Minds and Markets

Keith Gessen’s one minute manifesto, “it is time to say what you mean” is embodied in the title of this novel. It is beautiful and soul-baring. I started reading “All The Sad Young Literary Men” at 1:30 last night and I havn’t been able to sleep much since. I don’t know if one caused the other. But the book has affected me.

As you read the accounts of the phonies and rye catchers, if you are of a literary bent all this will seem familiar. The stories quicken your pulse, make you smile and groan with recognition. You see what it is to be young, to be steadfast, to make mistakes with women. Gessen weaves the duties of generation, youth, class and gender into an account of what it means to be literary and full of hope, to be brilliant and common, to think the world can be remade and to ignore the impending mediocrity even professional success can bring.

Our heros (and when we are allowed, heroines) are religious. Their lives find structure not so much in following principles but choosing to recognize them. The moral high ground does not require effort, it’s a decision, an attitude. They seek salvation not in love, which seems to be an undeserved earthly pleasure (what business does a thirty-year old almost-PhD have getting laid a lot in NYC?). It distracts from the pursuit of the Big Idea. Gessen’s taste for transcendence, transparent in his feted literary zine n+1, lends a welcome messianic element to a book ultimately about our mortality.

There’s hardly anyone mentioned in this book over thirty. The youth seemed to have dissolved the bonds of authority, and reached out to explore their brilliance, only occasionally tethered by their wallets. The fetishization of youth does not seem repulsive, but deserved. Didn’t we save, skip meals, avoid high-paying work? Don’t we deserve our drinks, our contrived intellectual stances, our denial of impending reality?

Gessen’s account of the unfolding of the sentience of youth is simple and precise. Our college selves just wanted to be seen as an embodiment of a set of ideals, to be recognized at the party at once. It was when we stepped out in the world we sought to assert our individuality. One of hallmarks of poor decision-making is believing you are good at making decisions, and though we wish we could anticipate our misconceptions and pick different battles, we know that forging one’s path in life cannot be accelerated or handed-down.

But we have to hand it to Gessen for trying. He offers us a thirtyish critic, milking the meager but pleasant reward of the attention of youth and with his opportunity to pontificate in his kitchen over breakfast, for a roadmap to his sort-of success:

‘”When you are young”, Morris said now, looking out his window, his back to us, “and you’re on your way, and you have everything before you and everyone with you - you don’t know anyone else - and you look at all the others with their screwed-up lives and you know you’ll do things differently, you know you will, and you do. You are kinder, gentler, you are smarter. And then one day you look up and you’ve done all the thins you said you were doing to do but somehow you forgot something, something happened along the way and everyone’s gone, everything’s different, and looking around you see you have the same screwed-up life as all those other idiots. And there - you are.”

After suffering from an accident that left him covered in third-degree burns, swathed in bandages for three years and fed 30 eggs a day to help his body heal, Dan Ariely recounts that what he particularly dreaded was spending his time immersed in a disinfectant bath. Not because the solution burned a little, but because the nurses would have to peel off his bandages first. On a much smaller scale, many of us have wondered which is more painful, tearing the bandage off at once for  quick burst of intense pain or enduring slow, creeping pain as we slowly peel. Ariely says tearing bandages off at once is more painful, and I believe him.

This, as the ads go, is psychology in action. Far removed from the sterile questionnaires probings the minds of white, middle-class college students, real people’s lives are affected by other’s theories of psychology. It’s easy to see where Ariely gets his passion for hewing his experiments from the stuff of everyday life. When he returned to the hospital years later with his studies on pain, the staff were attentive. But the problem is that it’s not just that the patient’s pain that must be addressed, it’s the nurses as well. Recalling the grimaces on the nurse’s faces, Ariely must have learned a lesson in how psychology toys with economics. If the nurses acknowledged there was a way to reduce pain for their patients, they would feel obligated to reduce it. But to reduce it merely halfway when it could be eliminated would seem like cruelty, pain-reduction seems to be an all-or-none proposition.

Where psychology meets economics, where people are found expressing preferences that don’t actually benefit them, or lack stable preferences, or are unable to successfully evaluate their options, a behavioral economist is poised to jump around the corner and triumphantly shout “aha” and then run off. Not Ariely. “Predictably Irrational” is his attempt to stand and deliver. Because Ariely’s research interests are eclectic and he is an excellent experimenter, he is able to triangulate on some interesting features of mental life, and his book’s earnestness for the research he loves wins us over.

Documenting that irrelevant options, contra to modern economic theory, do indeed influence our choices can be a real yawner.  Comparing items A and B that are different but of comparable value is difficult, but by introducing an inferior option C similar to A, the comparison between A and C is readily made and A is perceived to be globally a better option. But Ariely’s brilliant insight was to show us that this sort of decision process doesn’t just apply to choosing between breadmakers, it applies to how we choose between attractive mates. By presenting photos of two equally attractive mates and one altered photograph of one of the mates, students were much more likely to choose the mate that had the benefit of a clear comparison. But this is where Ariely’s book suffers. His policy advice: take an ugly friend that seems like you out to the singles bar.

Ariely is like a teenage magician so excited he has our attention that he rushes through his tricks. If he slowed down and took some time with his strongest ideas, this could have been a better book. His chapter on the power would have particularly benefited. After showing that we change our preferences for candy when the prices for two options go from 15 and 1 cents to 14 and zero cents, in violation of the assumptions of traditional economics, we would have appreciated his insight into the mechanisms behind it. Maybe, instead of subtracting costs from benefits in order to compare options, we divide benefits by costs, which would certainly explain why I spend most of my weekends in the library.

Social relationships are treated discretely, and a common medium like money cannot bridge the chasm between the rewards we expect and offer in these different relationships. Lawyers oppose offering needy retirees advice at $30/hr but eagerly help for free because they prefer to keep their market value high, and separately want to feel they are contributing high quality services out of the goodness of their hearts. This is a beautiful example of how to structure win-win transactions, one of the free lunches (getting more economic benefits from just rearranging the pieces) behavioral economics can offer. Because we model our value from previous economic transactions, this is why initial price anchors stubbornly persist - people don’t want to feel their initial efforts were undervalued, and they prefer denying themselves higher salaries and sever the past. Ariely missed opportunities to tie these ideas together. But in spite of the haste, this book is a charming tour of some of the most interesting findings of psychology and economics. If Ariely chose to follow up with a book subtitled “The Hidden Mechanisms That Shape Our Decisions”, I’d certainly give it a read.

From all the fuss we make about sparse text messages from friends (”omg luv nyc”) and emails sent without salutation, it’s obvious that communication is not just about information transmission. Our closest relationships are built and maintained around shared feelings, not shared information. And yet there are a contingent of politicians that seem to believe that people decide whom to vote for by weighing evidence and calculating economic self-interest. Needless to say, these politicians lose a lot.

For Drew Westen, the Democrat’s failure to communicate and lack of a mandate requires nothing less than a new theory of mind, which he attempts to lay out in “The Political Brain”. The Democrats have placed their faith in an outdated theory of rationalism, in which voters seek out information on policies and choose them based on a calculus of self-interest. It’s obvious our identities and morals are rooted in a much more powerful system, the chemistry of our desires and fears. Because emotions can be prickly and fickle, tapping into this source of alternative energy requires some thought.

So how does Westen’s approach fare? The science is inconsistent and lacks a meaningful narrative (sound familiar?). To say people possess “competing networks” and that people are conditioned to stimuli like Pavlov’s dog makes for as outdated a theory as, well, unbridled rationalism. Minds don’t passively “gravitate” or “equilibrate”, they actively engage the world to construct meaning. Westen’s watered down theory of mind leaves little room for serious discussion of the implications of psychology research or an intelligent treatment of how voters decide. But some of his political analysis is dead on. If emotions are what people run on, then it is in the Democrats’ interest to find emotionally charged issues, rather than shy away from them. A politician needs every opportunity to connect with a voter’s emotion, and Democrats have been to scared to to stand up and be honest about what they stand for. Of course, we didn’t need a scientist to tell us this.

Westen makes much hay from the fact that certain policies are more evocative than others, and Republicans have captured the interests of many voters on stances on abortion, gay marriage and gun control. But a scientist sees this and asks why would it be that some policies are more attractive to begin with. Opportunities missed like these make it obvious this book was never about an introduction of the mind in politics, but about justifying his political preferences post hoc. And we saw how successful that strategy was three years ago from George Lakoff, author of “Don’t Think Like an Elephant” that offered similar rhetorical massaging with lukewarm results.

Westen doesn’t draw the line between scientist and partisan. He seems as much a product of Washington-style politics as anyone else in his taste for “folksy” wisdom rhetoric, bigger-dick confrontations, pious invocations of God and political opportunism. If politicians are looking for their way out of the darkness, they will need a guiding light with some distance.

It’s damn near impossible to intuit the hidden workings of our physical universe. But after taking a physics course, even a humble pendulum is imbued with elegance and precision. You don’t really have to be sold on the science of physics, the profit comes soon enough. Sit down long enough to learn a few basic principles, and all of a sudden you can see how a spring can be like a pendulum. But the science of mental life is a harder sell. The stakes are higher. Sure, even if it seems like an ice cube is seeping cold into my hand, it’s a small loss to find out it’s really absorbing my heat. But what if our mental life is not what it seems?

People are bound to put up a fight. So enters veteran Steven Pinker. “The Stuff of Thought” is like watching Muhammad Ali at the top of his game - a lot of beautiful footwork, and the punches are an afterthought. The knockout jabs are delivered so fast we rewind the tape. How did he do it?

He hit us where we least expected it. Who would have thought how we use our verbs could reveal how we assign moral responsibility? The puzzle starts with transitive and intransitive verbs - wait, don’t leave just yet folks. Trust me, I’m not a linguistics-type guy, but this gets interesting fast. Some verbs can be used in a form that focuses on either of the objects mentioned, such as hay in “Hal loaded hay into the wagon” or a wagon in “Hal loaded the wagon with hay”. But it’s not universal. Why is it we say “Tex nailed posters into the board” but not “Tex nailed the board with posters”? One answer might be that language is the servant of our concepts. Then, the rules of language might reflect properties of the concepts we hold. Concepts such as actor and subject. So the mitigating factor in these verb constructions is whether we mean to say “something was moved into something else” (’loaded hay into the wagon’) or “something was changed by doing something to it” (loaded the wagon with hay).

But Pinker has lured us in. The syntactic fussiness of verb use gives way to a semantic fussiness, because not all actions are the same. We can pour into a glass, onto the floor or into the ocean, all acceptable because we don’t care about the final state. Conversely, “fill” is flexible about how the action is accomplished - whether by holding a glass out the window in the rain or scooping it out of a bathtub.That’s because “filling” is about a change of state in the object and “pouring” is about a change in motion. So how do we ever know when a verb implies a change of state or a change of motion? The answer seems to lie in our underlying model of causation.”Pouring” implies a weaker causal force than “filling”, with less control. We learn that our verb usage also implies a model of agency, that is, what entities in the world are capable of producing or accepting actions, which leads us to the language of intention, where the stuff of morality likes to hang out.

By MOVING hay into a wagon, the wagon changes STATE, which is conceptualized as MOVING from on STATE to another. We treat changing entities like moving entities. Our verb usage reflects an underlying theory of physics. Pinker has used this concept to prop up various arguments in “How the Mind Works” and “The Blank Slate”, and I sense he was buying time until he put his thoughts in order on this subject. Our linguistic demarcations allow us to look at the same scene and pronounce it accurately as “a few sausages” or “a lot of meat”. Just as we say earlier in our verb usage, different modes of referring to stuff, time and space do different kinds of work depending on the meaning we are trying to represent. And again, the meanings we are trying to represent are crucial for assigning moral responsibility and knowledge. We are responsible for what we are conscious actions, and we are conscious of whatever is “now”. Anything previous to that is in the past, which is thought to be knowable, so when Scott Peterson referred to his wife in the past tense, it revealed what he already knew. The future is unknowable, and hence any reference to future worlds necessarily reflect some representation of our intentions and desires.

Pinker cheekily offers the use-mention distinction (”hey, I didn’t say you were fat, I’m just repeating what she said”) as a justification for his chapter on cursing, but we see the showmanship behind it. We explore the logic of cursing in the different contexts we use it, the hidden story of power and inequality behind our curses, and what it reveals about our private and public desires. It certainly doesn’t leave you with a compelling theory of the nature of cursing, but it’s a satisfying morsel. “The Language of Thought” delivers the knockout blow in the chapter “Games People Play”. Innuendo is absolutely pervasive in our social use of language, so we don’t realize there is something ridiculous about saying “if you could pass the guacamole, that would be awesome”, which it might be if you were to use the Force. Why do we use indirect speech at all? Isn’t language about communication?

Certainly, but unpacking the language we use reveals communication is not just about information transmitted, it’s about the relationship between hearer and speaker. One influential account, in trying to account for the difference between what we say and what we mean assumed that speakers tacitly communicate with the intention of harmonizing with the hearer’s knowledge. Just as the greatest artists master and then break the rules, deviations from this implicit rule carry valuable information about the speaker’s beliefs. Considerations about social goals are important as well. The circumlocution of our guacamole comes from our goal to make the hearer sense an opportunity for a social interaction while avoiding the awkwardness of issuing a command and being denied.

“As with so any aspects of the mind, a danger we face is the temptation to explain a puzzle by appealing to intuitions that feel thoroughly natural but that themselves need an explanation”. It feels natural to assume speaker and listener are trying to cooperate. But the reality of human life is that so much of our relationships are as much defined by conflict as cooperation. Ask yourself who you love the most in the world? Then ask who has the capacity to frustrate you the most? For many, the answers to both are family members, often the same people. Pinker shows how the logic of plausible deniability isn’t just a tool of warring nations but of friends contemplating a casual tryst. Our relationships aren’t set in stone, but are constantly being negotiated, and language is a wonderful medium to do so in. But we aren’t all like George Costanza, we know that “coffee” doesn’t mean “coffee”, sometimes it means “sex”. The resolution lies in our implicit recognition of language as a digital medium. We treat overt propositions as certain, and anything else as merely probable. We know from an entirely different terrain of psychology that humans treat 100% certainty as being significantly different than any other probability. We can coordinate in the face of uncertainty over that which is certain, but the rest is just conjecture.

“The Stuff of Thought” isn’t just a good way to learn about features of the mind. It represents some of the best detective work on the unexpected side of our mental life. The gaps of explanation here simply invite us to go further down the rabbit hole.

Over a souvenir postcard of Jacques-Louis David’s famous painting of Socrates prepared to meet his fate, de Botton mused:

“If the postcard struck me so forcefully, it was perhaps because the behavior it depicted contrasted so sharply with my own. In conversations, my priority was to be liked, rather than speak the truth. A desire to please led me to laugh at modest jokes like a parent on an opening night of a school play…I did not publicly doubt ideas to which the majority was committed. I sought the approval of figures of authority and after encounters with them, worried at length whether they had though me acceptable. When passing through customs or driving alongside police cars, I harbored a confused wish for the uniformed officials to think well of me.”
 
A sumptuous treatment of what are perhaps banal concerns. Yet de Botton shows that everything depends upon a forced laugh or a hazy definition. Philosophy is made of banal concerns, elusive everyday stuff that can be unpackaged. Will more money make us happy? Does hardship bring wisdom? In showing how philosophers, men who ate, ached and puzzled as any others treated these concerns, de Botton describes the process of uncovering truths, accessible to us all.

Starting with this inspiration from Socrates, we wonder that if we are to create a set of beliefs of our own, how are we to handle possessing unpopular conclusions? Socrates was concerned with what justification people provided for their beliefs, and whether their beliefs could be justified. We are a product of our beliefs about the world, and if we never examined them or chose them, we would be no better than automata enacting instructions. On what basis can we chose? Socrates offers an an answer and a method. We ought to chose those beliefs that cannot be contradicted, that is, those that are necessarily true. We can discover these by taking a statement such as “being virtuous requires money” and questioning if there could be a situation in which the statement is not true, “could one ever have money and not be virtuous?” Exceptions will show the definition is either incorrect or that the definition is imprecise and must be modified. Rinse and repeat. The simple power of this algorithm speaks for itself. Already we see the tools for clarity are not difficult to master, one must only possess patience and will to to continue. As Epicures noted, “The man who alleges that he is not yet ready for philosophy or that the time for it has passed him by, is like the man who says that he is either too young or too old for happiness”.

For Socrates, truth-seeking itself offered salvation from our confusions, but Epicures sought a more direct means of inquiry to our satisfaction. A simple analogy suffices to describe his subject. Just as each of us may have intuitive diagnoses and prescriptions for our maladies, we are aware that we are often uninformed or worse, so under the influence of our ailments that we may make poor decisions about our health without the aid of someone trained to inquire and prescribe remedies. There is no reason why medicine should be such a privileged domain over any other, that we cannot believe the same may be true for our state of happiness as our state of health. Epicures offers philosophy of the utmost pragmatic value, “just as medicine confers no benefit if it does not drive away physical illness, so philosophy is useless if it does not drive away the sufferings of the mind.”

The conclusions Epicures and his friends drew is that happiness comes from the company of good friends, a life unencumbered by pursuit of money or status, and accordingly freedom to spend time in contemplation of life. In order to determine whether a pursuit will bring us happiness, we can bring the Socratic method to bear to ask if the pursuit will yield any of the three foundations of happiness. Given that we ought to know the answer in advance, application of the method may simply serve to show why it is so. Why do we err in seeking happiness? de Botton offers us his own insight: 

“Objects mimic in a material dimension what we require in a psychological one. We need to rearrange our minds but are lured towards new shelves.”

Advertisers exploit our natural desires - we may be tricked into buying a Jeep when we were really looking for freedom. If commerce is the stuff that makes life move forward, then ought we to believe that society is doomed to forever err? We will need to think more of happiness later. 

Just as Socrates earlier, Seneca too faced death for what he believed, but Seneca’s strange calmness came from another source. Epicures hinted at this strength: directing thought to mortality, for example, is so that “what is no trouble when it arrives is an idle worry in anticipation”.  Early on, the infant learns the world is not willed from within and our condition is laid bare. If Socrates was primarily concerned with rationality and Epicures with feelings, Seneca offers a connection. What is frustration? A ready answer is that it is an emotion that surpasses our rational selves when we are thwarted. Seneca recognized that this did not answer the question, but merely left it to another to ask why an emotion should respond to conflicts of will at all. His answer is that we are frustrated because we came tot he problem with the assumption the world ought to work in our favor, we had hoped for the best of all worlds. To adequately cope with limited resources in a world without gumdrop rain and creampuff pillows, we ought to expect for the worst. 

There are interesting consequences. A friend of Seneca, a loving mother was devastated by the loss of her son. Seneca showed that her torment lay in her belief in a just world. If she subscribes to the belief that good things happen to good people and bad things happen to bad people then she is left with a dillemma. Either she was a bad person that such a calamity befell her, or that she is a victim of failed administration of justice. Both of these feelings sap one of any feeling of agency, such are the gnarls certain beliefs leave in warping our mind. Conversely, in attributing the things that thwart us agency, as if they existed in order to thwart us, we make martyrs of ourselves. We feel impugned, and lose our sense of self and worth. It is essential to clear thought to maintain one’s identity independent of one’s circumstances. 

Seneca showed us that a way out of frustration is to prize independence of mind by ensuring the uncertainties of the world are kept external to it. Montaigne took a different approach to handling the problem, instead advocating a celebration of our confusion and advertisement of our limitations. Seneca showed we are dogs tethered to a willful cart with the choice to fighting or easing our journey by following fate. Montaigne too believed we are tethered, to our worldly needs and epistemological limitations. The roots of frustration that Seneca identified has deeper roots still, originating in our belief that certain ideas are natural, an overconfidence in our view of the world. To learn, we must expose our minds to different ideas and question what is natural. Truth is to be found everywhere, not in books written in tortured prose for “difficulty is a coin which the learned conjure with so as not to reveal the vanity of their studies and which human stupidity is keen to accept in payment”. Montaigne is honest and detailed, even down to his sexual inadequacies and physical ailments, and here we profit from de Botton’s sense for the details that illuminate the beliefs a philosopher espouses. 

This style works best for Schopenhauer’s life. We immediately see him as a harmless crank, and in light of this his beliefs that the world is made of frustration become comical. His search for satisfaction led him to ponder how his self-proclaimed massive intellect could be diverted by the gaze of a maiden. He could not as Montaigne could, cheerfully recognize the indignity of a fart or the frustration of an empty stomach. What could it be that could overcome the rational mind? It must be a powerful force independent of the human faculties, so Schopenhauer turned to nature for a will-to-life, a drive to stay alive and reproduce. Schopenhauer’s interpretation of biological evidence is to be praised in modern terms on a number of grounds. He offered evolutionary considerations in the design of the mind, and presciently recognized that conflicts of interest exist between an organism itself, their mates and the forces that produced them, which he believed to be “for the benefit of the species” but are more likely to be for the benefit of the genes. This even leads to a theory of love, that we are attracted to those who would best cancel out our genetic deviations (there is significant evidence that genetically average individuals are healthier, and attractive faces exhibit average traits) and that love is justified after the fact. 

But our interest is not so much in Schopenhauer’s (or anyone else discussed here) empirical accuracy, but in his approach.  In questioning why is love fraught with hardship, his answer was that love (and life, interrupted by love) was never about happiness to begin with. This serves as an abrupt lesson for the reader, accustomed to thinking philosophy as the device that converts experience into pleasurable conclusions. No one administers such bitter medicine with such delight as Nietszche: 

“What if pleasure and displeasure were so tied together that whoever wanted to have as much as possible of one must have as much as possible of the other” 

“…ask yourselves whether a tree that is supposed to grow to a proud height can dispense with bad weather and storms…”

That essential belief that perhaps our other philosophers took for granted, that pain and pleasure are apposite is suddenly challenged. This epistemological challenge serves in order to show us that success is to be strived for, to be earned and paid for in blood, sweat, tears and toil. By Nietszche’s own admission, the mind is a product of the body and thus it’s climate, and de Botton cleverly shows us the alpine origins of a belief in striving for this Swiss (”I am distressed to be Swiss!”), how Nietszche came to realize that as with glaciers, “so it is, too, in the history of mankind: the most savage forces beat a path, and are mainly destructive; but their work was none-the-less necessary, in order that later a gentler civilization might raise it’s house.” We all possess the potential to realize our will-to-self, but we must recognize we are born limited and must strive to earn our place. The solution, beyond Seneca, is not merely to accept uncertainty and difficulties but to endure in hope of being one of those unreasonable men that may change the world. Intellectual honesty is denigrated by pretending to deny our desires or accept inferiority. The worst, he said, would be to anesthetize oneself with consolations. 

These are heady days for cognitive scientists. Arcana such as “The Stuff of Thought” or “Musicophilia” top bestselling lists. Steven Pinker’s article on the moral sense in the New York Times Magazine is instructive. He explains that moral reasoning is not to be thought of as a set of beliefs or feelings about the world but rather a lens to view the world through, very much as our more salient senses are. Moral reasoning is typically performed automatically and justified retroactively. What’s striking about this article is that it represents a new approach for a timeless and elusive aspect of cognition. The computational approach to cognition and the dance of neuroscience, evolutionary biology and economics has been tremendously productive in generating theories and predictions by recognizing the best approach asks not only what brains do but what they are for. “Why Choose This Book” is a wonderful contribution to this tradition. Psychologists tend to suffer from physics envy, but Montague has happily avoided this because he is by training a biophysicist and now a neuroscientist. His energy and enthusiasm for physics, computer science, economics and psychology gives him a quite original approach to thinking about what the mind is for, and he does an excellent job of guiding us step by step to this new conception that is driving research today.

Until our language and reasoning changes a great deal, it will still be most convenient to use Cartesian dualism, even for scientists (”here we see a picture of my brain” is an odd thing for a brain to say) to informally discuss the mind. Most attempts at explaining cognition have attempted to dissect it without reference to its function. The functional approach in science, ushered in by William Harvey’s question of what valves in veins are for, is one of the great triumphs of human reasoning. Functional approaches to the mind are much younger. Charles Darwin provided the foundation for the modern conception of mind by showing that evolution is the method for imbuing matter with goals. Alan Turing provided the conceptual revolution that showed how mechanistic processes, including biological ones, are about manipulating information. Evolution is an algorithm for producing propagating entities working on their own survival.

With these two innovations, cognitive science found a solid foothold. But somehow this is not enough to say what the mind is for. Is cognition about learning what is true about the world? Hard to say, but Donald Hoffman, a vision scientist who’s put much thought into this thinks not:

“It used to be hard to imagine how perceptions could possibly be useful if they were not true. Now, thanks to technology, we have a metaphor that makes it clear — the windows interface of the personal computer. This interface sports colorful geometric icons on a two-dimensional screen. The colors, shapes and positions of the icons on the screen are not true depictions of what they represent inside the computer. And that is why the interface is useful. It hides the complexity of the diodes, resistors, voltages and magnetic fields inside the computer. It allows us to effectively interact with the truth because it hides the truth.”

In “On Intelligence”, Jeff Hawkins organizes intelligence around prediction. While certainly a useful explanation for explaining lots of properties of information processing and collection, this misses some key aspects of cognition. Unless prediction as a concept is so loose as to be meaningless, in what sense are our social interactions about prediction? How do we model other intelligent beings? It’s reasonable to conclude the primary reason I wish to know other minds is so I can take advantage of their experience, but to what end? The reason why intelligence is a property of the intelligent creatures we observe is that they are products of evolution.

Cognition is not some quirky preference of the algorithm, but rather the consequence of creatures with limited lifespans seeking to navigate the world and obtain resources. Creatures do not simply compute, they care about survival. Because life and resources are necessarily limited, organisms must make choices. As Montague points out, this means decisions are not disembodied from the constraints of the flesh, as Descartes would have it, but rather are inextricable linked to the goals of the organism. The key to navigating the world then, is more than just prediction. It’s valuation. Prediction, in the sense I am trying to malign, resembles a gentleman-scholar pinning butterflies in his study. Valuation comes from the hungry kid on the floor of the Merc - his nervous hands, his eye on the clock, the elbows all around. Evolution looks through his eyes.

Our gentleman-scholar is free to pursue his goals without consideration of cost. If there is a rare butterfly, cost is no object to mounting an expedition, even if this rare butterfly may add little knowledge of its genus. Montague considers computation without consideration of cost to be an odd and perhaps unfortunate legacy of the Bletchley Park lads (including Turing) who poured as much energy as they could to crack Enigma, the encryption system used by the German U-boats strangling Britain. Our young trader is acutely aware of the opportunity costs of his actions (even taking a bathroom break). Further, knowledge-gathering is not arbitrary. Our gentlemen scholar could just as easily study weather-formations at his cabin. The information the trader gathers directly impacts whether he will be able to return the next day, and indeed, he is rewarded for extracting extra information others have not considered. Traders and poker players alike seek “tells”, tell-tale signs of another’s behavior.

Montague refers to these properties of evolved creatures as “efficient computation”, where “instead of just the computation, there’s the computation plus ’something else’ and that ’something else’ is a measure of the value of that computation to the overall success of the organism”. Organisms possess goals, and guidance signals are feedback mechanisms used to provide suggestions on approaches and provide updates on progress. Valuations not only dynamically represent the expectations of achieving a goal but also organize the algorithms available to accomplish them. How does an organism compare algorithms? One way familiar to computer scientists of evaluating the efficiency of an algorithm is to compare it to other algorithms capable of producing an equivalent result. Evolution then places a premium on the ability to simulate algorithms, to navigate counterfactuals. Underlying this capacity is the ability to model other modules (individual components or steps that comprise cognition as a whole), which may be the happy by-product of modules that operate too fast for feedback and must simply provide related modules with a model of it’s actions. Its important to pay attention to the absence of the humonculus from here on out: to every module, *everything* else is “out there”, whether originating in the brain or in the outside world.

Valuation is necessary in an uncertain world. In order to build models, modules have to come to be able to extract information in spite of the noise inherent to the world. Reverend Bayes asked how, from a limited sampling of data, could we infer if there was a rule producing the data we observed. We’re all Bayesians now, and modelers must be able subtract noise from signal. Modules must recognize when there is opportunity to refine models (efficiently, of course) and the limitations inherent in a noisy world. Montague permits a illuminating aside: this noise may be appropriated for an excellent purpose. Organisms can use this noise to vary behavior, as Montague’s rabbit rehearses slightly random escape routes. Organisms engaging in exchange may wish to broadcast that they are unable to possess full models of their own behavior, eliminating any tells to be exploited. I wonder if organisms might actually prefer to trade with such partners - smart opponents last, and trade is beneficial.

Back to valuation. How to compare the effectiveness of one algorithm or another? Montague uses the example of trying to figure out how to access fruit on the ledge of a rock face. One can imagine various ways to attempt to grab the fruit. But none of the successful ones will involve flying DeLoreans or stretching limbs. Physical reality, and the invariance inherent to it is necessary for successful modelling. We already know we possess intuitive theories (that is, bodies of information) of physics involving object constancy, persistence throughout time and invariance to points of view. Montague makes a breathtaking observation: each of these concepts translates into the three laws of conservation of linear momentum, energy and angular momentum - the foundations of classical physics! That details about the physical world that corroborate with our scientific knowledge and is instantiated in the mind is both shocking and obvious. Another implication of invariance is by definition it holds true for what other organisms possess, so social learning is an effective way of gathering information about the world - model others as if they have similar goals and perceptions and you put yourself in their shoes - it could have happened to you. Empathy then, just makes sense.

Efficient computation requires guidance signals to provide information not only about how close we are to the goal (”getting warmer…”) but also about expectations about future rewards (”statistically, having this warmth means a forty percent likelihood of 30 units of…”). To help us choose efficient procedures, guidance signal is available for simulated models. And these guidance signals are not just a hypothetical construct, they match the behavior of the dopamine system. A mere 15-20,000 neurons (compared to a hundred billion in the entire brain) in the midbrain match the computational and physiological requirements of a system capable of acting on brain systems processing goals, notably the prefrontal cortex. We can interpret increases in activity corresponding to “reward is larger than expected”, pauses as “reward is less than expected” and no change as “reward is just as expected”.

Rewards do not come at once, they are distributed over time. Resources also do not come with labels such as “eat me”. As our trader, we are seeking information that predicts rewards. Dopamine helps us to this. When a light flashes, without any impact on our valuation of the world this is treated as irrelevant to our goals and dopamine produces a “things are as expected” signal. But if this light begins to consistently precede a reward, such as juice, when the light comes on dopamine releases a “better than expected” signal. In a sense, the future value of the reward is transferred to the light. Suddenly, we know something about the distribution of rewards in the world. Not only does this act of valuation help us predict rewards in the world, but it gives us a common currency for comparing them. As currency, these signals are not only stores of value but a means of exchange. Actions can be compared and simulated. Just as barter is inefficient if I do not want a whole goat or bale of cotton, neural currency smoothes out the potential comparisons to be made. Just as money can be used anywhere, proxies of value can be plugged into any model to compare potential returns.

But helping us choose actions by predicting rewards is only part of what dopamine does. What is rewarding is also constrained by what our goals are. According to the dopamine gating hypothesis, dopamine does indeed help us select goals. And it does this through the same mechanism it uses for stimuli in the world (remember, no humonculus): it learns that certain goals are predictive of rewards. Thus, a twenty dollar bill on the ground I see while walking to the bank is only predictive of twenty dollars extra in my pocket when my goal changes to “pick up twenty dollar bill”. Montague argues that the ability for humans to pursue abstract goals is by the hijacking of rewards by ideas: ideas become intrinsically valuable. Of course, the ability to do so can be extraordinarily positive, such as running a marathon for charity, or totally debilitating, as in drug addiction.

Montague makes exploring this “superpower” a focal element of his book, which is somewhat difficult to make compelling since as he acknowledges he cannot account for how certain ideas can hijack or why we are not continuously debilitated by alphabetizing our underwear or scrubbing our toenails. I would like a better account of how the content of something as a biological primitive such as goals of homeostasis can be equivalent to (and thus substitute for) an idea. This book is an odd mix of insightful stepwise building of a model with gaps in the details of the mechanisms involved. The gaps are not problematic because it is evident these are problems, not mysteries, and perhaps soon we will know much more about what other powerful and efficient computations we perform.

I was particularly intrigued by the connections to concepts in economics and finance. When Montague discussed the problem organisms face in allocating energy to either updating models or exercising them, I was reminded of the question of corporate dividend policy (reinvest extra profits or reward shareholders with it?). Regarding trade, only organisms with random and thus unpredictable behavior remain because predictable partners are exploited out of the market very much resembles the efficient markets hypothesis. I’d like some clarifications on the proxies of value the dopamine circuits produce. What is the connection between the valuation of the proxies (derivatives) and the underlying signals (underlying asset)? Many other cognitive science books have capitalized on developments in evolutionary biology, economics and computer science but few have as original insights as this book.

Before Darwin, a biologist seemed more like a curator than a scientist. Various features and phenomena of biological life were dutifully cataloged and classified, without any anticipation or desire of any connection between microbiology, physiology and zoology. The set of assumptions Darwin proposed in his theory of evolution not only unified these disparate fields but then generated a wealth of predictions that provided the engine behind biology’s explosive growth over the next century. Jeff Hawkins’ “On Intelligence” is an attempt to do the same for cognitive science. Whether he is right is, as the cliché goes, ‘an empirical question’, but if elegance is a sound criterion for a theory he gets high marks.

Hawkins begins with a critique of the various attempts of artificial intelligence researchers attempting to equip computers with human-like intelligence, which can roughly be summed up as “if more computational power isn’t working, you’re not using enough of it”. Such machines are like dancing bears: impressive, to be sure, but you can be sure no bear ever pulled aside his trainer to inquire about the waltz. Teach a girl ballet, and she might inquire about the music she has learned to dance to. Intelligent creatures exercise intelligence effortlessly. Intelligence is a process, not a result.

So what’s intelligence? To what extent can we abstract from the sometimes-messy contingencies of being carbon-based products of evolution to use the underlying principles anew? Hawkins proposes to do this we examine the neocortex, the evolutionarily recent brain matter that underlies many of the advanced reasoning capacities we possess. In examining the commonalities between the regions of cortex processing sensory and motor cognition, Vernon Mountcastle offered a simple and striking explanation: these regions seem similar because they are. Cortex implements the same computation everywhere.

For conscious beings who feel sight and sound are very different things and must require different information processing, this is deeply counterintuitive. But to a brain, it’s all just patterns, baby. Spatial and temporal patterns. Take sound, which feels as it merely has a temporal dimension. The sounds we hear come from vibrations to a membrane in our inner ear innervated by neurons throughout, which then provides both spatial and temporal information. Even in sight, we saccade, or look rapidly, in order to capture the three-dimensional data the 2-D retina itself cannot intrinsically convey. In other words, to get information about the real world as it is we have to do a little massaging of our data. Notice, the active brain. This is an important feature we will return to.

Let’s follow where this insight leads us. If all sensory data is equivalent, there’s no reason why we shouldn’t expect data to be shared among these modalities. This is an elegant solution to the tricky problem of how we integrate information from different modalities to form coherent representations of the world. If I hear a characteristic gait in my lab, I can tell if a postdoc is ambling by or if a professor is striding in looking for an update. But I did not “sense” a professor per se, this representation is abstracted from the data. In this sense, our entire knowledge of the world consists of abstractions from patterns that serve as predictions.

But the real world is messy. Lighting is not stable, there is noise everywhere. How can we ever construct memories that possess the important features of the things we wish to represent? How can I recognize my friend’s face in a crowd, and how do I notice when he has just grown a mustache? The answer seems to lie in our ability to produce invariant representations that store the pattern but are agnostic about how the pattern is discerned or expressed in turn. This what enables you to recognize muzak versions of your favorite songs (to your mortification) and sufficiently pen your signature with your off-hand when your good hand is clutching a small child. This is even what enables us to connect the wildly different visual input of a lover’s face up close and across the room.

These invariant representations play an important role in mitigating the noisy world. By meeting ambiguous data halfway, we are able to make sense of the world. The default stance of our brain is a steady stream of predictions, right down to the most mundane expectations of gravity and material properties of matter in order to make sense of the input. If you accidentally skip a step when walking down the stairs, you know very quickly something is wrong.

When predictions conform to feedback, this is what understanding the structure of the world comes down to. In other words, intelligence, the ability to discern features of the world and act on them, is primarily prediction. Incorrect predictions mean models need to be updated. So our worldview is constantly subjected to testing on the data we receive, as we would expect from a device attempting better and better represent the world. And of course, this means our experience is a really just a model of reality. Not a new insight by any means, but this is a great way to really comprehend how it is so.

I have a contention with Hawkins’ emphasis on prediction. Predictions are not the only metric to gauge performance. Again, intelligence is a process, not an outcome. Privileging prediction over process is like investing in a money manager with three hot years in a row without considering what part of his success was due to luck.
Evaluating explanations avoids such problems. Humans (and scientists) are not content with simply producing a description of the world, which can vary in content but produces identical predictions. To an extent, we are all interested in the causal essence of the world.

So where does the capacity for prediction come from? Recall the notion that the cortex is performing the same computation everywhere. Now, note that the actual neocortex has six layers. This hierarchical organization still retains the fractal nature of the common cortical algorithm: at every level the brain produces invariant representations on the underlying inputs. This is how more and more abstraction is produced at the “higher” level. It’s important not to take a simple view of the organization of the cortex, referring to “higher” processes as if these are the fount of wisdom. As we shall see, it is essentially the interaction between the sensory input and more abstract invariant representations that settles what our model, and thus our living experience is.

A consequence of invariance is not only the unity of the sensory areas, but the unity in sensation and behavior. These same invariant representations activating downwards can direct motor output. It’s not necessary to have two representations of “The Gettysburg Address”, one to speak it and one to read it. In a complimentary bit of efficiency, basic units of representation can be used combinatorially by higher-order invariant representations. This is pretty amazing stuff.

Hawkins elaborates on the basic neurobiology that would be able to implement and revise invariant representations which now needs to be put to empirical scrutiny. I find the memory-prediction explanation of intelligence to be simple and effective, and it’s a credit to Hawkin’s business sense to take a difficult problem and make it a digestible one to take action. But I wonder if he’s abstracted a few too many details of what humans actually do.

If there’s going to be more than one intelligent machine, then they better know how to represent other intelligent machines. Cognitive scientists have attempted to decompose goal-oriented behavior ever since Fritz Heider’s famous experiments showing that people can impute goal-directed behavior to simple animated geometric shapes. Likewise, others such as George Kelly have made prediction a central feature in theories of social cognition. What features would an invariant representation of a goal-directed object have?

From Jeff Hawkins’ own company, Palm, comes an interesting illustration. Palm was a wholly owned subsidiary of 3Com, which sold 5% of Palm in an initial public offering and announced the intention to spin off the remainder of the firm within nine months, at which time each 3Com shareholder would receive 1.5 shares of Palm. Thus, at the IPO, one would expect shares of 3Com to stand at 150% the price of Palm. In fact, at the close of trading on the first day, Palm shares were $95 and 3Com’s were $81, as if 3Com’s business outside of Palm were worth -$60 per share.

This incident is the real-world output of intelligent machines – lots of them. There is a need to address the intersection between a memory-prediction model and the probabilistic reasoning and behavioral economics literature. In these two literatures, two features of thinking are explored: the extent to which we rationally update our beliefs based on data and the extent to which our beliefs normatively acceptable, respectively. I don’t actually have much more to say on possible connections to these literatures, but again the question of what intelligence is normatively about and whether features of actual humans are important to include is a very significant and difficult question that must be addressed.

The sheer optimism and energy this book brings to cognitive science is exciting. Perhaps our entrepreneurial Jeff Hawkins will direct us to start down the stairs and update our model as we go.

One of the more remarkable entries in “The Hitchhiker’s Guide to the Galaxy” succinctly explains the nature of progress:

“The History of every major Galactic Civilization tends to pass through three distinct and recognizable phases, those of Survival, Inquiry and Sophistication, otherwise known as the How, Why and Where phases. For instance, the first phrase is characterized by the question How can we eat? The second by the question Why do we eat? and the third by the question Where shall we have lunch?”

And if this is the History of every civilization, Michael Pollan argues their Future lies in the Ethical phase: What should we eat? What woke Pollan from his dogmatic slumbers was the recent excitement over the Atkins diet. That a diet based on increased consumption of red met and wholesale abandonment of bread and pasta could sweep the nation makes you wonder about the stability of our national culinary culture. Pollan asks “what would make a good meal?” to see if this can clarify what we should care about food.

The Omnivore’s Dilemma was coined by Paul Rozin to articulate the challenges omnivores face. Given that organisms cannot completely anticipate their future environments, natural selection favors the flexible. Omnivores that wish to survive changing ecologies must have a certain neophilia, or inclination to try new foods to see what’s out there. On the other hand, the plants and animals pursued don’t always want to be eaten, and the toxins and counter-adaptations they develop is the source of neophobia. In this era of plenty (for industrialized nations), one might think the dilemma is resolved - if it’s wrapped in plastic with a nutritional label, you can feed it to your children. Pollan argues rather that it renders the problem acute, because what exactly is xanthan gum and where did it come from?

With a couple premises we can understand the logic of this book. One is a matter of ecology, that is, what is natural. Perhaps the defining feature a creature plays in an ecological system is what it eats. To understand an organism, for instance humans, one can use this convenient heuristic. The other is that the industrial era is a logical extension to the agricultural shift we as a species took, and that the logic of industry is is based on profit and production which compromises goals such as sustainability and pleasure. The first claim is mildly interesting and the second is mildly controversial, but these themes are explored wonderfully in his tour of what he deems the industrial, the pastoral, and the forager ways of obtaining a meal.

On the industrial food chain, Pollan is amusing and appropriately stark.. Not having convenient access to the information about where your food comes from is one thing, but to require a journalist, an ecological detective, to tell you where it’s been is something to contemplate. And it all come down to corn. There are 45,000 items in the average grocery store, and roughly a quarter of them have some corn product in them. Corn is what is fed to produce the meat (including farm-raised salmon), the dairy and a bewildering host of processed component from the sugar substitute corn syrup to the obscure but ubiquitous lechithin and yes, xanthan gum. Noting that Mexicans proudly recognize their culinary origins with the moniker “walking corn”, Pollan sums up the problem of industrial food: “For an American like me, growing up linked to a very different food chain, yet one that is also rooted in corn, not to think of himself as a corn person suggests either a failure of imagination or a triumph of capitalism”.

Pollan must be commended for beautifully explaining the implications of the biological features of corn. For someone trained in biological sciences, I was still struck by simple majesty of photosynthesis (how the sheer tonnage of biological mass is culled from the air) and how the fantastic nature of corn sex illustrates that our dependent relationship challenges the logic that we are using corn and not the other way around. Pollan’s demonstration of the origins of our artificial fertilizers from excess World War II explosives (”Fixing nitrogen allowed the food chain to turn from the logic of biology and embrace the logic of industry. Instead of eating exclusively from the sun, humanity now began to sip petroleum”) and the pathos of a farmer forced to drive a rig to purchase the latest agribusiness tools to keep his farm afloat couldn’t offer better metaphors for the relentless and bizarre logic of industrialism.

This slippery slope this farmer has found himself on, joining the race to produce more corn which in turn depressed prices, indirectly subsidizes a number of other industries, notably meat and processed foods. Pollan’s stomach-churning account of the industrial meat industry may not be the first but certainly one of the most satisfying explanations of how the industry functions and the loopholes and quirks that abound. Pollan presents an original explanation for the processed foods industry: why sell the raw stuff when you can manipulate the underlying foodstuffs and charge more? The challenge food sellers face is “how to get people to spend more money for the same three-quarters of a ton of food, or entice them to actually eat more than that. The two strategies are not mutually exclusive, of course, and the food industry energetically pursues them at the same time”. Given that it is apparent that the industrial food industry is not designed in the consumers or farmer’s interests, the inescapable conclusion is it is designed either for the benefit of the food industry - or corn.

The real meat of the book lies in the section on the pastoralist model of farming, examining one PolyFace Farm, an alternative farm in Virginia run by Joel Salatin and his family. From a mere hundred acres Salatin manages to produce 40,000 pounds of beef, 30,000 pounds of pork, 10,000 broilers, 1,200 turkeys, 1,000 rabbits and 35,000 eggs. Astonishing? Whereas in industrial logic, feeding inputs and managing outputs presents two problems, in pastoral logic inputs cycle into outputs using the same features natural ecologies use. This is how you can capture much more sun from the same land. The feat is done by what is called “management-intensive grazing”, which is an amusing description for an self-declared “libertarian-environmentalist” farmer. Perhaps it would be more appropriate to call it “computationally-intensive grazing”. It is much more labor-intensive than capital intensive. Farmers become knowledge workers. Salatin’s description of himself as an orchestra conductor comes closer to capturing the elegance of the system he has developed.

I had anticipated his hunter-gatherer experience to be the highlight of the book, and I was also excited to read his section on the ethics of eating meat, but these sections were less impressive. It is Pollan’s curiosity that clearly made the industrial and pastoral sections so spirited and well-researched, but when he explicitly became the center of attention the story becomes less compelling. Pollan’s work is best when he leads his viewers carefully along the experiences that are our food: the desecration of corn trampled underfoot at a depot, the scratches bales of hay leave, the extra-awareness of the hunt. This book is for those who seek to experience their food and think carefully about what is says about you.

[Disclaimer: I work with Jason Jankovsky on trader education]

The markets come with their own basic set of rules. In the case of futures and foreign exchange, the most important rule is that these are zero sum markets. That is, for every winner there is a loser. The other basic rule is that order flow dictates price action. If there are more orders to buy than to sell, as the orders match up with sellers the lowest selling prices get exhausted and prices climb. These two basic rules are enacted by market participants. Each of these participants has the goal to be profitable. What information about the market they are using and when they plan on trading may be in conflict with one another. Despite all the complications that ensue when participants interact, the most basic rule holds that order flow is the ultimate source of price. If one’s trading plan does not accommodate this basic fact, you will not be profitable.

What’s not obvious is that given these basic rules, the markets actually allow you to participate very flexibly. Most traders, however, are not profitable. It seems that traders either do not know the rules of the market or do not act upon them consistently. Jason Jankovsky in his book “Trading Rules That Work” clarifies what the rules of the markets are and explains that since traders are loss averse they might not act on them consistently. The underlying goal of trading the markets lies in understanding market psychology. The dynamics of order flow are nothing more than trader’s expression of and reaction to this sentiment. A losing trader suffers the double indignity of eventually needing to admit they were wrong by contributing to the order flow pushing against them in order to close.

At the heart of this understanding is a plan. A trading plan is not the same as trading strategy. Trading strategy dictates favorable entry points to the market. Once you’re in, you’re subject to the probability that your plan is effective. What you do when you move to profitability or loss is determined by your plan. A good way to think about this is that a financial goal is to earn money. If you win the lottery, would you have a plan for retaining that money? Without a plan, you will suffer the fate of many such winners who have no discipline and lose all their money. The most basic part of this plan is determining what your goals are for trading and what your temperamental style is. In sections covering topics such as determining the time frame of your trades, Jankovsky does an excellent job of showing just why there can be many solutions to establish a trading plan and how you determine whether you are matching your trading needs. In this section he also shows how different traders with different objectives may play off each other, as when a long term bullish trader can use the short term bearish trader to accept the order flow in his direction.

By maintaining discipline and a trading plan that suits your style, you will be able to exercise with confidence all the components of your plan. Rules like cutting your losses are well known to traders, but the cost of being strict in your losses can be made up by being generous with your gains by adding to your winners. If you have correctly identified that order flow is on your side, then adding to your winner will strengthen this force. Thus by definition if you are right, adding to your winner is a good idea. Jankovsky also does a good job of illustrating how to select values for somewhat arbitrary factors like timeframe or establishing a ratio for reward to risk for each trade to show how a trading plan can be coherent but based on individual experience and needs. One chapter that particularly merits reading is “All Markets are Bearish”, in which Jankovsky illustrates the logical basis for markets lies in providing hedgers with the opportunity to limit risk and get the best price possible for their asset and this necessarily entails that hedgers will ultimately exert selling pressure on the market.

The market is a machine. If you drive a car and do not understand how to use the car you can be faced with costly loss. There’s no need for your car to break down when gas stations are plentiful. If you needed to fill your tank before an important appointment, that is not the fault of the car but your time management. If you do not have enough money for gas, that is also external to the car. If you drive with the low-gas indicator on, you are constantly in fear of the car breaking down under you. By maintaining discipline and a trading plan, you ensure that you are using the car and that the car is not using you.

The business of America has always had moral imperative. As noted in my former history teacher Scott Sandage’s “Born Losers”, the word failure as conflated by personal and economic conditions is uniquely American. Popular notions of what business is for changes with the times. Fifty years ago, in the age of mass media and industrial boom, business principles in public consciousness can be summarized by Peter Drucker’s “management by objectives”: stern dictums issued from above. What then, are today’s tipping point and the long tail about?

The latest development of the self-referential economy: business as entertainment. Now we demand our CEOs shed their anonymous pinstripes to don black turtlenecks. Sleek geeks. In an era where a theater-quality movie can reasonably be produced for less than the cost of a house, we are broaching an era where the entrepreneur and the creative class are the dominant cultural force. The motivations are to make customer’s lives easier, rather than creating artificial demands as mass media tried. Netflix merely takes our desire for a hundred year old medium and makes it easier to select and get. Amazon works with an even older business.

Leading the way in the new era are mavens like Guy Kawasaki, who spells out his evangelism in “The Art of the Start”. Forget the business plan, what’s your mantra? Kawasaki brings us his insight from his twenty years as an entrepreneur to distill the essence of the art. We discover the entrepreneur is not some mythical hero, but rather an ordinary citizen equipped with one basic notion: get started on something that means something. One has the urge to almost throw down the book in shame of wasting time reading and run to our desks to get started. His energy is infectious, his examples crisp and memorable, and he does not belabor himself. Be clear, be brief, be seated.

Communication is at the heart of his mission. This means maintaining a clear idea of what the pursuit is for. If it can’t be expressed in a handful of words, can it. If the competitors won’t say the opposite (we’re slow and customer-unfriendly) then you’re not standing for anything meaningful. Once you’ve developed your own mantra, spread the good word. The decision makers are not always the customer per se, sometimes it’s implicitly their parents or spouse. If they can’t explain what it is, it’s dead in the water. But ultimately, the customer is who you are appealing to, not your ego. The customer doesn’t care that you want to “kill the competition” or “be the leader in ____”, what can you do for them? Write a business plan to shore up the ideas you were already working on. Build a sales forecast from the bottom up (there’s a global market of $5 billion, but right now I can reach $1 million). Use your competitors against themselves: copy their business model, partner up, brand against them.

Kawasaki succeeds in getting us to realize entrepreneurship is about going from the status quo to the hoi polloi’s needs. But this book is far too enjoyable to be business literature. Truman was close, the entertainment of America is business.