this baton has been passed to those viewing the world as networks (i.e. Steven Johnson) and information (i.e. Seth Lloyd), but Wiener scooped them all.

Employing Claude Shannon’s new information theory, Von Neumann’s thoughts on computers, Gibbs’ statistical physics, and his own keen intellect, Wiener muses on humans as patterns of information in the entropic flow of the universe, human “transmission” (teleportation), and even the social issues stemming from it, such as the economic leapfrog played by agile third-world economics and the dangers of a wholesale shift away from menial labor (and the ensuing creation of an entire generation with no place in the world). Actually, his awareness of the ethical issues implicated by the changes he describes are outstanding coming from a lifelong theoretical mathematician.

He also employs these paradigms in ways I hadn’t seen before such as interpreting science as the decoding of nature’s secrets. He describes each species and other entity in their world as adopting its own “secret codes” to communicate with allies and befuddle enemies (yes, this was the era when every scientist in America was employed by the US war effort in some fashion and Wiener indeed worked on code-breaking). Evolution then progresses as a constant effort for an entity in the world to maintain the integrity and secrecy of those communications against the continual efforts of competitors to decode them. Its a fascinating way to view evolution (both of biological species and non-living evolutionarily stable situations in our universe), but Wiener is careful to point out that it would be a mistake to view nature as seeking to keep her secrets from man. I’m not sure he gave a satisfactory justification for believing this beyond the fact that the entire endeavor of science presupposes that we are not being lead on a wild-goose chase. (Though honestly, the physics we’re exploring know sometimes makes you wonder…) Half the battle of science and engineering is simply knowing that a solution to your problem exists. For instance, if Russian scientists were to announce that they had figured out how to encode humans and safely transmit them through broadband lines, half the physicists and computer scientists in the US would immediately drop their projects and focus on figuring out how to do it themselves. One, because no American likes to be beat by the Russians, but two, and more importantly, because they know a solution exists. The scientific endeavor (like many others I imagine) is inevitably plagued by that tiny voice of doubt inside every researchers head that says, “This cannot be done.” Wiener’s sound advice: ignore it.

Wiener’s careful consideration of the details of early computers also tipped me off to the technological desensitization that occurs with each passing generation. To Wiener, the computer’s great limitation was the time investment needed to design a “tape” customized to the user’s needs. Computers, he suspected, would spread as far as cottage industry but not down to the consumer level because consumers would never be able to afford to a hire a team of technicians to create a “tape” suitable to their needs. He never saw desktops, consumers OSs, commoditized software, and ten-year olds programming in their basements… because he never saw past the tape. The shift from “hard” software programs like a tape and those we have today is one that’s hard to appreciate if you grew up with C++, STL, and a school full of Dells. Each generation marvels at and analyzes the new; the constant or omnipresent is taken for granted and left unexamined. Wiener analyzes that which to us would not seem worth a second glance.

My one criticism is against Wiener’s stoicism. For such a revolutionary thinker, he can still be quite stodgy. His extremely disciplined childhood seems to have closed his mind to any view of invention and scientific investigation but that of the careful, ever-progressing technician. He outright condemns the idea of an engineer taking apart and building things “for fun” when he could be working toward solving the world’s problems. While I agree with his statement that its important to prioritize the “know-what” over the “know-how” question, engineering “play” is essential. One, humans are powerful predicting machines but not that powerful and a bit of leeway can lead to many an accidental discovery. Two, science and engineering is not solely for the purpose of progress. Its also a source of pleasure for those who do it. I suspect Wiener would faint like a Victorian duchess in the presence of pot-smoking, bongo-playing Richard Feynman or Dean Kamen and his technotoy paradise island.

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I read this book in the midst of a wave of readings on viewing the world as information (cybernetics, thermodynamics, information theory). I can’t say it introduced many new concepts to this conversation, but more importantly, Seth Lloyd is a wizard with strange analogies that cast old ideas in new frameworks. Many scientists are so obsessed with the importance of their ideas (read: Stephen Wolfram) that they’d be horrified to toss them around and play with them like a child learning new words. Like Feynman though, Lloyd has avoided building a scientific pillow fort and posting his “no jokes allowed” sign. (And like Feynman, he’s probably been mistaken for a baked potato a few times.) I’d like to see him write more, but his papers on arxiv are (in comparison to most physics papers) just as quirky but accessible.

If anything, this book mostly served mostly as reinforcement:

• reinforcement of my appreciation of analogy (both as an indication of understanding and a means for teaching)
• reinforcement of my interest in this line of readings
• reinforcement of my intent to apply for MIT’s quantum information summer program for undergraduates (which Seth Lloyd heads)

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This is the first graphic novel I’ve indulged in. For anyone considering this book who is wary that “graphic novels” are simply comic books rebranded by elitist, give this book a chance. This is great literature.

Watchmen is supposedly the first graphic novel to discard the stereotypes of squeaky clean heroes and concentrate on their faults. Between Gibbons’ illustrations and Moore’s strange past, Watchmen cooks up characters like Jon Osterman and Adrian Veidt that could never have existed in another novel.


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Truth and meaning are perhaps two of the most polarizing issues one can write about. Humans are generally quite defensive about their core beliefs and unwilling to accept direct criticism on them. Most books that attempt to do so simply end up pandering to their already faithful disciples (just how many evangelicals do you think have read The Gold Delusion?). Those who back “science” often declare it the absolute monarch of knowledge, place it atop an unassailable throne, and condemn all who refuse to bow as mentally bankrupt. Given that I was a staunch royalist, finding a book that probed me on these issues was surprising and enlightening.

To irresponsibly sum it up in one sentence, Against Method’s message is: “Science is not a particular set of values, rules, or methods; it’s simply whatever works.” This argument has two main parts. First, how we actually do science has very little resemblance to how we say we do science. Second, how we say we do science would be an awful method anyways.

Below are my notes while reading. They are not necessarily from the book but they are certainly inspired by it. Following, I present a few issues with the book (though if you’ve read the book yourself, you’ll notice I take issue with the book in my notes as well).

This book is incredibly rich and thought-provoking and given the acquisition of new perceptual frameworks through other books and research experience, I intend to return to this book in the future.

EDUCATION

• Scientific theories are passed on naked of their historical context. Argument occurs and only the results are passed on. The strengths of opponents and weaknesses of the idea are lost and what once had to be qualified and carefully argued as an “enemy theory” is now taken for granted and may even be taken as platitude.
• Mainstream theory is so crystallized in education that it becomes taken for granted and no longer carefully examined or criticized.
• Like the humanities, science must encourage debate and theory in class (for example, a TA might lead with “Can you explain inheritance without genetics in an attractive way?).

Acquiring Knowledge

• Experience and observation are colored by perceptual tools, prevailing theory, culture, and the intricacies of the human brain, at the very least.
• Intellectual play makes science more productive and more fun.
• Adventurers consult maps but also ignore then “correct” them.
• Results are starting points for further explanation. In science, you never “arrive” at your destination.

Natural Interpretations

• Natural interpretations are biases so common they are “natural.”
• They can arise from ubiquity in education, continual human sensory experience, and historical precedent.
• They are extremely difficult to detect. One way is to assume a competing theory is correct and discuss what must change.

Observational Languages

• Observation languages, like verbal ones, seem absolute until you encounter others.
• Certain observation languages are great for basic survival but the goal of the scientist is not survival; it is discovery.
• Unfamiliar and counterintuitive observation languages are often great vehicles for discovery.

Comparing Theories

• Prevailing scientific theories are a product of politics, history, power, economics, religion, culture, philosophy, evolution, neuroscience, memetics, and many other influences. Divorcing them from their stories discards a great deal of important information.
• Ideas are often presented before the means or modes of thinking to verify them are available and are therefore often prematurely disposed of. For this reason, we cannot ignore old passed-over ideas on the assumption that they are wrong.
• Historical precedence is not a virtue. Yes, we may need to print new books, change university courses, etc but perhaps we must rethink such rigid investments instead of compromising on the ideas.
• No theory agrees with all the facts available, so disagreement with facts is no criterion for disregard.
• New theories are like grains of sand in a clam and can, though seen as an irritation at first, seed an aggregate of new ideas that form a pearl of science.
• New theories don’t necessarily have to solve or adhere to the old problems of old theories. Theories describe their own problem spaces.

Other Disciplines

• We cannot ignore the “non-sciences.” People believe in them for some reason and by investigating this reason, we, at the very least, learn something about memetics and the human mind.
• Other disciplines may also discover productive world views capable of framing observations long before those observations are actually possible. Looking to them for assistance, particularly in times of new or unexplained data, could prove to be helpful.
• One major goal of science is personal pleasure. Attacking other disciplines for their focus on personal pleasure is indefensible for science.

Issues

• The anarchistic approach to science is particularly compelling for the individual scientist because it is free of restrictions. It grants him the freedom to study whatever he likes in whatever way he pleases. Scientists as individuals then might be necessarily biased towards it.
• The anarchistic approach to science also, however, grants credence to fields traditionally outside science (like Chinese traditional medicine and homeopathy). This approach challenges science’s unassailable claim to the purveyor of all knowledge. Science as an institution then might be necessarily biased against it.
• I believe science can be defined, not by method but by intent: Science, united under the shared goal of discovery, is the open and continuous questioning of nature accompanied by predictions and, to the greatest extent possible, their verification. (Alternatively, science is a bundle of current and possible procedures unified under the shared goal of understanding and predicting.)
• This book does not stand alone particularly well. Significant parts of it are responses to debates and other books that aren’t always introduced. I’d highly recommend reading “The Structure of Scientific Revolutions” by Thomas Kuhn first. It presents much of the backstory for “Against Method” in a more self-contained and accessible way.

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DESIGN OUT OF CHAOS WITHOUT MIND
This book is not “yet another pop-sci book on evolution.” It does not set out to convince the reader with a series of well-known arguments that evolution is true. Instead, it assumes you’ve accepted the idea and explores it as an abstract framework for understanding the world. It is the first and only book I’ve encountered that takes evolution as a worldview and not just a biological explanation of speciation.

I drew far too many wonderful ideas and frameworks from this book to write a review essay-style, so I’ll enumerate the most salient ideas by topic.

HISTORY OF THE IDEA
-Natural selection may have been the first strong step toward viewing the world by processes and not things.
-Humans ignore gathering pools of evidence until an explanation of the mechanism is proposed. In other words, we seem to value understanding and predictability over evidence.

POSSIBILITY AND DESIGN SPACES
-Speciation is not the presence of something (read: an essential nature of a species); it is the absence of reproductive bridges between related organisms.
-Discovery and invention are indistinguishable from the framework of possibility spaces. One doesn’t invent theories or configurations of matter; one discovers them in design space.

CAUSATION
-History is made relevant by the future. This is especially true in evolutionary biology, in which the evolutionary past is unavoidingly coupled to the future.-Speciation is determined by the future survival of one’s ancestors; not by the contemporary actions of a proverbial “Adam” or “Eve.”

PHILOSOPHY AND LIFE
-Life is a statistical fluctuation of low entropy.
-Life is matter grasping at a rock in the river of increasing entropy.

MISCONCEPTIONS
-Evolution does not process the “best” solutions; it produces “stable” solutions.
-Evolutionary thinking is not the simple application of determining whether or how a trait increases rate of survival. It is the intricate conversation that takes place between concepts such as forced moves, culture, genetics, survival, reproductive prowess, and stability.

MEMETICS
-Memes operate under different selection pressures in different groups (i.e. science, fashion) and at different levels of magnification (i.e. individuals, families).
-Commitments can be viewed as stable governments of memes. In others words, a stable collection of memes that support one another.

INTELLIGENCE
-Intelligence may be embedded in objects. We invest some intelligence in designing an object to be used by others. A user may, without a manual, recognize the use of the object and gain intelligence through it. Objects then may be seen as vectors of intelligence and sources of inspiration.

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First, the good. Penrose weaves tales of science, philosophy, and history that few others can, due to his wide-ranging and vast intellect. He touches on a wealth of interesting subjects in this book and his enthusiasm for them bleeds through the pages. In particular, this book offered the most illuminating introduction to entropy (in the “Cosmology and the arrow of time” chapter) that I have ever read. In short, before I read it, I didn’t believe in the second law of thermodynamics. After I read it, I could interpret the entire world through “entropy goggles”. In other books, entropy was some esoteric concept; here it is a beautiful and central feature of our universe.

Now, the irritating. Penrose’s stated goal in this book is to convince the reader that strong AI will not be realized. In other words, what human brains do, no computer ever could. Yet, however many fascinating ideas he introduces, his core evidence is little more than hope that what he does as a mathematician is unique; that human “aha!” moments are somehow distinguished from anything a computer ever does.

Penrose fervently declares that he is no “formalist”, claiming that the mere idea of a computer arriving at mathematical proofs makes the pursuit of mathematical truth “meaningless”. Why? A computer may arrive at such a truth, but it is the human’s role to make human meaning out of it. Meaning isn’t some quality embedded into the fabric of our universe. It is a manufactured human ideal - a wonderful, enjoyable one at that.

Penrose goes on to cite the vague notion of “reflection principles” (the imprecise methods by which the human mind discovers mathematical truth “upon reflection”) as above and beyond algorithms. He uses these “aha!” moments as support for his argument that algorithms cannot possibly imitate what we do. Yet, how can we be so sure that these “aha!” moments do not arise from some complicated algorithm themselves?

Perhaps, any human-created set of mathematical axioms will always be subject to “reflection principles” and only a more intelligent species could create a set for which there are no human-generated “reflection principles”. Perhaps the notion of computability simply refers to a hierarchy of skill among complex adaptive systems. (If anyone knows of a book or research on such an idea, please let me know)

Finally, on Penrose in general. Penrose’s books tend to occupy a literary no-man’s-land between popular science and technical writing: too technical for the average hobbyist yet not deep enough for a student in the sciences. It seems he’s just too damn smart to recognize what falls into each category (for example, he might spend half a chapter explaining fractions and then breeze through Hamiltonians in half a paragraph). For me, he’s best as a connector of mathematical and physical ideas after I’ve been formally introduced to them.

As any good book should do, this one did leave me with a few questions (besides the above):

• Which is a deeper truth - math or physics?
• In reflecting on the story non-Euclidean geometry, what else are our evolutionary adaptations leading us to falsely assume?
• Has anyone checked whether Hamiltonians would be deterministic for computable universal constants and discrete input?
• Can we really separate dynamical equations from boundary conditions? Are not boundary conditions simply consequences of other not-yet-understood dynamical equations?

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The writing in this book deserves 4 stars. The ideas, however, deserve 2, and since I judge books on ideas, the book itself gets 2 stars. I’ll review each aspect of this book separately.

The Writing
This book communicates emotions like none I have encountered before. I assume this book was semiautobiographical because I don’t know how Hosseini could otherwise have charged it with so much emotional character. At times, I felt so affected by this book that I wanted to put it down. I wanted to stop because it was uncomfortable for a book to have such a hold over my emotional state. I won’t give away what those emotions were (for those who haven’t read the book) but I commend Hosseini for his ability to elicit such an experience in a reader.

The Ideas (Spoiler Warning: You may not wanted to read this section if you haven’t yet read the book.)

‘The Kiterunner’ ultimately praises sacrifice and suffering for the sake of others as a highly honorable trait, an assertion that I could barely stomach while reading this book. Hassan occupies the role of hero in this story for the first half of the book, based on his tendency to subject his desires to those of others. Amir attains his own semi-heroic status only by imitating these actions and again sacrificing his own happiness for others.

I find it entirely despairing that suffering and asceticism still play such a prominent role in our moral lives. Life is too often painted in literature as a win/lose game in which wealthy, happy, or successful become so only through the suffering and loss of the poor, unhappy, and unsuccessful.

For readers of this book (or others) dismayed by such notions, fear not! The world is not so! Life can be a win/win game. Happiness does not require suffering and books that perpetuate this moral myth do a great disservice to the world.

For a more uplifting view on happiness, check out Ayn Rand’s The Fountainhead.

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