Part fictional, part autobiographical book based on Millman’s life as he finds his way through romance, magic, light, dark, mind, body, spirit, etc. while working with his “coach” Socrates
The best warriors have the quietest minds in times of truth (performance)
Regardless if you get what you want or not you suffer as everything changes. The mind wants to be free of sin, free of change but change is law.
Life is not suffering. We make it suffer until we learn to let go and love whatever happens (Amor fati)
Brain and mind are not the same. Brain is real. The mind isn’t. The mind is an illusory outgrowth, an obstacle to be overcome
Learn from your life experiences instead of complaining or basking in them
Your moods are a direct outcome of your thoughts – not the events themselves
When the mind resists life, thoughts arrive. Thoughts are an unconscious reaction to life
Silence is the warrior’s art
Aim to be perfectly content and happy regardless of what is going on around you
Anger is more powerful than fear or sorrow. It can generate action where fear and sorrow turn you away from action
True emotion is pure energy which should be directed outward and not withheld. The way to control your emotions is to let them flow and then let them go
Must enjoy the entire process of eating – preparation, chewing, breathing, and the feeling of lightness after the meal
What comes out of your mouth is as important as what goes into it – speak less and when you do speak, speak deliberately and purposefully
Never give in to unconscious impulses
When you sit, sit. When you stand, stand. No matter what you do, don’t wobble. Do it with all your might and focus. Better to make mistakes with the full force of your being than doing something mediocre while being unsure
Urges do not matter, actions do
Death is simply a transformation. The warrior neither seeks it nor runs away from it
There are no ordinary moments – every moment is worthy of your full attention
Satori – thoughtless awareness (what to aim for and often can access it through sports, meditation, etc.)
The mind becomes bored with things because we only know them as a name. Babies simply experience life before they become “namers” and “knowers”
Boredom is a result of fundamental unawareness
Happiness = satisfaction over desires. If you have enough to cover your desires you are rich. Can either have a lot of money and desires or cultivate a simple lifestyle. Happiness comes from the capacity of enjoying less instead of seeking more
The only time is now and the only place is where you currently are
Do not let anybody or anything, especially your thoughts, draw you out of the present
It doesn’t matter what you do but you must do it well
Your goal is not invulnerability but complete and transparent vulnerability
A warrior is not something you become. It is something you either are or are not in the present moment. The way itself creates the warrior
Act happy. Be happy without a reason in the world. Then you can truly love and live
All searches, all goals are equally enjoyable and equally unnecessary
No need to resist life. Just do your best and enjoy the present. You and the world and everyone in it is one
What I got out of it
Awesome read that I’d definitely read again. Learned about happiness, goals, what you really want to get out of life, priorities, etc.
Some major takeaways from the field of engineering
Civil engineering is the grandparent of all engineering
Engineering suceeds and fails because of the black box – it conceptually contains the knowledge and processes of an engineering specialty
You are a vector – a force is expressed graphically by a vector. Any single vector can be replaced by more than one component vectors, and vice versa, as long as they yield an equivalent net result
When overwhlemed by a complex problem, identify those aspects of it that can be grasped with familiar principles and tools
An object receives a force, experiences a stress (force / area), and exhibits strain (measurable deformation)
4 material characteristics – stiffness/elasticity (resistance to change in length/ability to return to original size and shape), strength (ability to accept a load), ductility/brittleness (extent a material deforms or elongates before fracturing), toughness (overall measure of ability to absorb energy before fracture)
A battery works because of corrosion – electrons moving to the cathode from the anode
Soldiers shouldn’t march across a bridge – when a force acts repeatedly on a structural member, and at a rate that matches its natural frequency, the member’s response is enhanced with every cycle
Roundabouts are teh safest, most efficient intersection
Maximum friction is found right at the start of motion and declines immediately when motion starts
Accuracy is the absence of error, precision is the level of detail – effective problem solving requires always being accurate, but being only as precise as is helpful at a given stage of problem solving. Early in the problem solving process, accurate but imprecise methods, rather than very exact methods, will facilitate design explorations while minimizing the tracking of needlessly detailed data
Good design is not maximization of every response, or even compromise among them; it’s optimization among alternatives
Quantification is exact not unto reality, but unto itself, it is approximation of reality
You don’t fully understand something until you quantify it. But you understand nothing at all if all you do is quantify
Safety margins are constantly used by engineers, overestimating loads, rounding calculations, selecting for structures larger or thicker than calculations call for
The complexity of a truss is a product of simplicity – allowing long distance bridges to be built using a fraction of the material used by an ordinary beam
Structures are built from the bottom up, but designed from the top down
Earthquake design: let it move a lot or not at all
Figuring out how to make a system work is as important as figuring out how to make it not work in undesirable ways
A masonry arch (keystone) gets stronger as it does more work
Early decisions have the greatest impact on design, feasibility, and cost
Perfect reliability isn’t always desirable – some aircraft parts are meant to be replaced frequently in order to save time, weight,
Few customers will play for a perfectly engineered part – trade off between cost and value
Design a part to fail – electrical systems are protected by fuses or circuit breakers that trip before a power surge can ruin expensive components or damage ahrd to access wires
Turbulent flow is when particle paths are irregular and laminar flow occurs when particles move in straight lines (low flow velocities and small pathways)
Think systematically – apply your thinking consistently and thoroughly to all other aspects of the problem at all possible scales, from concept to detail and back again
Think systemically – thinking about systems and connections – the web of relationships within a system, the relationship of the system to other systems, and the larger system that contains all the systems
A successful system won’t necessarily work at a different scale
Seek negative feedback – a system responds in the opposite direction of the stimulus, bringing overall stability or equilibrium (positive feedback decreases equilibrium further and further)
Center of gravity – the center of gravity of an object is the average position of the particles that comprise it – the point on which it will balance
Articulate the why, not just the what – by articulating your intent, you help others understand and preserve the most critical goals while giving them room to investigate possibilities that did not occur to you
All engineers calculate. Good engineers communicate
There are 3 kinds of people – language people, people people, object people
When struggling to analyze a complex problem, shift your point of view from that of outside observer to that of the thing you are analyzing. If you were that thing, what forces would you feel? What internal stresses would you experience? How would you have to react to remain stable and not twist, turn, deform, be pushed over, or be caused to accelerate?
Satisfaction = reward / input. When people feel fairly rewarded – when their ratio is at least as high as a peer’s ratio – they are more likely to be motivated, under-rewarded leads to feeligns of distinterest and resentment, and over-rewarded may lead to feelings of guilt
There’s design behind the design – a well-designed product isn’t well-designed if the process needed to manufacture it is unrealistic or uneconomical
Engineering solutions must demonstrate objectively measurable improvement against a benchmark – bias is the difference between a predicted and actual value, variance the average distance between a set of data points and their mean value
The most important thing is to keep the most important thing the most important thing – Donald Coduto. You must solve what you set out to do but don’t become so focused on that one thing that you don’t do as much as you can
Sometimes the fix for an apparent engineering problem might not be an engineering fix – i.e., 66% of airplane accidents is caused by flight crew errors
Engineering usually isn’t inventing the wheel; it’s improving the wheel
The great continuum – engineering is undertaken within a continuum that connects profound human questions to ordinary activities. Engineers who work without awareness of the continuum will be inclined toward performing rote procedures. Those working in awareness of it will be better positioned to adapt to changing times, unexpected challenges, and unfamiliar circumstances. Those working across the continuum may be most apt to contribute something new.
What I got out of it
Even if you’re not an engineer, or should I say, especially if you’re not an engineer, these principles and ways to think will be valuable to understand and apply. They hold true in business and in relationships
“My goals in writing this book are twofold. In the first section, I identify many of the pitfalls that face investors. By highlighting where so many go wrong, I hope to help investors learn to avoid these losing strategies. For the remainder of the book, I recommend one particular path for investors to follow—a value-investment philosophy. Value investing, the strategy of investing in securities trading at an appreciable discount from underlying value, has a long history of delivering excellent investment results with very limited downside risk.”
Ideally this will be considered, not a book about investing, but a book about thinking about investing. Like most eighth-grade algebra students, some investors memorize a few formulas or rules and superficially appear competent but do not really understand what they are doing. To achieve long-term success over many financial market and economic cycles, observing a few rules is not enough. Too many things change too quickly in the investment world for that approach to succeed. It is necessary instead to understand the rationale behind the rules in order to appreciate why they work when they do and don’t when they don’t. I could simply assert that value investing works, but I hope to show you why it works and why most other approaches do not.
The temptation of making a fast buck is great, and many investors find it difficult to fight the crowd.
Regardless of the market environment, many investors seek a formula for success. The unfortunate reality is that investment success cannot be captured in a mathematical equation or a computer program.
Ultimately investors must choose sides. One side—the wrong choice—is a seemingly effortless path that offers the comfort of consensus. This course involves succumbing to the forces that guide most market participants, emotional responses dictated by greed and fear and a short-term orientation emanating from the relative-performance derby. Investors following this road increasingly think of stocks like sowbellies, as commodities to be bought and sold. This ultimately requires investors to spend their time guessing what other market participants may do and then trying to do it first. The problem is that the exciting possibility of high near-term returns from playing the stocks-as-pieces-of-paper-that-you-trade game blinds investors to its foolishness. The correct choice for investors is obvious but requires a level of commitment most are unwilling to make. This choice is known as fundamental analysis, whereby stocks are regarded as fractional ownership of the underlying businesses that they represent. One form of fundamental analysis—and the strategy that I recommend—is an investment approach known as value investing. There is nothing esoteric about value investing. It is simply the process of determining the value underlying a security and then buying it at a considerable discount from that value. It is really that simple. The greatest challenge is maintaining the requisite patience and discipline to buy only when prices are attractive and to sell when they are not, avoiding the short-term performance frenzy that engulfs most market participants. The focus of most investors differs from that of value investors. Most investors are primarily oriented toward return, how much they can make, and pay little attention to risk, how much they can lose.
The value discipline seems simple enough but is apparently a difficult one for most investors to grasp or adhere to. As Buffett has often observed, value investing is not a concept that can be learned and applied gradually over time. It is either absorbed and adopted at once, or it is never truly learned.
Where Most Investors Stumble
Mark Twain said that there are two times in a man’s life when he should not speculate: when he can’t afford it and when he can. Because this is so, understanding the difference between investment and speculation is the first step in achieving investment success.
Investors believe that over the long run security prices tend to reflect fundamental developments involving the underlying businesses
Investors in a stock thus expect to profit in at least one of three possible ways: from free cash flow generated by the underlying business, which eventually will be reflected in a higher share price or distributed as dividends; from an increase in the multiple that investors are willing to pay for the underlying business as reflected in a higher share price; or by a narrowing of the gap between share price and underlying business value.
In reality, no one knows what the market will do; trying to predict it is a waste of time, and investing based upon that prediction is a speculative undertaking.
The distinction is not clear to most people. Both investments and speculations can be bought and sold. Both typically fluctuate in price and can thus appear to generate investment returns. But there is one critical difference: investments throw off cash flow for the benefit of the owners; speculations do not. They return to the owners of speculations depends exclusively on the vagaries of the resale market.
If you look to Mr. Market as a creator of investment opportunities (where price departs from underlying value), you have the makings of a value investor. If you insist on looking to Mr. Market for investment guidance, however, you are probably best advised to hire someone else to manage your money.
Many unsuccessful investors regard the stock market as a way to make money without working rather than as a way to invest capital in order to earn a decent return. Anyone would enjoy a quick and easy profit, and the prospect of an effortless gain incites greed in investors. Greed leads many investors to seek shortcuts to investment success. Rather than allowing returns to compound over time, they attempt to turn quick profits by acting on hot tips. They do not stop to consider how the tipster could possibly be in possession of valuable information that is not illegally obtained or why, if it is so valuable, it is being made available to them. Greed also manifests itself as undue optimism or, more subtly, as complacency in the face of bad news. Finally greed can cause investors to shift their focus away from the achievement of long-term investment goals in favor of short-term speculation
It is human nature to seek simple solutions to problems, however complex. Given the complexities of the investment process, it is perhaps natural for people to feel that only a formula could lead to investment success. Just as many generals persist in fighting the last war, most investment formulas project the recent past into the future. Some investment formulas involve technical analysis, in which past stock-price movements are considered predictive of future prices. Other formulas incorporate investment fundamentals such as price-to-earnings (P/E) ratios, price-to-book-value ratio, sales or profits growth rates, dividend yields, and the prevailing level of interest rates. Despite the enormous effort that has been put into devising such formulas, none has been proven to work.
Nature of Wall Street Works Against Investors
Wall Streeters get paid primarily for what they do, not how effectively they do it. Wall Street’s traditional compensation is in the form of up-front fees and commissions. Brokerage com-missions are collected on each trade, regardless of the outcome for the investor. Investment banking and underwriting fees are also collected up front, long before the ultimate success or fail-ure of the transaction is known. All investors are aware of the conflict of interest facing stockbrokers. While their customers might be best off owning (minimal commission) U.S. Treasury bills or (commission-free) no-load mutual funds, brokers are financially motivated to sell high-commission securities. Brokers also have an incentive to do excessive short-term trading (known as churning) on behalf of discretionary customer accounts (in which the broker has discretion to transact) and to encourage such activity in nondiscretionary accounts. Many investors are also accustomed to conflicts of interest in Wall Street’s trading activities, where the firm and customer are on opposite sides of what is often a zero-sum game.
The point I am making is that investors should be aware of the motivations of the people they transact business with; up-front fees clearly create a bias toward frequent, and not necessarily profitable, transactions.
The Institutional Performance Derby: The Client is the Loser
Economist Paul Rosenstein-Rodan has pointed to the “tremble factor” in understanding human motivation. “In the building practices of ancient Rome, when scaffolding was removed from a completed Roman arch, the Roman engineer stood beneath. If the arch came crashing down, he was the first to know. Thus his concern for the quality of the arch was intensely personal, and it is not surprising that so many Roman arches have survived.”
Remaining fully invested at all times certainly simplifies the investment task. The investor simply chooses the best available investments. Relative attractiveness becomes the only investment yardstick; no absolute standard is to be met. Unfortunately the important criterion of investment merit is obscured or lost when substandard investments are acquired solely to remain fully invested. Such investments will at best generate mediocre returns; at worst they entail both a high opportunity cost—foregoing the next good opportunity to invest—and the risk of appreciable loss.
Remaining fully invested at all times is consistent with a relative-performance orientation. If one’s goal is to beat the market (particularly on a short-term basis) without falling significantly behind, it makes sense to remain 100 percent invested. Funds that would otherwise be idle must be invested in the market in order not to underperforms the market. Absolute-performance-oriented investors, by contrast, will buy only when investments meet absolute standards of value. They will choose to be fully invested only when available opportunities are both sufficient in number and compelling in attractiveness, preferring to remain less than fully invested when both conditions are not met. In investing, there are times when the best thing to do is nothing at all. Yet institutional money managers are unlikely to adopt this alternative unless most of their competitors are similarly inclined.
Investing without understanding the behavior of institutional investors is like driving in a foreign land without a map. You may eventually get where you are going, but the trip will certainly take longer, and you risk getting lost along the way.
Avoiding losses is the most important prerequisite to investment success
Defining Your Investment Goals
Warren Buffett likes to say that the first rule of investing is “Don’t lose money,” and the second rule is, “Never forget the first rule.” I too believe that avoiding loss should be the primary goal of every investor. This does not mean that investors should never incur the risk of any loss at all. Rather “don’t lose money” means that over several years an investment portfolio should not be exposed to appreciable loss of principal.
Greedy, short-term-oriented investors may lose sight of a sound mathematical reason for avoiding loss: the effects of compounding even moderate returns over many years are com-pelling, if not downright mind boggling. Table 1 shows the delightful effects of compounding even relatively small amounts.
Investors must be willing to forego some near-term return, if necessary, as an insurance premium against unexpected and unpredictable adversity.
Rather than targeting a desired rate of return, even an eminently reasonable one, investors should target risk
Value Investing: The Importance of a Margin of Safety
Value investing is the discipline of buying securities at a significant discount from their current underlying values and holding them until more of their value is realized. The element of a bar-gain is the key to the process. In the language of value investors, this is referred to as buying a dollar for fifty cents. Value investing combines the conservative analysis of underlying value with the requisite discipline and patience to buy only when a sufficient discount from that value is available. The number of available bargains varies, and the gap between the price and value of any given security can be very narrow or extremely wide. Sometimes a value investor will review in depth a great many potential investments without finding a single one that is sufficiently attractive. Such persistence is necessary, however, since value is often well hidden. The disciplined pursuit of bargains makes value investing very much a risk-averse approach. The greatest challenge for value investors is maintaining the required discipline. Being a value investor usually means standing apart from the crowd, challenging conventional wisdom, and opposing the prevailing investment winds. It can be a very lonely undertaking. A value investor may experience poor, even horrendous, performance compared with that of other investors or the market as a whole during prolonged periods of market overvaluation. Yet over the long run the value approach works so successfully that few, if any, advocates of the philosophy ever abandon it.
Value investors continually compare potential new investments with their current holdings in order to ensure that they own only the most undervalued opportunities available. Investors should never be afraid to reexamine current holdings as new opportunities appear, even if that means realizing losses on the sale of current holdings. In other words, no investment should be considered sacred when a better one comes along.
Because investing is as much an art as a science, investors need a margin of safety. A margin of safety is achieved when securities are purchased at prices sufficiently below underlying value to allow for human error, bad luck, or extreme volatility in a complex, unpredictable, and rapidly changing world. According to Graham, “The margin of safety is always dependent on the price paid. For any security, it will be large at one price, small at some higher price, nonexistent at some still higher price.” Buffett described the margin of safety concept in terms of tolerances: “When you build a bridge, you insist it can carry 30,000 pounds, but you only drive 10,000-pound trucks across it. And that same principle works in investing.”
How can investors be certain of achieving a margin of safety? By always buying at a significant discount to underlying business value and giving preference to tangible assets over intangibles. (This does not mean that there are not excellent investment opportunities in businesses with valuable intangible assets.) By replacing current holdings as better bargains come along. By selling when the market price of any investment comes to reflect its underlying value and by holding cash, if necessary, until other attractive investments become available. Investors should pay attention not only to whether but also to why current holdings are undervalued. It is critical to know why you have made an investment and to sell when the reason for owning it no longer applies. Look for investments with catalysts that may assist directly in the realization of underlying value. Give preference to companies having good managements with a personal financial stake in the business.
A market downturn is the true test of an investment philosophy. Securities that have performed well in a strong market are usually those for which investors have had the highest expectations.
Investors should understand not only what value investing is but also why it is a successful investment philosophy. At the very core of its success is the recurrent mispricing of securities in the marketplace. Value investing is, in effect, predicated on the proposition that the efficient-market hypothesis is frequently wrong. If, on the one hand, securities can become undervalued or overvalued, which I believe to be incontrovert-ibly true, value investors will thrive. If, on the other hand, all securities at some future date become fairly and efficiently priced, value investors will have nothing to do. It is important, then, to consider whether or not the financial markets are efficient.
The efficient-market hypothesis takes three forms. The weak form maintains that past stock prices provide no useful information on the future direction of stock prices. In other words, technical analysis (analysis of past price fluctuations) cannot help investors. The semistrong form says that no published information will help investors to select undervalued securities since the market has already discounted all publicly available information into securities prices. The strong form maintains that there is no information, public or private, that would benefit investors. The implication of both the semi-strong and strong forms is that fundamental analysis is useless. Investors might just as well select stocks at random.
An entire book could be written on this subject alone, but one enlightening article cleverly rebuts the efficient-market theory with living, breathing refutations. Buffett’s “The Superinvestors of Graham-and-Doddsville” demonstrates how nine value-investment disciples of Benjamin Graham, holding varied and independent portfolios, achieved phenomenal investment success over long periods.
In a sense, value investing is a large-scale arbitrage between security prices and underlying business value. Arbitrage is a means of exploiting price differentials between markets.
At the Root of a Value-Investment Philosophy
There are three central elements to a value-investment philosophy. First, value investing is a bottom-up strategy entailing the identification of specific undervalued investment opportunities. Second, value investing is absolute-performance-, not relative-performance oriented. Finally, value investing is a risk-averse approach; attention is paid as much to what can go wrong (risk) as to what can go right (return).
In investing it is never wrong to change your mind. It is only wrong to change your mind and do nothing about it.
The risk of an investment is described by both the probability and the potential amount of loss. The risk of an investment— the probability of an adverse outcome—is partly inherent in its very nature. A dollar spent on biotechnology research is a riskier investment than a dollar used to purchase utility equipment. The former has both a greater probability of loss and a greater percentage of the investment at stake.
Unlike return, however, risk is no more quantifiable at the end of an investment than it was at its beginning. Risk simply cannot be described by a single number. Intuitively we under-stand that risk varies from investment to investment: a government bond is not as risky as the stock of a high-technology company. But investments do not provide information about their risks the way food packages provide nutritional data. Rather, risk is a perception in each investor’s mind that results from analysis of the probability and amount of potential loss from an investment. If an exploratory oil well proves to be a dry hole, it is called risky. If a bond defaults or a stock plunges in price, they are called risky. But if the well is a gusher, the bond matures on schedule, and the stock rallies strongly, can we say they weren’t risky when the investment was made? Not at all. The point is, in most cases no more is known about the risk of an investment after it is concluded than was known when it was made. There are only a few things investors can do to counteract risk: diversify adequately, hedge when appropriate, and invest with a margin of safety. It is precisely because we do not and cannot know all the risks of an investment that we strive to invest at a discount. The bargain element helps to provide a cushion for when things go wrong.
The trick of successful investors is to sell when they want to, not when they have to. Investors who may need to sell should not own marketable securities other than U.S. Treasury bills.
The Art of Business Valuation
In Security Analysis he and David Dodd discussed the concept of a range of value:
The essential point is that security analysis does not seek to determine exactly what is the intrinsic value of a given security. It needs only to establish that the value is adequate—e.g., to protect a bond or to justify a stock purchase—or else that the value is considerably higher or considerably lower than the market price. For such purposes an indefinite and approximate measure of the intrinsic value may be sufficient.
To be a value investor, you must buy at a discount from underlying value. Analyzing each potential value investment opportunity therefore begins with an assessment of business value. While a great many methods of business valuation exist, there are only three that I find useful. The first is an analysis of going-concern value, known as net present value (NPV) analy-sis. NPV is the discounted value of all future cash flows that a business is expected to generate. A frequently used but flawed shortcut method of valuing a going concern is known as private-market value. This is an investor’s assessment of the price that a sophisticated businessperson would be willing to pay for a business.
How do value investors deal with the analytical necessity to predict the unpredictable? The only answer is conservatism. Since all projections are subject to error, optimistic ones tend to place investors on a precarious limb. Virtually everything must go right, or losses may be sustained. Conservative forecasts can be more easily met or even exceeded. Investors are well advised to make only conservative projections and then invest only at a substantial discount from the valuations derived therefrom.
The other component of present-value analysis, choosing a discount rate, is rarely given sufficient consideration by investors. A discount rate is, in effect, the rate of interest that would make an investor indifferent between present and future dollars. Investors with a strong preference for present over future consumption or with a preference for the certainty of the present to the uncertainty of the future would use a high rate for discounting their investments. Other investors may be more willing to take a chance on forecasts holding true; they would apply a low discount rate, one that makes future cash flows nearly as valuable as today’s. There is no single correct discount rate for a set of future cash flows and no precise way to choose one. The appropriate discount rate for a particular investment depends not only on an investor’s preference for present over future consumption but also on his or her own risk profile, on the perceived risk of the investment under consideration, and on the returns available from alternative investments.
A valuation method related to net present value is private-market value, which values businesses based on the valuation multiples that sophisticated, prudent businesspeople have recently paid to purchase similar businesses. Private-market value can provide investors with useful rules of thumb based on the economics of past transactions to guide them in business valuation. This valuation method is not without its shortcomings, however. Within a given business or industry all companies are not the same, but private-market value fails to distinguish among them. Moreover, the multiples paid to acquire businesses vary over time; valuations may have changed since the most recent similar transaction. Finally, buyers of businesses do not necessarily pay reasonable, intelligent prices.
The liquidation value of a business is a conservative assessment of its worth in which only tangible assets are considered and intangibles, such as going-concern value, are not. Accordingly, when a stock is selling at a discount to liquidation value per share, a near rock-bottom appraisal, it is frequently an attractive investment.
In The Alchemy of Finance George Soros stated, “Fundamental analysis seeks to establish how underlying values are reflected in stock prices, whereas the theory of reflexivity shows how stock prices can influence underlying values.”7 In other words, Soros’s theory of reflexivity makes the point that its stock price can at times significantly influence the value of a business. Investors must not lose sight of this possibility.
Investment Research: The Challenge of Finding Attractive Investments
Value investing by its very nature is contrarian. Out-of-favor securities may be undervalued; popular securities almost never are. What the herd is buying is, by definition, in favor. Securities in favor have already been bid up in price on the basis of optimistic expectations and are unlikely to represent good value that has been overlooked.
Obviously investors need to be alert to the motivations of managements at the companies in which they invest.
Portfolio Management and Trading
The challenge of successfully managing an investment portfolio goes beyond making a series of good individual investment decisions. Portfolio management requires paying attention to the portfolio as a whole, taking into account diversification, possible hedging strategies, and the management of portfolio cash flow. In effect, while individual investment decisions should take risk into account, portfolio management is a further means of risk reduction for investors. Even relatively safe investments entail some probability, however small, of downside risk. The deleterious effects of such improbable events can best be mitigated through prudent diver-sification. The number of securities that should be owned to reduce portfolio risk to an acceptable level is not great; as few as ten to fifteen different holdings usually suffice. Diversification for its own sake is not sensible. This is the index fund mentality: if you can’t beat the market, be the market. Advocates of extreme diversification—which I think of as overdiversification—live in fear of company-specific risks; their view is that if no single position is large, losses from unanticipated events cannot be great. My view is that an investor is better off knowing a lot about a few investments than knowing only a little about each of a great many holdings. One’s very best ideas are likely to generate higher returns for a given level of risk than one’s hundredth or thousandth best idea.
Diversification, after all, is not how many different things you own, but how different the things you do own are in the risks they entail.
Some investors buy and hold for the long term, stashing their securities in the proverbial vault for years. While such a strategy may have made sense at some time in the past, it seems misguided today. This is because the financial markets are prolific creators of investment opportunities. Investors who are out of touch with the markets will find it difficult to be in touch with buying and selling opportunities regularly created by the markets. Today with so many market participants having little or no fundamental knowledge of the businesses their investments represent, opportunities to buy and sell seem to present themselves at a rapid pace.
Being in touch with the market does pose dangers, however. Investors can become obsessed, for example, with every market uptick and downtick and eventually succumb to short-term-oriented trading. There is a tendency to be swayed by recent market action, going with the herd rather than against it. Investors unable to resist such impulses should probably not stay in close touch with the market; they would be well advised to turn their investable assets over to a financial professional
The single most crucial factor in trading is developing the appropriate reaction to price fluctuations. Investors must learn to resist fear, the tendency to panic when prices are falling, and greed, the tendency to become overly enthusiastic when prices are rising. One half of trading involves learning how to buy. In my view, investors should usually refrain from purchasing a “full position” (the maximum dollar commitment they intend to make) in a given security all at once. Those who fail to heed this advice may be compelled to watch a subsequent price decline helplessly, with no buying power in reserve. Buying a partial position leaves reserves that permit investors to “average down,” lowering their average cost per share, if prices decline.
All investments are for sale at the right price. Decisions to sell, like decisions to buy, must be based upon underlying business value. Exactly when to sell—or buy— depends on the alternative opportunities that are available. Should you hold for partial or complete value realization, for example? It would be foolish to hold out for an extra fraction of a point of gain in a stock selling just below underlying value when the market offers many bargains. By contrast, you would not want to sell a stock at a gain (and pay taxes on it) if it were still significantly undervalued and if there were no better bargains available.
Investment Alternatives for the Individual Investor
Obviously a manager who has achieved dismal long-term results is not someone to hire to manage your money. Nevertheless, you would not necessarily hire the best-performing manager for a recent period either. Returns must always be examined in the context of risk. Consider asking whether the manager was fully invested at all times or even more than 100 percent invested through the use of borrowed money. (Leverage is neither necessary nor appropriate for most investors.)
What I got out of it
A beautiful overview on value investing from one of the all-time greats
A distillation of some of the key principles that Feynman covers in his lectures
Feynman was a theoretical physicist par excellence. Newton had been both experimentalist and theorist in equal measure. Einstein was quite simply contemptuous of experiment, preferring to put his faith in pure thought. Feynman was driven to develop a deep theoretical understanding of nature, but he always remained close to the real and often grubby world of experimental results.
Feynman diagrams are a symbolic but powerfully heuristic way of picturing what is going on when electrons, photons, and other particles interact with each other. These days Feynman diagrams are a routine aid to calculation, but in the early 1950s they marked a startling departure from the traditional way of doing theoretical physics.
The Feynman style can best be described as a mixture of reverence and disrespect for received wisdom. Physics is an exact science, and the existing body of knowledge, while incomplete, can’t simply be shrugged aside. Feynman acquired a formidable grasp of the accepted principles of physics at a very young age, and he chose to work almost entirely on conventional problems. He was not the sort of genius to beaver away in isolation in a backwater of the discipline and to stumble across the profoundly new. His special talent was to approach essentially mainstream topics in an idiosyncratic way. This meant eschewing existing formalisms and developing his own highly intuitive approach. Whereas most theoretical physicists rely on careful mathematical calculation to provide a guide and a crutch to take them into unfamiliar territory, Feynman’s attitude was almost cavalier. You get the impression that he could read nature like a book and simply report on what he found, without the tedium of complex analysis.
Physics is continually linked to other sciences while leaving the reader in no doubt about which is the fundamental discipline.
Right at the beginning of Six Easy Pieces we learn how all physics is rooted in the notion of law—the existence of an ordered universe that can be understood by the application of rational reasoning. However, the laws of physics are not transparent to us in our direct observations of nature.
A great unifying theme among particle physicists has been the role of symmetry and conservation laws in bringing order to the subatomic zoo.
First figure out why you want the students to learn the subject and what you want them to know, and the method will result more or less by common sense.
“The power of instruction is seldom of much efficacy except in those happy dispositions where it is almost superfluous.” (Gibbon)
You might ask why we cannot teach physics by just giving the basic laws on page one and then showing how they work in all possible circumstances, as we do in Euclidean geometry, where we state the axioms and then make all sorts of deductions. (So, not satisfied to learn physics in four years, you want to learn it in four minutes?) We cannot do it in this way for two reasons. First, we do not yet know all the basic laws: there is an expanding frontier of ignorance. Second, the correct statement of the laws of physics involves some very unfamiliar ideas which require advanced mathematics for their description. Therefore, one needs a considerable amount of preparatory training even to learn what the words mean. No, it is not possible to do it that way. We can only do it piece by piece. Each piece, or part, of the whole of nature is always merely an approximation to the complete truth, or the complete truth so far as we know it. In fact, everything we know is only some kind of approximation, because we know that we do not know all the laws as yet. Therefore, things must be learned only to be unlearned again or, more likely, to be corrected. The principle of science, the definition, almost, is the following: The test of all knowledge is experiment. Experiment is the sole judge of scientific “truth.” But what is the source of knowledge? Where do the laws that are to be tested come from? Experiment, itself, helps to produce these laws, in the sense that it gives us hints. But also needed is imagination to create from these hints the great generalizations—to guess at the wonderful, simple, but very strange patterns beneath them all, and then to experiment to check again whether we have made the right guess. This imagining process is so difficult that there is a division of labor in physics: there are theoretical physicists who imagine, deduce, and guess at new laws, but do not experiment; and then there are experimental physicists who experiment, imagine, deduce, and guess.
Now, what should we teach first? Should we teach the correct but unfamiliar law with its strange and difficult conceptual ideas, for example the theory of relativity, four-dimensional space-time, and so on? Or should we first teach the simple “constant-mass” law, which is only approximate, but does not involve such difficult ideas? The first is more exciting, more wonderful, and more fun, but the second is easier to get at first, and is a first step to a real understanding of the first idea. This point arises again and again in teaching physics. At different times we shall have to resolve it in different ways, but at each stage it is worth learning what is now known, how accurate it is, how it fits into everything else, and how it may be changed when we learn more.
If, in some cataclysm, all of scientific knowledge were to be destroyed, and only one sentence passed on to the next generations of creatures, what statement would contain the most information in the fewest words? I believe it is the atomic hypothesis (or the atomic fact, or whatever you wish to call it) that all things are made of atoms—little particles that move around in perpetual motion, attracting each other when they are a little distance apart, but repelling upon being squeezed into one another. In that one sentence, you will see, there is an enormous amount of information about the world, if just a little imagination and thinking are applied.
This means that when we compress a gas slowly, the temperature of the gas increases. So, under slow compression, a gas will increase in temperature, and under slow expansion it will decrease in temperature.
The difference between solids and liquids is, then, that in a solid the atoms are arranged in some kind of an array, called a crystalline array, and they do not have a random position at long distances; the position of the atoms on one side of the crystal is determined by that of other atoms millions of atoms away on the other side of the crystal.
Most simple substances, with the exception of water and type metal, expand upon melting, because the atoms are closely packed in the solid crystal and upon melting need more room to jiggle around, but an open structure collapses, as in the case of water.
As we decrease the temperature, the vibration decreases and decreases until, at absolute zero, there is a minimum amount of vibration that the atoms can have, but not zero. This minimum amount of motion that atoms can have is not enough to melt a substance, with one exception: helium. Helium merely decreases the atomic motions as much as it can, but even at absolute zero there is still enough motion to keep it from freezing. Helium, even at absolute zero, does not freeze, unless the pressure is made so great as to make the atoms squash together. If we increase the pressure, we can make it solidify.
The other processes so far described are called physical processes, but there is no sharp distinction between the two. (Nature does not care what we call it, she just keeps on doing it.)
Carbon attracts oxygen much more than oxygen attracts oxygen or carbon attracts carbon. Therefore in this process the oxygen may arrive with only a little energy, but the oxygen and carbon will snap together with a tremendous vengeance and commotion, and everything near them will pick up the energy. A large amount of motion energy, kinetic energy, is thus generated. This of course is burning; we are getting heat from the combination of oxygen and carbon. The heat is ordinarily in the form of the molecular motion of the hot gas, but in certain circumstances it can be so enormous that it generates light. That is how one gets flames.
if we look at very tiny particles (colloids) in water through an excellent microscope, we see a perpetual jiggling of the particles, which is the result of the bombardment of the atoms. This is called the Brownian motion.
Everything is made of atoms. That is the key hypothesis. The most important hypothesis in all of biology, for example, is that everything that animals do, atoms do. In other words, there is nothing that living things do that cannot be understood from the point of view that they are made of atoms acting according to the laws of physics. This was not known from the beginning: it took some experimenting and theorizing to suggest this hypothesis, but now it is accepted, and it is the most useful theory for producing new ideas in the field of biology.
A few hundred years ago, a method was devised to find partial answers to such questions. Observation, reason, and experiment make up what we call the scientific method.
What do we mean by “understanding” something? We can imagine that this complicated array of moving things which constitutes “the world” is something like a great chess game being played by the gods, and we are observers of the game. We do not know what the rules of the game are; all we are allowed to do is to watch the playing. Of course, if we watch long enough, we may eventually catch on to a few of the rules. The rules of the game are what we mean by fundamental physics…If we know the rules, we consider that we “understand” the world.
At first the phenomena of nature were roughly divided into classes, like heat, electricity, mechanics, magnetism, properties of substances, chemical phenomena, light or optics, x-rays, nuclear physics, gravitation, meson phenomena, etc. However, the aim is to see complete nature as different aspects of one set of phenomena. That is the problem in basic theoretical physics today—to find the laws behind experiment; to amalgamate these classes.
Some historic examples of amalgamation are the following. First, take heat and mechanics. When atoms are in motion, the more motion, the more heat the system contains, and so heat and all temperature effects can be represented by the laws of mechanics. Another tremendous amalgamation was the discovery of the relation between electricity, magnetism, and light, which were found to be different aspects of the same thing, which we call today the electromagnetic field. Another amalgamation is the unification of chemical phenomena, the various properties of various substances, and the behavior of atomic particles, which is in the quantum mechanics of chemistry. The question is, of course, is it going to be possible to amalgamate everything, and merely discover that this world represents different aspects of one thing? Nobody knows. All we know is that as we go along, we find that we can amalgamate pieces, and then we find some pieces that do not fit, and we keep trying to put the jigsaw puzzle together. Whether there are a finite number of pieces, and whether there is even a border to the puzzle, are of course unknown. It will never be known until we finish the picture, if ever. What we wish to do here is to see to what extent this amalgamation process has gone on, and what the situation is at present, in understanding basic phenomena in terms of the smallest set of principles. To express it in a simple manner, what are things made of and how few elements are there?
Because the chemical properties depend upon the electrons on the outside, and in fact only upon how many electrons there are. So the chemical properties of a substance depend only on a number, the number of electrons.
Magnetic influences have to do with charges in relative motion, so magnetic forces and electric forces can really be attributed to one field, as two different aspects of exactly the same thing.
X-rays are nothing but very high-frequency light.
The mechanical rules of “inertia” and “forces” are wrong—Newton’s laws are wrong—in the world of atoms. Instead, it was discovered that things on a small scale behave nothing like things on a large scale. That is what makes physics difficult—and very interesting. It is hard because the way things behave on a small scale is so ”unnatural“; we have no direct experience with it. Here things behave like nothing we know of, so that it is impossible to describe this behavior in any other than analytic ways. It is difficult, and takes a lot of imagination. Quantum mechanics has many aspects. In the first place, the idea that a particle has a definite location and a definite speed is no longer allowed; that is wrong.
there is a rule in quantum mechanics that says that one cannot know both where something is and how fast it is moving.
Another most interesting change in the ideas and philosophy of science brought about by quantum mechanics is this: it is not possible to predict exactly what will happen in any circumstance.
One of the consequences is that things which we used to consider as waves also behave like particles, and particles behave like waves; in fact everything behaves the same way. There is no distinction between a wave and a particle. So quantum mechanics unifies the idea of the field and its waves, and the particles, all into one.
We have been seeking a Mendeléev-type chart for the new particles. One such chart of the new particles was made independently by Gell-Mann in the USA and Nishijima in Japan. The basis of their classification is a new number, like the electric charge, which can be assigned to each particle, called its “strangeness,” S. This number is conserved, like the electric charge, in reactions which take place by nuclear forces.
What is this “zero mass”? The masses given here are the masses of the particles at rest. The fact that a particle has zero mass means, in a way, that it cannot be at rest. A photon is never at rest; it is always moving at 186,000 miles a second.
In fact, there seem to be just four kinds of interaction between particles which, in the order of decreasing strength, are the nuclear force, electrical interactions, the beta-decay interaction, and gravity.
Physics is the most fundamental and all-inclusive of the sciences, and has had a profound effect on all scientific development. In fact, physics is the present-day equivalent of what used to be called natural philosophy, from which most of our modern sciences arose. Students of many fields find themselves studying physics because of the basic role it plays in all phenomena.
Statistical mechanics, then, is the science of the phenomena of heat, or thermodynamics.
There was an interesting early relationship between physics and biology in which biology helped physics in the discovery of the conservation of energy, which was first demonstrated by Mayer in connection with the amount of heat taken in and given out by a living creature.
Thus most chemical reactions do not occur, because there is what is called an activation energy in the way. In order to add an extra atom to our chemical requires that we get it close enough that some rearrangement can occur; then it will stick. But if we cannot give it enough energy to get it close enough, it will not go to completion it will just go partway up the “hill” and back down again.
Physics is of great importance in biology and other sciences for still another reason, that has to do with experimental techniques. In fact, if it were not for the great development of experimental physics, these biochemistry charts would not be known today. The reason is that the most useful tool of all for analyzing this fantastically complex system is to label the atoms which are used in the reactions.
Proteins have a very interesting and simple structure. They are a series, or chain, of different amino acids. There are twenty different amino acids, and they all can combine with each other to form chains in which the backbone is CO-NH, etc. Proteins are nothing but chains of various ones of these twenty amino acids. Each of the amino acids probably serves some special purpose.
If our small minds, for some convenience, divide this glass of wine, this universe, into parts—physics, biology, geology, astronomy, psychology, and so on—remember that nature does not know it! So let us put it all back together, not forgetting ultimately what it is for.
There is a fact, or if you wish, a law, governing all natural phenomena that are known to date. There is no known exception to this law—it is exact so far as we know. The law is called the conservation of energy. It states that there is a certain quantity, which we call energy, that does not change in the manifold changes which nature undergoes.
In order to verify the conservation of energy, we must be careful that we have not put any in or taken any out. Second, the energy has a large number of different forms, and there is a formula for each one. These are gravitational energy, kinetic energy, heat energy, elastic energy, electrical energy, chemical energy, radiant energy, nuclear energy, mass energy. If we total up the formulas for each of these contributions, it will not change except for energy going in and out.
We call the sum of the weights times the heights gravitational potential energy—the energy which an object has because of its relationship in space, relative to the earth.
The general name of energy which has to do with location relative to something else is called potential energy. In this particular case, of course, we call it gravitational potential energy.
Elastic energy is the formula for a spring when it is stretched. How much energy is it? If we let go, the elastic energy, as the spring passes through the equilibrium point, is converted to kinetic energy and it goes back and forth between compressing or stretching the spring and kinetic energy of motion.
other conservation laws there are in physics. There are two other conservation laws which are analogous to the conservation of energy. One is called the conservation of linear momentum. The other is called the conservation of angular momentum.
The laws which govern how much energy is available are called the laws of thermodynamics and involve a concept called entropy for irreversible thermodynamic processes.
What is this law of gravitation? It is that every object in the universe attracts every other object with a force which for any two bodies is proportional to the mass of each and varies inversely as the square of the distance between them. This statement can be expressed mathematically by the equation
Galileo discovered a very remarkable fact about motion, which was essential for understanding these laws. That is the principle of inertia—if something is moving, with nothing touching it and completely undisturbed, it will go on forever, coasting at a uniform speed in a straight line. (Why does it keep on coasting? We do not know, but that is the way it is.) Newton modified this idea, saying that the only way to change the motion of a body is to use force. If the body speeds up, a force has been applied in the direction of motion. On the other hand, if its motion is changed to a new direction, a force has been applied sideways. Newton thus added the idea that a force is needed to change the speed or the direction of motion of a body.
Any great discovery of a new law is useful only if we can take more out than we put in.
Why can we use mathematics to describe nature without a mechanism behind it? No one knows. We have to keep going because we find out more that way.
We conclude the following: The electrons arrive in lumps, like particles, and the probability of arrival of these lumps is distributed like the distribution of intensity of a wave. It is in this sense that an electron behaves “sometimes like a particle and sometimes like a wave.”
“It is impossible to design an apparatus to determine which hole the electron passes through, that will not at the same time disturb the electrons enough to destroy the interference pattern.” If an apparatus is capable of determining which hole the electron goes through, it cannot be so delicate that it does not disturb the pattern in an essential way. No one has ever found (or even thought of) a way around the uncertainty principle. So we must assume that it describes a basic characteristic of nature. The complete theory of quantum mechanics which we now use to describe atoms and, in fact, all matter depends on the correctness of the uncertainty principle.
We would like to emphasize a very important difference between classical and quantum mechanics. We have been talking about the probability that an electron will arrive in a given circumstance. We have implied that in our experimental arrangement (or even in the best possible one) it would be impossible to predict exactly what would happen. We can only predict the odds!
What I got out of it
A fun introductory lesson into some key physics ideas and a great view into Feynman’s thinking process
“This book is about innovation—about how it happens, why it happens, and who makes it happen. It is likewise about why innovation matters, not just to scientists, engineers, and corporate executives but to all of us. That the story is about Bell Labs, and even more specifically about life at the Labs between the late 1930s and the mid-1970s, isn’t a coincidence.” The people helping to make it happen including Mervin Kelly, Jim Fisk, William Shockley, Claude Shannon, John Pierce, and William Baker.
Where is the knowledge we have lost in information? —T. S. Eliot, The Rock
Yet understanding the circumstances that led up to that unusual winter of 1947 at Bell Labs, and what happened there in the years afterward, promises a number of insights into how societies progress. With this in mind, one might think of a host of reasons to look back at these old inventions, these forgotten engineers, these lost worlds.
Edison’s genius lay in making new inventions work, or in making existing inventions work better than anyone had thought possible. But how they worked was to Edison less important.
Contrary to its gentle image of later years, created largely through one of the great public relations machines in corporate history, Ma Bell in its first few decades was close to a public menace—a ruthless, rapacious, grasping “Bell Octopus,” as its enemies would describe it to the press. “The Bell Company has had a monopoly more profitable and more controlling—and more generally hated—than any ever given by any patent,” one phone company lawyer admitted.
AT&T’s savior was Theodore Vail, who became its president in 1907, just a few years after Millikan’s friend Frank Jewett joined the company.11 In appearance, Vail seemed almost a caricature of a Gilded Age executive: Rotund and jowly, with a white walrus mustache, round spectacles, and a sweep of silver hair, he carried forth a magisterial confidence. But he had in fact begun his career as a lowly telegraph operator. Thoughtfulness was his primary asset; he could see almost any side of an argument. Also, he could both disarm and outfox his detractors. As Vail began overseeing Bell operations, he saw that the costs of competition were making the phone business far less profitable than it had been—so much so, in fact, that Vail issued a frank corporate report in his first year admitting that the company had amassed an “abnormal indebtedness.” If AT&T were to survive, it had to come up with a more effective strategy against its competition while bolstering its public image.
Vail didn’t do any of this out of altruism. He saw that a possible route to monopoly—or at least a near monopoly, which was what AT&T had always been striving for—could be achieved not through a show of muscle but through an acquiescence to political supervision. Yet his primary argument was an idea. He argued that telephone service had become “necessary to existence.” Moreover, he insisted that the public would be best served by a technologically unified and compatible system—and that it made sense for a single company to be in charge of it. Vail understood that government, or at least many politicians, would argue that phone subscribers must have protections against a monopoly; his company’s expenditures, prices, and profits would thus have to be set by federal and local authorities. As a former political official who years before had modernized the U.S. Post Office to great acclaim, Vail was not hostile toward government. Still, he believed that in return for regulation Ma Bell deserved to find the path cleared for reasonable profits and industry dominance. In Vail’s view, another key to AT&T’s revival was defining it as a technological leader with legions of engineers working unceasingly to improve the system.
The Vail strategy, in short, would measure the company’s progress “in decades instead of years.” Vail also saw it as necessary to merge the idea of technological leadership with a broad civic vision. His publicity department had come up with a slogan that was meant to rally its public image, but Vail himself soon adopted it as the company’s core philosophical principle as well. It was simple enough: “One policy, one system, universal service.” That this was a kind of wishful thinking seemed not to matter.
“Of its output,” Arnold would later say of his group, “inventions are a valuable part, but invention is not to be scheduled nor coerced.” The point of this kind of experimentation was to provide a free environment for “the operation of genius.” His point was that genius would undoubtedly improve the company’s operations just as ordinary engineering could. But genius was not predictable. You had to give it room to assert itself.
From the start, Jewett and Arnold seemed to agree that at West Street there could be an indistinctness about goals. Who could know in advance exactly what practical applications Arnold’s men would devise? Moreover, which of these ideas would ultimately move from the research department into the development department and then mass production at Western Electric? At the same time, they were clear about larger goals. The Bell Labs employees would be investigating anything remotely related to human communications, whether it be conducted through wires or radio or recorded sound or visual images.
The industrial lab showed that the group—especially the interdisciplinary group—was better than the lone scientist or small team. Also, the industrial lab was a challenge to the common assumption that its scientists were being paid to look high and low for good ideas. Men like Kelly and Davisson would soon repeat the notion that there were plenty of good ideas out there, almost too many. Mainly, they were looking for good problems.
Quantum mechanics, as it was beginning to be called, was a science of deep surprises, where theory had largely outpaced the proof of experimentation. Some years later the physicist Richard Feynman would elegantly explain that “it was discovered that things on a small scale behave nothing like things on a large scale.” In the quantum world, for instance, you could no longer say that a particle has a certain location or speed. Nor was it possible, Feynman would point out, “to predict exactly what will happen in any circumstance.”
The Great Depression, as it happened, was a boon for scientific knowledge. Bell Labs had been forced to reduce its employees’ hours, but some of the young staffers, now with extra time on their hands, had signed up for academic courses at Columbia University in uptown Manhattan.
“The [Bell] System,” Danielian pointed out, “constitutes the largest aggregation of capital that has ever been controlled by a single private company at any time in the history of business. It is larger than the Pennsylvania Railroad Company and United States Steel Corporation put together. Its gross revenues of more than one billion dollars a year are surpassed by the incomes of few governments of the world. The System comprises over 200 vassal corporations. Through some 140 companies it controls between 80 and 90 percent of local telephone service and 98 percent of the long-distance telephone wires of the United States.”
The 512A was an example of how, if good problems led to good inventions, then good inventions likewise would lead to other related inventions, and that nothing was too small or incidental to be excepted from improvement. Indeed, the system demanded so much improvement, so much in the way of new products, so much insurance of durability, that new methods had to be created to guarantee there was improvement and durability amid all the novelty.
We usually imagine that invention occurs in a flash, with a eureka moment that leads a lone inventor toward a startling epiphany. In truth, large leaps forward in technology rarely have a precise point of origin. At the start, forces that precede an invention merely begin to align, often imperceptibly, as a group of people and ideas converge, until over the course of months or years (or decades) they gain clarity and momentum and the help of additional ideas and actors. Luck seems to matter, and so does timing, for it tends to be the case that the right answers, the right people, the right place—perhaps all three—require a serendipitous encounter with the right problem. And then—sometimes—a leap. Only in retrospect do such leaps look obvious.
There was something in particular about the way he [William Shockley] solved difficult problems, looking them over and coming up with a method—often an irregular method, solving them backward or from the inside out or by finding a trapdoor that was hidden to everyone else—to arrive at an answer in what seemed a few heartbeats.
By intention, everyone would be in one another’s way. Members of the technical staff would often have both laboratories and small offices—but these might be in different corridors, therefore making it necessary to walk between the two, and all but assuring a chance encounter or two with a colleague during the commute. By the same token, the long corridor for the wing that would house many of the physics researchers was intentionally made to be seven hundred feet in length. It was so long that to look down it from one end was to see the other end disappear at a vanishing point. Traveling its length without encountering a number of acquaintances, problems, diversions, and ideas would be almost impossible. Then again, that was the point. Walking down that impossibly long tiled corridor, a scientist on his way to lunch in the Murray Hill cafeteria was like a magnet rolling past iron filings.
Essentially Kelly was creating interdisciplinary groups—combining chemists, physicists, metallurgists, and engineers; combining theoreticians with experimentalists—to work on new electronic technologies.
If the ingredients in the alloy weren’t pure—if they happened to contain minute traces of carbon, oxygen, or nitrogen, for instance—Permendur would be imperfect. “There was a time not so long ago when a thousandth of a percent or a hundredth of a percent of a foreign body in a chemical mixture was looked upon merely as an incidental inclusion which could have no appreciable effect on the characteristics of the substance,” Frank Jewett, the first president of the Labs, explained. “We have learned in recent years that this is an absolutely erroneous idea.”
For Scaff and Theurer—and, in time, the rest of the solid-state team at Bell Labs—one way to think of these effects was that purity in a semiconductor was necessary. But so was a controlled impurity. Indeed, an almost vanishingly small impurity mixed into silicon, having a net effect of perhaps one rogue atom of boron or phosphorus inserted among five or ten million atoms of a pure semiconductor like silicon, was what could determine whether, and how well, the semiconductor could conduct a current. One way to think of it—a term that was sometimes used at the Labs—was as a functional impurity.
The formal purpose of the new solid-state group was not so much to build something as to understand it. Officially, Shockley’s men were after a basic knowledge of their new materials; only in the back of their minds did a few believe they would soon find something useful for the Bell System.
On November 17, Brattain and an electrochemist in the solid-state group, Robert Gibney, explored whether applying an electrolyte—a solution that conducts electricity—in a particular manner would help cut through the surface states barrier. It did. Shockley would later identify this development as a breakthrough and the beginning of what he called “the magic month.” In time, the events of the following weeks would indeed be viewed by some of the men in terms resembling enchantment—the team’s slow, methodical success effecting the appearance of preordained destiny. For men of science, it was an odd conclusion to draw. Yet Walter Brattain would in time admit he had “a mystical feeling” that what he ultimately discovered had been waiting for him.
Any Bell scientist knew about the spooky and coincidental nature of important inventions. The origins of their entire company—Alexander Bell’s race to the patent office to beat Elisha Gray and become the recognized inventor of the telephone—was the textbook case.
If an idea begat a discovery, and if a discovery begat an invention, then an innovation defined the lengthy and wholesale transformation of an idea into a technological product (or process) meant for widespread practical use. Almost by definition, a single person, or even a single group, could not alone create an innovation. The task was too variegated and involved.
“It is the beginning of a new era in telecommunications and no one can have quite the vision to see how big it is,” Mervin Kelly told an audience of telephone company executives in 1951. Speaking of the transistor, he added that “no one can predict the rate of its impact.” Kelly admitted that he wouldn’t see its full effect before he retired from the Labs, but that “in the time I may live, certainly in 20 years,” it would transform the electronics industry and everyday life in a manner much more dramatic than the vacuum tube. The telecommunications systems of the future would be “more like the biological systems of man’s brain and nervous system.” The tiny transistor had reduced dimensions and power consumption “so far that we are going to get into a new economic area, particularly in switching and local transmission, and other places that we can’t even envision now.” It seemed to be some kind of extended human network he had in mind, hazy and fantastical and technologically sophisticated, one where communications whipped about the globe effortlessly and where everyone was potentially in contact with everyone else.
He could remember, too, that as the tubes became increasingly common—in the phone system, radios, televisions, automobiles, and the like—they had come down to price levels that once seemed impossible. He had long understood that innovation was a matter of economic imperatives. As Jack Morton had said, if you hadn’t sold anything you hadn’t innovated, and without an affordable price you could never sell anything. So Kelly looked at the transistor and saw the past, and the past was tubes. He thereby intuited the future.
“A Mathematical Theory of Communication”—“the magna carta of the information age,” as Scientific American later called it—wasn’t about one particular thing, but rather about general rules and unifying ideas. “He was always searching for deep and fundamental relations,” Shannon’s colleague Brock McMillan explains. And here he had found them. One of his paper’s underlying tenets, Shannon would later say, “is that information can be treated very much like a physical quantity, such as mass or energy.”
One shouldn’t necessarily think of information in terms of meaning. Rather, one might think of it in terms of its ability to resolve uncertainty. Information provided a recipient with something that was not previously known, was not predictable, was not redundant. “We take the essence of information as the irreducible, fundamental underlying uncertainty that is removed by its receipt,” a Bell Labs executive named Bob Lucky explained some years later. If you send a message, you are merely choosing from a range of possible messages. The less the recipient knows about what part of the message comes next, the more information you are sending.
(1) All communications could be thought of in terms of information; (2) all information could be measured in bits; (3) all the measurable bits of information could be thought of, and indeed should be thought of, digitally. This could mean dots or dashes, heads or tails, or the on/off pulses that comprised PCM.
His calculations showed that the information content of a message could not exceed the capacity of the channel through which you were sending it. Much in the same way a pipe could only carry so many gallons of water per second and no more, a transmission channel could only carry so many bits of information at a certain rate and no more. Anything beyond that would reduce the quality of your transmission. The upshot was that by measuring the information capacity of your channel and by measuring the information content of your message you could know how fast, and how well, you could send your message. Engineers could now try to align the two—capacity and information content.
Shannon’s paper contained a claim so surprising that it seemed impossible to many at the time, and yet it would soon be proven true. He showed that any digital message could be sent with virtual perfection, even along the noisiest wire, as long as you included error-correcting codes—essentially extra bits of information, formulated as additional 1s and 0s—with the original message. In his earlier paper on cryptography, Shannon had already shown that by reducing redundancy you could compress a message to transmit its content more efficiently. Now he was also demonstrating something like the opposite: that in some situations you could increase the redundancy of a message to transmit it more accurately.
And yet Kelly would say at one point, “With all the needed emphasis on leadership, organization and teamwork, the individual has remained supreme—of paramount importance. It is in the mind of a single person that creative ideas and concepts are born.” There was an essential truth to this, too—John Bardeen suddenly suggesting to the solid-state group that they should consider working on the hard-to-penetrate surface states on semiconductors, for instance. Or Shockley, mad with envy, sitting in his Chicago hotel room and laying the groundwork for the junction transistor. Or Bill Pfann, who took a nap after lunch and awoke, as if from an edifying dream, with a new method for purifying germanium. Of course, these two philosophies—that individuals as well as groups were necessary for innovation—weren’t mutually exclusive. It was the individual from which all ideas originated, and the group (or the multiple groups) to which the ideas, and eventually the innovation responsibilities, were transferred.
He would acknowledge that building devices like chess-playing machines “might seem a ridiculous waste of time and money. But I think the history of science has shown that valuable consequences often proliferate from simple curiosity.” “He never argued his ideas,” Brock McMillan says of Shannon. “If people didn’t believe in them, he ignored those people.”
In truth, the handoff between the three departments at Bell Labs was often (and intentionally) quite casual. Part of what seemed to make the Labs “a living organism,” Kelly explained, were social and professional exchanges that moved back and forth, in all directions, between the pure researchers on one side and the applied engineers on the other. These were formal talks and informal chats, and they were always encouraged, both as a matter of policy and by the inventive design of the Murray Hill building.
Physical proximity, in Kelly’s view, was everything. People had to be near one another. Phone calls alone wouldn’t do. Kelly had even gone so far as to create “branch laboratories” at Western Electric factories so that Bell Labs scientists could get more closely involved in the transition of their work from development to manufacture.
Bell Labs had the advantage of necessity; its new inventions, as one of Kelly’s deputies, Harald Friis, once said, “always originated because of a definite need.”
To innovate, Kelly would agree, an institute of creative technology required the best people, Shockleys and Shannons, for instance—and it needed a lot of them, so many, as the people at the Labs used to say (borrowing a catchphrase from nuclear physics), that departments could have a “critical mass” to foster explosive ideas.
There was no precise explanation as to why this was such an effective goad, but even for researchers in pursuit of pure scientific understanding rather than new things, it was obvious that their work, if successful, would ultimately be used. Working in an environment of applied science, as one Bell Labs researcher noted years later, “doesn’t destroy a kernel of genius—it focuses the mind.”
An instigator is different from a genius, but just as uncommon. An instigator is different, too, from the most skillful manager, someone able to wrest excellence out of people who might otherwise fall short. Somewhere between Shannon (the genius) and Kelly (the manager), Pierce steered a course for himself at Bell Labs as an instigator. “I tried to get other people to do things, I’m lazy,” Pierce once told an interviewer.
Pierce’s real talent, according to Friis and Pierce himself, was in getting people interested in something that hadn’t really occurred to them before.
Pierce had been correct in some respects about the traveling wave tube’s potential. But as he came to understand, inventions don’t necessarily evolve into the innovations one might at first foresee. Humans all suffered from a terrible habit of shoving new ideas into old paradigms. “Everyone faces the future with their eyes firmly on the past,” Pierce said, “and they don’t see what’s going to happen next.”
A terrestrial signal could be directed toward the orbiting satellite in space; the satellite, much like a mirror, could in turn direct the signal to another part of the globe. Pierce didn’t consider himself the inventor of this idea; it was, he would later say, “in the air.”
Ideas may come to us out of order in point of time,” the first director of the Rockefeller Institute for Medical Research, Simon Flexner, once remarked. “We may discover a detail of the façade before we know too much about the foundation. But in the end all knowledge has its place.”
Why move in this direction? What kind of future did the men envision? One of the more intriguing attributes of the Bell System was that an apparent simplicity—just pick up the phone and dial—hid its increasingly fiendish interior complexity. What also seemed true, and even then looked to be a governing principle of the new information age, was that the more complex the system became in terms of capabilities, speed, and versatility, the simpler and sleeker it appeared. ESS was a case in point.
I liked Fisk very much. But the combination of Fisk, who didn’t know a lot about what was going on in the bowels of the place, and Julius, who knew everything about what was going on in the bowels of the place, was a good combination.”
Colleagues often stood amazed that Baker could recall by name someone he had met only once, twenty or thirty years before. His mind wasn’t merely photographic, though; it worked in some ways like a switching apparatus: He tied everyone he ever met, and every conversation he ever had, into a complex and interrelated narrative of science and technology and society that he constantly updated, with apparent ease.
To Pollak, this was a demonstration not of Bill Baker’s cruelty but of his acumen—in this case to push his deep belief that science rests on a foundation of inquiry rather than certainty. Also, it revealed how nimble Baker’s mind really was. “A very small number of times in my life I’ve been in the presence of somebody who didn’t necessarily answer the question I asked. They answered the question I should have asked,” Pollak says. “And Bill Baker was one of those people. And there are other people who just build a mystique and give the impression of a mystique around them. And Bill had that, too.”
New titles might not have increased his influence. By the start of the 1960s Baker was engaged in a willfully obscure second career, much like the one Mervin Kelly had formerly conducted, a career that ran not sequentially like some men’s—a stint in government following a stint in business, or vice versa—but simultaneously, so that Baker’s various jobs in Washington and his job at Bell Labs intersected in quiet and complex and multifarious ways. Baker could bring innovations in communications to the government’s attention almost instantly.
“So often,” says Ian Ross, who worked in Jack Morton’s department at Bell Labs doing transistor development in the 1950s, “the original concept of what an innovation will do”—the replacement of the vacuum tube, in this case—“frequently turns out not to be the major impact.” The transistor’s greatest value was not as a replacement for the old but as an exponent for the new—for computers, switches, and a host of novel electronic technologies.
Innovations are to a great extent a response to need.
In the wake of the 1956 agreement, AT&T appeared to be indestructible. It now had the U.S. government’s blessing. It was easily the largest company in the world by assets and by workforce. And its Bell Laboratories, as Fortune magazine had declared, was indisputably “the world’s greatest industrial laboratory.” And yet even in the 1960s and 1970s, as Bill Baker’s former deputy Ian Ross recalls, the “long, long history of worry about losing our monopoly status persisted.” To a certain extent, Bill Baker and Mervin Kelly believed their involvement in government affairs could lessen these worries. In the view of Ross and others, such efforts probably helped delay a variety of antitrust actions. Ross recalls, “Kelly set up Sandia Labs, which was run by AT&T, managed by us, and whenever I asked, ‘Why do we stay with this damn thing, it’s not our line of business,’ the answer was, ‘It helps us if we get into an antitrust suit.’ And Bell Labs did work on military programs. Why? Not really to make money. It was part of being invaluable.”
The fundamental goal in making transistor materials is purity; the fundamental goal in making fiber materials is clarity. Only then can light pass through unimpeded; or as optical engineers say, only then can “losses” of light in the fiber be kept to an acceptable minimum.
Indeed, a marketing study commissioned by AT&T in the fall of 1971 informed its team that “there was no market for mobile phones at any price.” Neither man agreed with that assessment. Though Engel didn’t perceive it at the time, he later came to believe that marketing studies could only tell you something about the demand for products that actually exist. Cellular phones were a product that people had to imagine might exist.
Pierce later remarked that one thing about Kelly impressed him above all else: It had to do with how his former boss would advise members of Bell Labs’ technical staff when they were asked to work on something new. Whether it was a radar technology for the military or solid-state research for the phone company, Kelly did not want to begin a project by focusing on what was known. He would want to begin by focusing on what was not known. As Pierce explained, the approach was both difficult and counterintuitive. It was more common practice, at least in the military, to proceed with what technology would allow and fill in the gaps afterward. Kelly’s tack was akin to saying: Locate the missing puzzle piece first. Then do the puzzle.
Shannon had become wealthy, too, through friends in the technology industry. He owned significant shares in Hewlett-Packard, where his friend Barney Oliver ran the research labs, and was deeply invested in Teledyne, a conglomerate started by another friend, Henry Singleton. Shannon sat on Teledyne’s board of directors.
“Ideas and plans are essential to innovation,” he remarked, “but the time has to be right.”
“It is just plain silly,” he wrote, “to identify the new AT&T Bell Laboratories with the old Bell Telephone Laboratories just because the new Laboratories has inherited buildings, equipment and personnel from the old. The mission was absolutely essential to the research done at the old Laboratories, and that mission is gone and has not been replaced.”
At the time of the breakup, in fact, it was widely assumed in the business press that IBM and AT&T would now struggle for supremacy. What undermined such an assumption was the historical record: Everything Bell Labs had ever made for AT&T had been channeled into a monopoly business. “One immediate problem for which no amount of corporate bulk can compensate is the firm’s lack of marketing expertise,” one journalist, Christopher Byron of Time, noted. It was a wise point. Bell Labs and AT&T had “never really had to sell anything.”3 And when they had tried—as was the case with the Picturephone—they failed. Government regulation, as AT&T had learned, could be immensely difficult to manage and comply with. But markets, they would soon discover, were simply brutal. AT&T’s leaders, such as CEO Charlie Brown, “had never had the experience or the training to compete,” Irwin Dorros, a former Bell Labs and AT&T executive, points out. “They tried to apply the skills that they grew up with, and it didn’t work.” In later years, the downsizing at Bell Labs, in terms of both purpose and people, would mostly be linked to this inability to compete.
The purpose of innovation is sometimes defined as new technology. But the point of innovation isn’t really technology itself. The point of innovation is what new technology can do. “Better, or cheaper, or both”—Kelly’s rule—is one way to think about this goal.
A large group of physicists, certainly, created a healthy flow of ideas. But Kelly believed the most valuable ideas arose when the large group of physicists bumped against other departments and disciplines, too. “It’s the interaction between fundamental science and applied science, and the interface between many disciplines, that creates new ideas,” explains Herwig Kogelnik, the laser scientist. This may indeed have been Kelly’s greatest insight.
Eugene Kleiner, moreover, a founding partner at the premier venture capital firm Kleiner Perkins, was originally hired by Bill Shockley at his ill-fated semiconductor company. But the Silicon Valley process that Kleiner helped develop was a different innovation model from Bell Labs. It was not a factory of ideas; it was a geography of ideas. It was not one concentrated and powerful machine; it was the meshing of many interlocking small parts grouped physically near enough to one another so as to make an equally powerful machine. The Valley model, in fact, was soon so productive that it became a topic of study for sociologists and business professors. They soon bestowed upon the area the title of an “innovation hub.”
“You may find a lot of controversy over how Bell Labs managed people,” John Mayo, the former Bell Labs president, says. “But keep in mind, I don’t think those managers saw it that way. They saw it as: How do you manage ideas? And that’s very different from managing people. So if you hear something negative about how John Pierce managed people, I’d say, well, that’s not surprising. Pierce wasn’t about managing people. Pierce was about managing ideas. And you cannot manage ideas and manage people the same way. It just doesn’t work. So if somebody tells you Pierce wasn’t a great manager . . . you say, of what?”
Pierce, to put it simply, was asking himself: What about Bell Labs’ formula was timeless? In his 1997 list, he thought it boiled down to four things: A technically competent management all the way to the top. Researchers didn’t have to raise funds. Research on a topic or system could be and was supported for years. Research could be terminated without damning the researcher.
What seems more likely, as the science writer Steven Johnson has noted in a broad study of scientific innovations, is that creative environments that foster a rich exchange of ideas are far more important in eliciting important new insights than are the forces of competition.
To think long-term toward the revolutionary, and to simultaneously think near-term toward manufacturing, comprises the most vital of combinations.
What I got out of it
The dominance of AT&T and how they were able to structure the organization to take advantage of the talent at Bell Labs was great to learn more about. Having to build or invent something which will have to go to market is important, having a diverse group of people who interact often, and “A technically competent management all the way to the top. Researchers didn’t have to raise funds. Research on a topic or system could be and was supported for years. Research could be terminated without damning the researcher.”
The tendencies of basic biological, social and technological evolutions can be explained in scientific, physical terms. Directionality seems to be imputed and the author argues that Non-Zero Sum games has been the driving force for biological life. The core of biological and human history can be traced back to more numerous, larger, more elaborate, more interdependent forms of NZS games being played. “Non-Zero Sumness” can be thought of as the tendency which gives time its directionality, helping explain how NZS was likely to lead to complex life forms and technology which further enriched how these life forms interacted
Game theory was developed by von Neumann. Zero sum games are games in which one person’s win means another person’s loss (sports) whereas Non-Zero sum games aren’t necessarily negative for one party. The authors argue that NZS games are a driving force for the world has been shaped. NZS games can be win/win, win/lose, lose/win, or lose/lose
Human history has shown that technological advancements allow for richer and more widespread NZS thinking and actions to occur, and social structures evolve from these interactions to more fully capitalize on these positive sum interactions, increasing social complexity and depth. NZS is not always win/win, but it trends in that direction and this causes people to become more embedded in webs of mutual interdependence.
Hunting large prey requires coordination which spurs altruism, reciprocity, social complexity, and positive sum games. “The best place to store your excess food is somebody else’s stomach.”
The author argues that population density is the overriding factor in predicting technological evolution and social complexity in a group of people
A quick summary of NZS would be the extent to which outcomes are shared, also known as skin in the game
Writing builds trust in a society (lenders don’t have to worry about debtors cheating them and vice versa, etc.) which helps streamline much of life and leads to positive sum outcomes
Increasing NZS leads to a more interconnected and codependent world where you not only care about your local neighbors but also the global community as trade commerce and ideas seamlessly transfer from one area to another
Increasing seamlessness in travel, commerce, communication, mostly driven by improvements in technology lead to new areas and opportunities for NZS, and how open and willing countries are to adopt the new technology and drive it’s future success and ability to capitalize on these positive sum games.
Technology, freedom, and increasing wealth seem to be inherently and intimately intertwined
NZS is responsible for reciprocal altruism love has evolution selected for those who could cooperate with each other and survive and this helped in hard times when others with chip in to pay back your favor
Time’s arrow does not necessarily point towards complexity but competition, survival, and natural selection push species to become more adapted and more complex in their thinking and behavior just in order to survive. If there was no competition and no threat of being eaten, animals don’t naturally just become more complex. Positive feedback at play
Natural selection beautifully fills in open inches
Truly valuable traits evolve independently. For example eyesight and reciprocal altruism evolved in multiple times and species. These are prime behaviors that have helped species survive for eons and are traits that we can bank on
What I got out of it
Really interesting idea that non-zero games, technological advancement, win/win have spurred evolution towards complexity in behavior
Harris walks us through some key persuasion traits and habits
The 11 Habits
Being your own weird self makes it difficult for others to see you as phony or manipulative, and allows them to recognize you as a unique individual.
The power of storytelling will help you to reframe contentious issues and offer your point of view in a way that resonates on a human level.
Never be closing and avoiding the “hard sell” will help demonstrate that you care about things other than your own immediate gain.
Give yourself away by seeking to give something away in every interaction. You’ll be laying the groundwork for cooperation.
The pull of positivity counteracts the negative emotions that separate us.
Just a little respect can neutralize toxic “us versus them” thinking on the part of your audience.
It’s not me, it’s us is the ability to see things from the perspective of others. Truly empathizing with someone else’s point of view will enable you to meet your audience on their own terms and guide them to a new point of view.
Collaboration will lead others to see you as a member of their team, making them far more likely to take your side now and in the future.
Finding common ground involves learning to see people as basically similar. This will combat tribal tendencies in your own thinking and will help move others to do the same.
Skill-hunting brings a high level of proficiency to everything that you do, lending you an innate authority that carries real influence.
Being a source of inspiration will help others to move past their normal limitations and join you in your positive pursuits.
The 11 Habits fit into 4 core patterns
First, persuasive people are original. When they speak, you sense they are coming from a place of authenticity and honesty and that you’re getting a glimpse of the real, unique them—not some prepackaged version designed to please you.
Second, persuasive people are generous. They give habitually and without expecting things in return. I’m not just talking about money or physical gifts. Persuasive people also are generous with advice, opportunities, introductions, respect, and emotional positivity. You never get the impression that they are just looking out for themselves.
Third, persuasive people are empathetic. They are naturally curious about other people and seek out engaging conversations that delve past small talk into topics that genuinely matter to others.
Finally, persuasive people are soulful. They hold themselves to their own self-imposed ethical and personal standards, always strive to be better, and motivate others to push beyond their normal limits. They are sources of inspiration for those around them. As a result, they possess a personal authority that makes them naturally influential.
Specifically, you should always be on the lookout for people you admire for their sincere, no-bullshit demeanor.
The methods I’ve found to avoid this kind of insincerity are: Put your true self out there. Speak and act with confidence. Collect role models. Boldly follow your core values.
If you can’t state your message in a single uncomplicated sentence, you haven’t got one. And if you’re trying to communicate more than one message with a single story, then you’re likely to lose your audience.
Persuasion isn’t about coercing your audience to do what you want. Rather, it’s about attracting them to a particular conclusion, and letting them get there on their own. Being pulled is always preferable to being pushed.
Transactions are about getting what you want; the long game is about forging relationships. “Always be closing” is about pushing people to do something; the long game is about pulling people toward your way of seeing things by engaging them on a human level.
Rule 1: Never Sell Anything You Wouldn’t Buy Yourself
Rule 2: The Simple Power of No
Rule 3: Never Let Relationships Drop to Zero
Pick four people a week to touch base with. It doesn’t need to be a long email or phone conversation—it could just be a quick “I was thinking about X and that reminded me of you” text message. It could also be a face-to-face meeting or scheduled phone call.
Don’t force the interaction; just make the introduction and let them do the rest. Your goal is to value relationships for their own sake—and that includes other people’s relationships.
Rule 4: Put Some Skin in the Game
It’s long been thought that one of the best ways to wield influence is by engaging in reciprocal, give-and-take exchanges. But this is a paradigm example of the kind of transactional thinking that undermines one’s persuasiveness in the long run. Focus solely on the “give.” Simple as it may seem, habitually generous people are more persuasive. So get in the habit of giving things away in as many interactions as possible. Some of the latest science backs me up. Human beings evolved to be generous, it turns out, because it was a reliable way to get people to cooperate. And in a real-world environment where people aren’t always in a position to reciprocate, a default generosity is a proven way to earn people’s trust and appreciation. The more you look at your interactions with others as opportunities to give, the more you will recognize what’s being asked of you or what you have to contribute. Giving breaks down into four categories: Time and attention Advice and recommendations Compliments and recognition Stuff What’s crucial is that no matter what you’re giving away, it must be something you find valuable. Just as important, you can’t expect anything in return. Being generous will make you a happier person and will create stronger relationships and bonds with those in your life. If you become the kind of person who exhibits a generous character, persuasiveness will be a natural by-product. The returns that come from putting good things into the world will accrue with compound interest.
That’s why a respectful disposition is an essential ingredient for a persuasive character. How to be respectful comes down to three elements: RESPECT OTHERS: Be reliable by doing what you say you will, no matter how small the commitment. RESPECT TIME: Remain present in conversation (and if you can’t, tell the audience why). RESPECT MISTAKES: Admit it when you do screw up or do the wrong thing, and use these moments to demonstrate your thorough respect, generosity, and honesty by handling the situation gracefully and taking responsibility. If you want to remain influential, you need to use these situations as opportunities to show people the real you.
We can decide to be more empathetic. And we can do it by adopting two goals: Becoming naturally curious. Listening more, judging less
There are four collaborative skills for you to consider that are particularly powerful: Ask for small favors. Ask for advice. Give honest encouragement. Think outside the silo.
People who are skilled at seeing commonalities instead of differences also find it easier to relate to people of different backgrounds, experiences, ages, and seniority. Adopting a commonality-based point of view is easy, so long as you’re willing to make the effort. That process begins with these techniques: Make the choice to emphasize similarities. Practice seeing shared traits. Call out points of agreement. If your default position is to see other people as more or less the same as you, that will help bring people to your side.
It follows, then, that from the standpoint of persuasion, the best way to approach any project, large or small, is to see it in terms of the skills required to perform it well—and to commit to developing and improving those skills. This is skill-hunting in a nutshell. And it strikes an important balance between life-hacking and the masochistic “more is more is more” work philosophy that many blindly subscribe to. You can make the shift to this skill-based approach by: Deliberate practice The two-year skill hunt Passions, not hobbies Quality over quantity Straight facts Over time, the high standards and commitment to quality you display will come to define you in the eyes of others.
Of all the ways of persuading another person to action, inspiration is without a doubt the most profound, and in a lot of cases the most powerful. If you can be a source of inspiration for others, you’ll rarely struggle to have your opinions taken seriously. Your views will carry the weight of authority. And people will go out of their way to grant your requests. You will have achieved a kind of influence that goes far beyond salesmanship or rhetoric or bargaining. It is a persuasive power that comes directly from your soul. Becoming a source of inspiration is a challenging, lifelong project. It involves constantly striving to act in accordance with your principles. Perhaps most important, inspirational figures have a highly developed capacity to resist the bystander effect and break away from the pack when their values demand action. The most inspirational people: Preach less and practice more Use their powers for good Seek out causes that advance their values Reach out to their heroes
What I got out of it
Win/Win, respect people, listen, others-focus, be deserving and trustworthy,
The many ways that data and statistics can be manipulated depending on the story the author wants to tell and how to guard against this chicanery
So it is with much that you read and hear. Averages and relationships and trends and graphs are not always what they seem. There may be more in them than meets the eye, and there may be a good deal less. The secret language of statistics, so appealing in a fact-minded culture, is employed to sensationalize, inflate, confuse, and oversimplify. Statistical methods and statistical terms are necessary in reporting the mass data of social and economic trends, business conditions, “opinion” polls, the census. But without writers who use the words with honesty and understanding and readers who know what they mean, the result can only be semantic nonsense.
This book is a sort of primer in ways to use statistics to deceive. It may seem altogether too much like a manual for swindlers.
The fact is that, despite its mathematical base, statistics is as much an art as it is a science. A great many manipulations and even distortions are possible within the bounds of propriety.
Not all the statistical information that you may come upon can be tested with the sureness of chemical analysis or of what goes on in an assayer’s laboratory. But you can prod the stuff with five simple questions, and by finding the answers avoid learning a remarkable lot that isn’t so. Who Says So?
How Does He Know?
Did Somebody Change the Subject?
It is sad truth that conclusions from such samples, biased or too small or both, lie behind much of what we read or think we know.
A river cannot, we are told, rise above its source. Well, it can seem to if there is a pumping station concealed somewhere about. It is equally true that the result of a sampling study is no better than the sample it is based on. By the time the data have been filtered through layers of statistical manipulation and reduced to a decimal-pointed average, the result begins to take on an aura of conviction that a closer look at the sampling would deny. To be worth much, a report based on sampling must use a representative sample, which is one from which every source of bias has been removed. The test of the random sample is this: Does every name or thing in the whole group have an equal chance to be in the sample? The purely random sample is the only kind that can be examined with entire confidence by means of statistical theory, but there is one thing wrong with it. It is so difficult and expensive to obtain for many uses that sheer cost eliminates it. A more economical substitute, which is almost universally used in such fields as opinion polling and market research, is called stratified random sampling.
The importance of using a small group is this: With a large group any difference produced by chance is likely to be a small one and unworthy of big type. A two-peracent-improvement claim is not going to sell much tooth-paste.
The point is that when there are many reasonable explanations you are hardly entitled to pick one that suits your taste and insist on it. But many people do.
When you are told that something is an average you still don’t know very much about it unless you can find out which of the common kinds of average it is—mean, median, or mode. So when you see an average-pay figure, first ask: Average of what? Who’s included?
Only when there is a substantial number of trials involved is the law of averages a useful description or prediction.
If the source of your information gives you also the degree of significance, you’ll have a better idea of where you stand. This degree of significance is most simply expressed as a probability,
Comparisons between figures with small differences are meaningless. You must always keep that plus-or-minus in mind, even (or especially) when it is not stated.
In the end it was found that if you wanted to know what certain people read it was no use asking them. You could learn a good deal more by going to their houses and saying you wanted to buy old magazines and what could be had?
To say “almost one and one-half” and to be heard as “three”—that’s what the one-dimensional picture can accomplish.
If you can’t prove what you want to prove, demonstrate something else and pretend that they are the same thing. In the daze that follows the collision of statistics with the human mind, hardly anybody will notice the difference. The semiattached figure is a device guaranteed to stand you in good stead. It always has.
More people were killed by airplanes last year than in 1910. Therefore modern planes are more dangerous? Nonsense. There are hundreds of times more people flying now, that’s all.
The fallacy is an ancient one that, however, has a powerful tendency to crop up in statistical material, where it is disguised by a welter of impressive figures. It is the one that says that if B follows A, then A has caused B.
Percentages offer a fertile field for confusion. And like the ever-impressive decimal they can lend an aura of precision to the inexact.
It is the illusion of the shifting base that accounts for the trickiness of adding discounts. When a hardware jobber offers “50% and 20% off list,” he doesn’t mean a seventy percent discount. The cut is sixty percent since the twenty percent is figured on the smaller base left after taking off fifty percent.
Author Louis Bromfield is said to have a stock reply to critical correspondents when his mail becomes too heavy for individual attention. Without conceding anything and without encouraging further correspondence, it still satisfies almost everyone. The key sentence: “There may be something in what you say.”
What I got out of it
Written decades ago but even more important today than in the past
Taleb discusses why skin in the game is so important and drives much of human behavior. “Skin in the Game is about four topics in one: a) uncertainty and the reliability of knowledge (both practical and scientific, assuming there is a difference), or in less polite words bull***t detection, b) symmetry in human affairs, that is, fairness, justice, responsibility, and reciprocity, c) information sharing in transactions, and d) rationality in complex systems and in the real world. That these four cannot be disentangled is something that is obvious when one has…skin in the game.* It is not just that skin in the game is necessary for fairness, commercial efficiency, and risk management: skin in the game is necessary to understand the world.”
Skin in the Game
Do not mistake skin in the game as defined here and used in this book for just an incentive problem, just having a share of the benefits (as it is commonly understood in finance). No. It is about symmetry, more like having a share of the harm, paying a penalty if something goes wrong. The very same idea ties together notions of incentives, used car buying, ethics, contract theory, learning (real life vs. academia), Kantian imperative, municipal power, risk science, contact between intellectuals and reality, the accountability of bureaucrats, probabilistic social justice, option theory, upright behavior, bull***t vendors, theology…I stop for now.
definition, what works cannot be irrational; about every single person I know who has chronically failed in business shares that mental block, the failure to realize that if something stupid works (and makes money), it cannot be stupid.
Now skin in the game brings simplicity—the disarming simplicity of things properly done. People who see complicated solutions do not have an incentive to implement simplified ones.
System that doesn’t have a mechanism of skin in the game, with a buildup of imbalances, will eventually blow up and self-repair that way. If it survives.
We saw that interventionistas don’t learn because they are not the victims of their mistakes, and, as we hinted at with pathemata mathemata: The same mechanism of transferring risk also impedes learning. More practically, You will never fully convince someone that he is wrong; only reality can.
Evolution can only happen if risk of extinction is present. Further, There is no evolution without skin in the game. This last point is quite obvious, but I keep seeing academics with no skin in the game defend evolution while at the same time rejecting skin in the game and risk sharing.
It is much more immoral to claim virtue without fully living with its direct consequences. This will be the main topic of this chapter: exploiting virtue for image, personal gain, careers, social status, these kinds of things—and by personal gain I mean anything that does not share the downside of a negative action.
No muscles without strength, friendship without trust, opinion without consequence, change without aesthetics, age without values, life without effort, water without thirst, food without nourishment, love without sacrifice, power without fairness, facts without rigor, statistics without logic, mathematics without proof, teaching without experience, politeness without warmth, values without embodiment, degrees without erudition, militarism without fortitude, progress without civilization, friendship without investment, virtue without risk, probability without ergodicity, wealth without exposure, complication without depth, fluency without content, decision without asymmetry, science without skepticism, religion without tolerance, and, most of all: nothing without skin in the game.
Systems learn by removing parts, via negativa.
Via negativa: the principle that we know what is wrong with more clarity than what is right, and that knowledge grows by subtraction. Also, it is easier to know that something is wrong than to find the fix. Actions that remove are more robust than those that add because addition may have unseen, complicated feedback loops.
The more robust Silver Rule says Do not treat others the way you would not like them to treat you. More robust? How? Why is the Silver Rule more robust? First, it tells you to mind your own business and not decide what is “good” for others. We know with much more clarity what is bad than what is good.
The idea is fractal, in the sense that it works at all scales: humans, tribes, societies, groups of societies, countries, etc., assuming each one is a separate standalone unit and can deal with other counterparts as such. Just as individuals should treat others the way they would like to be treated (or avoid being mistreated), families as units should treat other families in the same way.
Immanuel Kant’s categorical imperative, which I summarize as: Behave as if your action can be generalized to the behavior of everyone in all places, under all conditions.
The principle of intervention, like that of healers, is first do no harm (primum non nocere); even more, we will argue, those who don’t take risks should never be involved in making decisions.
Via Negativa: in theology and philosophy, the focus on what something is not, an indirect definition, deemed less prone to fallacies than via positiva. In action, it is a recipe for what to avoid, what not to do—subtraction, not addition, works better in domains with multiplicative and unpredictable side effects. In medicine, stopping someone from smoking has fewer adverse effects than giving pills and treatments.
Anything you do to optimize your work, cut some corners, or squeeze more “efficiency” out of it (and out of your life) will eventually make you dislike it. Artisans have their soul in the game.
Primo, artisans do things for existential reasons first, financial and commercial ones later. Their decision making is never fully financial, but it remains financial. Secundo, they have some type of “art” in their profession; they stay away from most aspects of industrialization; they combine art and business. Tertio, they put some soul in their work: they would not sell something defective or even of compromised quality because it hurts their pride. Finally, they have sacred taboos, things they would not do even if it markedly increased profitability. Compendiaria res improbitas, virtusque tarda—the villainous takes the short road, virtue the longer one. In other words, cutting corners is dishonest.
Now, something very practical. One of the best pieces of advice I have ever received was the recommendation by a very successful (and happy) older entrepreneur, Yossi Vardi, to have no assistant. The mere presence of an assistant suspends your natural filtering—and its absence forces you to do only things you enjoy, and progressively steer your life that way. (By assistant here I exclude someone hired for a specific task, such as grading papers, helping with accounting, or watering plants; just some guardian angel overseeing all your activities). This is a via negativa approach: you want maximal free time, not maximal activity, and you can assess your own “success” according to such metric. Otherwise, you end up assisting your assistants, or being forced to “explain” how to do things, which requires more mental effort than doing the thing itself. In fact, beyond my writing and research life, this has proved to be great financial advice as I am freer, more nimble, and have a very high benchmark for doing something, while my peers have their days filled with unnecessary “meetings” and unnecessary correspondence. Having an assistant (except for the strictly necessary) removes your soul from the game.
The skills at making things diverge from those at selling things.
“What is hateful to you, do not do to your fellow: this is the whole Torah; the rest is the explanation; go and learn.” Rabbi Hillel the Elder drawing on Leviticus 19:18.
Simply: if you can’t put your soul into something, give it up and leave that stuff to someone else.
I have learned a lesson from my own naive experiences: Beware of the person who gives advice, telling you that a certain action on your part is “good for you” while it is also good for him, while the harm to you doesn’t directly affect him. Of course such advice is usually unsolicited. The asymmetry is when said advice applies to you but not to him
So, “giving advice” as a sales pitch is fundamentally unethical—selling cannot be deemed advice. We can safely settle on that. You can give advice, or you can sell (by advertising the quality of the product), and the two need to be kept separate.
Diogenes held that the seller ought to disclose as much as civil law requires. As for Antipater, he believed that everything ought to be disclosed—beyond the law—so that there was nothing that the seller knew that the buyer didn’t know. Clearly Antipater’s position is more robust—robust being invariant to time, place, situation, and color of the eyes of the participants. Take for now that The ethical is always more robust than the legal. Over time, it is the legal that should converge to the ethical, never the reverse. Hence: Laws come and go; ethics stay.
Avoid taking advice from someone who gives advice for a living, unless there is a penalty for their advice.
Things designed by people without skin in the game tend to grow in complication (before their final collapse).
There is absolutely no benefit for someone in such a position to propose something simple: when you are rewarded for perception, not results, you need to show sophistication.
Scaling & Complexity
Things don’t “scale” and generalize, which is why I have trouble with intellectuals talking about abstract notions. A country is not a large city, a city is not a large family, and, sorry, the world is not a large village.
Today’s Roma people (aka Gypsies) have tons of strict rules of behavior toward Gypsies, and others toward the unclean non-Gypsies called payos. And, as the anthropologist David Graeber has observed, even the investment bank Goldman Sachs, known for its aggressive cupidity, acts like a communist community from within, thanks to the partnership system of governance. So we exercise our ethical rules, but there is a limit—from scaling—beyond which the rules cease to apply. It is unfortunate, but the general kills the particular.
Scaling matters, I will keep repeating until I get hoarse. Putting Shiites, Christians, and Sunnis in one pot and asking them to sing “Kumbaya” around the campfire while holding hands in the name of unity and fraternity of mankind has failed.
And that is what plagues socialism: people’s individual interests do not quite work well under collectivism.
Groups behave differently at a different scale. This explains why the municipal is different from the national. It also explains how tribes operate: you are part of a specific group that is larger than the narrow you, but narrower than humanity in general. Critically, people share some things but not others within a specified group. And there is a protocol for dealing with the outside.
A saying by the brothers Geoff and Vince Graham summarizes the ludicrousness of scale-free political universalism. I am, at the Fed level, libertarian; at the state level, Republican; at the local level, Democrat; and at the family and friends level, a socialist.
The main idea behind complex systems is that the ensemble behaves in ways not predicted by its components. The interactions matter more than the nature of the units. Studying individual ants will almost never give us a clear indication of how the ant colony operates. For that, one needs to understand an ant colony as an ant colony, no less, no more, not a collection of ants. This is called an “emergent” property of the whole, by which parts and whole differ because what matters are the interactions between such parts. And interactions can obey very simple rules.
Human nature is not defined outside of transactions involving other humans. Remember that we do not live alone, but in packs, and almost nothing of relevance concerns a person in isolation—which is what is typically done in laboratory-style works.
Groups are units on their own. There are qualitative differences between a group of ten and a group of, say, 395,435. Each is a different animal, in the literal sense, as different as a book is from an office building. When we focus on commonalities, we get confused, but, at a certain scale, things become different. Mathematically different. The higher the dimension, in other words, the higher the number of possible interactions, and the more disproportionally difficult it is to understand the macro from the micro, the general from the simple units. This disproportionate increase of computational demands is called the curse of dimensionality.
Understanding how the subparts of the brain (say, neurons) work will never allow us to understand how the brain works.
The underlying structure of reality matters much more than the participants,
Volatile things are not necessarily risky, and the reverse is also true. Jumping from a bench would be good for you and your bones, while falling from the twenty-second floor will never be so.
Antifragile has been about the failure of the average to represent anything in the presence of nonlinearities and asymmetries similar to the minority rule. So let us go beyond: The average behavior of the market participant will not allow us to understand the general behavior of the market.
What matters isn’t what a person has or doesn’t have; it is what he or she is afraid of losing. The more you have to lose, the more fragile you are.
Statistics isn’t about data but distillation, rigor, and avoiding being fooled by randomness
Now, crucially, time is equivalent to disorder, and resistance to the ravages of time, that is, what we gloriously call survival, is the ability to handle disorder. That which is fragile has an asymmetric response to volatility and other stressors, that is, will experience more harm than benefit from it. In probability, volatility and time are the same. The idea of fragility helped put some rigor around the notion that the only effective judge of things is time—by things we mean ideas, people, intellectual productions, car models, scientific theories, books, etc. You can’t fool Lindy: For time operates through skin in the game. Things that have survived are hinting to us ex post that they have some robustness—conditional on their being exposed to harm. For without skin in the game, via exposure to reality, the mechanism of fragility is disrupted: things may survive for no reason for a while, at some scale, then ultimately collapse, causing a lot of collateral harm.
Alfonso X of Spain, nicknamed El Sabio, “the wise,” had as a maxim: Burn old logs. Drink old wine. Read old books. Keep old friends. The insightful and luckily nonacademic historian Tom Holland once commented: “The thing I most admire about the Romans was the utter contempt they were capable of showing the cult of youth.” He also wrote: “The Romans judged their political system by asking not whether it made sense but whether it worked,” which is why, while dedicating this book, I called Ron Paul a Roman among Greeks.
Macroeconomics, for instance, can be nonsense since it is easier to macrobull***t than microbull***t—nobody can tell if a theory really works.
Theory vs. Practice
People can detect the difference between front- and back-office operators.
We are much better at doing than understanding.
Before we end, take some Fat Tony wisdom: always do more than you talk. And precede talk with action. For it will always remain that action without talk supersedes talk without action.
If your private life conflicts with your intellectual opinion, it cancels your intellectual ideas, not your private life. And a solution to the vapid universalism we discussed in the Prologue: If your private actions do not generalize, then you cannot have general ideas.
Rationality resides in what you do, not in what you think or in what you “believe” (skin in the game), and b) rationality is about survival.
Your eyes are not sensors designed to capture the electromagnetic spectrum. Their job description is not to produce the most accurate scientific representation of reality; rather the most useful one for survival.
Survival comes first, truth, understanding, and science later.
Or as per the expression attributed to Hobbes: Primum vivere, deinde philosophari (First, live; then philosophize). This logical precedence is well understood by traders and people in the real world, as per the Warren Buffett truism “to make money you must first survive”—skin in the game again; those of us who take risks have their priorities firmer than vague textbook pseudo-rationalism.
The axiom of revelation of preferences (originating with Paul Samuelson, or possibly the Semitic gods), as you recall, states the following: you will not have an idea about what people really think, what predicts people’s actions, merely by asking them—they themselves don’t necessarily know. What matters, in the end, is what they pay for goods, not what they say they “think” about them, or the various possible reasons they give you or themselves for that. If you think about it, you will see that this is a reformulation of skin in the game.
It is therefore my opinion that religion exists to enforce tail risk management across generations, as its binary and unconditional rules are easy to teach and enforce. We have survived in spite of tail risks; our survival cannot be that random.
How much you truly “believe” in something can be manifested only through what you are willing to risk for it.
Risk and ruin are different tings. In a strategy that entails ruin, benefits never offset risks of ruin.
Ergodicity holds when a collection of players have the same statistical properties (particularly expectation) as a single player over time. Ensemble probabilities are similar to time probabilities. Absence of ergodicity makes the risk properties not directly transferable from observed probability to the payoff of a strategy subjected to ruin (or any absorbing barrier or “uncle point”)—in other words, not probabilistically sustainable. Mediocristan:
The fat tails argument: The more a system is capable of delivering large deviations, the worse under the axiom of sustainability, i.e., that “one should take risks as if you were going to do it forever,” only a logarithmic (or similar) transformation
Even if their forecasts were true (they aren’t), no individual can get the same returns as the market unless he has infinite pockets and no uncle points. This is conflating ensemble probability and time probability. If the investor has to eventually reduce his exposure because of losses, or because of retirement, or because he got divorced to marry his neighbor’s wife, or because he suddenly developed a heroin addiction after his hospitalization for appendicitis, or because he changed his mind about life, his returns will be divorced from those of the market, period. Anyone who has survived in the risk-taking business more than a few years has some version of our by now familiar principle that “in order to succeed, you must first survive.” My own has been: “never cross a river if it is on average four feet deep.” I effectively organized all my life around the point that sequence matters and the presence of ruin disqualifies cost-benefit analyses; but it never hit me that the flaw in decision theory was so deep. Until out of nowhere came a paper by the physicist Ole Peters, working with the great Murray Gell-Mann. They presented a version of the difference between ensemble and time probabilities with a thought experiment similar to mine above, and showed that just about everything in social science having to do with probability is flawed. Deeply flawed. Very deeply flawed. Largely, terminally flawed. For, in the quarter millennia since an initial formulation of decision making under uncertainty by the mathematician Jacob Bernoulli, one that has since become standard, almost all people involved in the field have made the severe mistake of missing the effect of the difference between ensemble and time.*1 Everyone? Not quite: every economist maybe, but not everyone: the applied mathematicians Claude Shannon and Ed Thorp, and the physicist J. L. Kelly of the Kelly Criterion got it right. They also got it in a very simple way. The father of insurance mathematics, the Swedish applied mathematician Harald Cramér, also got the point. And, more than two decades ago, practitioners such as Mark Spitznagel and myself built our entire business careers around it. (I mysteriously got it right in my writings and when I traded and made decisions, and detect deep inside when ergodicity is violated, but I never explicitly got Peters and Gell-Mann’s mathematical structure—ergodicity is even discussed in Fooled by Randomness, two decades ago). Spitznagel and I even started an entire business to help investors eliminate uncle points so they could get the returns of the market. While I retired to do some flaneuring, Mark continued relentlessly (and successfully) at his Universa. Mark and I have been frustrated by economists who, not getting ergodicity, keep saying that worrying about the tails is “irrational.”
A situation is deemed non-ergodic when observed past probabilities do not apply to future processes. There is a “stop” somewhere, an absorbing barrier that prevents people with skin in the game from emerging from it—and to which the system will invariably tend. Let us call these situations “ruin,” as there is no reversibility away from the condition. The central problem is that if there is a possibility of ruin, cost-benefit analyses are no longer possible.
If you incur a tiny probability of ruin as a “one-off” risk, survive it, then do it again (another “one-off” deal), you will eventually go bust with a probability of one hundred percent. Confusion arises because it may seem that if the “one-off” risk is reasonable, then an additional one is also reasonable. This can be quantified by recognizing that the probability of ruin approaches 1 as the number of exposures to individually small risks, say one in ten thousand, increases.
Another common error in the psychology literature concerns what is called “mental accounting.” The Thorp, Kelly, and Shannon school of information theory requires that, for an investment strategy to be ergodic and eventually capture the return of the market, agents increase their risks as they are winning, but contract after losses, a technique called “playing with the house money.” In practice, it is done by threshold,
Let us return to the notion of “tribe.” One of the defects modern education and thinking introduces is the illusion that each one of us is a single unit. Thus, we see the point that individual ruin is not as big a deal as collective ruin. To use the ergodic framework: my death at Russian roulette is not ergodic for me but it is ergodic for the system.
Every single risk you take adds up to reduce your life expectancy. Finally: Rationality is avoidance of systemic ruin.
One debases a principle by endlessly justifying it.
We retain from this first vignette that, just like Antaeus, you cannot separate knowledge from contact with the ground. Actually, you cannot separate anything from contact with the ground. And the contact with the real world is done via skin in the game—having an exposure to the real world, and paying a price for its consequences, good or bad. The abrasions of your skin guide your learning and discovery, a mechanism of organic signaling, what the Greeks called pathemata mathemata (“guide your learning through pain,” something mothers of young children know rather well).
The knowledge we get by tinkering, via trial and error, experience, and the workings of time, in other words, contact with the earth, is vastly superior to that obtained through reasoning, something self-serving institutions have been very busy hiding from us.
Rent-seeking is trying to use protective regulations or “rights” to derive income without adding anything to economic activity, not increasing the wealth of others.
It is a filtering, nonsense-expurgating mechanism. I have no sympathy for moaning professional researchers. I for my part spent twenty-three years in a full-time, highly demanding, extremely stressful profession while studying, researching, and writing my first three books at night; it lowered (in fact, eliminated) my tolerance for career-building research.
Same with real estate: most people, I am convinced, are happier in close quarters, in a real barrio-style neighborhood, where they can feel human warmth and company. But when they have big bucks they end up pressured to move into outsized, impersonal, and silent mansions, far away from neighbors. On late afternoons, the silence of these large galleries has a funereal feel to it, but without the soothing music. This is something historically rare: in the past, large mansions were teeming with servants, head-servants, butlers, cooks, assistants, maids, private tutors, impoverished cousins, horse grooms, even personal musicians. And nobody today will come to console you for having a mansion—few will realize that it is quite sad to be there on Sunday evening.
If anything, being rich you need to hide your money if you want to have what I call friends. This may be known; what is less obvious is that you may also need to hide your erudition and learning. People can only be social friends if they don’t try to upstage or outsmart one another. Indeed, the classical art of conversation is to avoid any imbalance, as in Baldassare Castiglione’s Book of the Courtier: people need to be equal, at least for the purpose of the conversation, otherwise it fails.
This reasoning shows that sophistication can, at some level, cause degradation, what economists call “negative utility.” This tells us something about wealth and the growth of gross domestic product in society; it shows the presence of an inverted U curve with a level beyond which you get incremental harm. It is detectable only if you get rid of constructed preferences.
We used to live in small communities; our reputations were directly determined by what we did—we were watched. Today, anonymity brings out the a**hole in people. So I accidentally discovered a way to change the behavior of unethical and abusive persons without verbal threat. Take their pictures. Just the act of taking their pictures is similar to holding their lives in your hands and controlling their future behavior thanks to your silence. They don’t know what you can do with it, and will live in a state of uncertainty.
As far as I know, we only have one planet. So the burden is on those who pollute—or who introduce new substances in larger than usual quantities—to show a lack of tail risk. In fact, the more uncertainty about the models, the more conservative one should be. The same newspapers had lauded
So true virtue lies mostly in also being nice to those who are neglected by others, the less obvious cases, those people the grand charity business tends to miss. Or people who have no friends and would like someone once in while to just call them for a chat or a cup of fresh roasted Italian-style coffee.
Courage is the only virtue you cannot fake.
Finally, when young people who “want to help mankind” come to me asking, “What should I do? I want to reduce poverty, save the world,” and similar noble aspirations at the macro-level, my suggestion is: 1) Never engage in virtue signaling; 2) Never engage in rent-seeking; 3) You must start a business. Put yourself on the line, start a business. Yes, take risk, and if you get rich (which is optional), spend your money generously on others. We need people to take (bounded) risks. The entire idea is to move the descendants of Homo sapiens away from the macro, away from abstract universal aims, away from the kind of social engineering that brings tail risks to society. Doing business will always help (because it brings about economic activity without large-scale risky changes in the economy); institutions (like the aid industry) may help, but they are equally likely to harm (I am being optimistic; I am certain that except for a few most do end up harming). Courage (risk taking) is the highest virtue. We need entrepreneurs.
History is largely peace punctuated by wars, rather than wars punctuated by peace. The problem is that we humans are prone to the availability heuristic, by which the salient is mistaken for the statistical, and the conspicuous and emotional effect of an event makes us think it is occurring more regularly than in reality. This helps us to be prudent and careful in daily life, forcing us to add an extra layer of protection, but it does not help with scholarship.
My lifetime motto is that mathematicians think in (well, precisely defined and mapped) objects and relations, jurists and legal thinkers in constructs, logicians in maximally abstract operators, and…fools in words.
As Gibbon wrote: The various modes of worship, which prevailed in the Roman world, were all considered by the people, as equally true; by the philosopher, as equally false; and by the magistrate, as equally useful. And thus toleration produced not only mutual indulgence, but even religious concord.
The main theological flaw in Pascal’s wager is that belief cannot be a free option. It entails a symmetry between what you pay and what you receive.
Love without sacrifice is theft (Procrustes). This applies to any form of love, particularly the love of God.
Simon formulated the notion now known as bounded rationality: we cannot possibly measure and assess everything as if we were a computer; we therefore produce, under evolutionary pressures, some shortcuts and distortions. Our knowledge of the world is fundamentally incomplete, so we need to avoid getting into unanticipated trouble. And even if our knowledge of the world were complete, it would still be computationally near-impossible to produce a precise, unbiased understanding of reality.
The only definition of rationality that I’ve found that is practically, empirically, and mathematically rigorous is the following: what is rational is that which allows for survival. Unlike modern theories by psychosophasters, it maps to the classical way of thinking. Anything that hinders one’s survival at an individual, collective, tribal, or general level is, to me, irrational. Hence the precautionary principle and sound risk understanding.
Courage is when you sacrifice your own well-being for the sake of the survival of a layer higher than yours. Selfish courage is not courage. A foolish gambler is not committing an act of courage, especially if he is risking other people’s funds or has a family to feed.
Never compare a multiplicative, systemic, and fat-tailed risk to a non-multiplicative, idiosyncratic, and thin-tailed one.
Even economics is based on the notion of “revealed preferences.” What people “think” is not relevant—you want to avoid entering the mushy-soft and self-looping discipline of psychology. People’s “explanations” for what they do are just words, stories they tell themselves, not the business of proper science. What they do, on the other hand, is tangible and measurable and that’s what we should focus on.
What I got out of it
Skin in the game is sharing in the outcomes and helps align behavior and incentives, mitigate principal/agent problems, and more. One of my favorite books of the year