Recently, Bic launched a campaign to “save handwriting.” Named “Fight for Your Write,” it includes a pledge to “encourage the act of handwriting” in the pledge-taker’s home and community, and emphasizes putting more of the company’s ballpoints into classrooms.
As a teacher, I couldn’t help but wonder how anyone could think there’s a shortage. I find ballpoint pens all over the place: on classroom floors, behind desks. Dozens of castaways collect in cups on every teacher’s desk. They’re so ubiquitous that the word “ballpoint” is rarely used; they’re just “pens.” But despite its popularity, the ballpoint pen is relatively new in the history of handwriting, and its influence on popular handwriting is more complicated than the Bic campaign would imply.
The creation story of the ballpoint pen tends to highlight a few key individuals, most notably the Hungarian journalist László Bíró, who is credited with inventing it. But as with most stories of individual genius, this take obscures a much longer history of iterative engineering and marketing successes. In fact, Bíró wasn’t the first to develop the idea: The ballpoint pen was originally patented in 1888 by an American leather tanner named John Loud, but his idea never went any further. Over the next few decades, dozens of other patents were issued for pens that used a ballpoint tip of some kind, but none of them made it to market.
These early pens failed not in their mechanical design, but in their choice of ink. The ink used in a fountain pen, the ballpoint’s predecessor, is thinner to facilitate better flow through the nib—but put that thinner ink inside a ballpoint pen, and you’ll end up with a leaky mess. Ink is where László Bíró, working with his chemist brother György, made the crucial changes: They experimented with thicker, quick-drying inks, starting with the ink used in newsprint presses. Eventually, they refined both the ink and the ball-tip design to create a pen that didn’t leak badly. (This was an era in which a pen could be a huge hit because it only leaked ink sometimes.)
The Bírós lived in a troubled time, however. The Hungarian author Gyoergy Moldova writes in his book Ballpoint about László’s flight from Europe to Argentina to avoid Nazi persecution. While his business deals in Europe were in disarray, he patented the design in Argentina in 1943 and began production. His big break came later that year, when the British Air Force, in search of a pen that would work at high altitudes, purchased 30,000 of them. Soon, patents were filed and sold to various companies in Europe and North America, and the ballpoint pen began to spread across the world.
The ballpoint’s universal success has changed how most people experience ink.
Businessmen made significant fortunes by purchasing the rights to manufacture the ballpoint pen in their country, but one is especially noteworthy: Marcel Bich, the man who bought the patent rights in France. Bich didn’t just profit from the ballpoint; he won the race to make it cheap. When it first hit the market in 1946, a ballpoint pen sold for around $10, roughly equivalent to $100 today. Competition brought that price steadily down, but Bich’s design drove it into the ground. When the Bic Cristal hit American markets in 1959, the price was down to 19 cents a pen. Today the Cristal sells for about the same amount, despite inflation.
The ballpoint’s universal success has changed how most people experience ink. Its thicker ink was less likely to leak than that of its predecessors. For most purposes, this was a win—no more ink-stained shirts, no need for those stereotypically geeky pocket protectors. However, thicker ink also changes the physical experience of writing, not necessarily all for the better.
I wouldn’t have noticed the difference if it weren’t for my affection for unusual pens, which brought me to my first good fountain pen. A lifetime writing with the ballpoint and minor variations on the concept (gel pens, rollerballs) left me unprepared for how completely different a fountain pen would feel. Its thin ink immediately leaves a mark on paper with even the slightest, pressure-free touch to the surface. My writing suddenly grew extra lines, appearing between what used to be separate pen strokes. My hand, trained by the ballpoint, expected that lessening the pressure from the pen was enough to stop writing, but I found I had to lift it clear off the paper entirely. Once I started to adjust to this change, however, it felt like a godsend; a less-firm press on the page also meant less strain on my hand.
My fountain pen is a modern one, and probably not a great representation of the typical pens of the 1940s—but it still has some of the troubles that plagued the fountain pens and quills of old. I have to be careful where I rest my hand on the paper, or risk smudging my last still-wet line into an illegible blur. And since the thin ink flows more quickly, I have to refill the pen frequently. The ballpoint solved these problems, giving writers a long-lasting pen and a smudge-free paper for the low cost of some extra hand pressure.
As a teacher whose kids are usually working with numbers and computers, handwriting isn’t as immediate a concern to me as it is to many of my colleagues. But every so often I come across another story about the decline of handwriting. Inevitably, these articlesfocus on how writing has been supplanted by newer, digital forms of communication—typing, texting, Facebook, Snapchat. They discuss the loss of class time for handwriting practice that is instead devoted to typing lessons. Last year, a New York Timesarticle—one that’s since been highlighted by the Bic’s “Fight for your Write” campaign—brought up an fMRI study suggesting that writing by hand may be better for kids’ learning than using a computer.
I can’t recall the last time I saw students passing actual paper notes in class, but I clearly remember students checking their phones (recently and often). In his history of handwriting, The Missing Ink, the author Philip Hensher recalls the moment he realized that he had no idea what his good friend’s handwriting looked like. “It never struck me as strange before… We could have gone on like this forever, hardly noticing that we had no need of handwriting anymore.”
No need of handwriting? Surely there must be some reason I keep finding pens everywhere.
Of course, the meaning of “handwriting” can vary. Handwriting romantics aren’t usually referring to any crude letterform created from pen and ink. They’re picturing the fluid, joined-up letters of the Palmer method, which dominated first- and second-grade pedagogy for much of the 20th century. (Or perhaps they’re longing for a past they never actually experienced, envisioning the sharply angled Spencerian script of the 1800s.) Despite the proliferation of handwriting eulogies, it seems that no one is really arguing against the fact that everyone still writes—we just tend to use unjoined print rather than a fluid Palmerian style, and we use it less often.
Fountain pens want to connect letters. Ballpoint pens need to be convinced to write.
I have mixed feelings about this state of affairs. It pained me when I came across a student who was unable to read script handwriting at all. But my own writing morphed from Palmerian script into mostly print shortly after starting college. Like most gradual changes of habit, I can’t recall exactly why this happened, although I remember the change occurred at a time when I regularly had to copy down reams of notes for mathematics and engineering lectures.
In her book Teach Yourself Better Handwriting, the handwriting expert and type designer Rosemary Sassoon notes that “most of us need a flexible way of writing—fast, almost a scribble for ourselves to read, and progressively slower and more legible for other purposes.” Comparing unjoined print to joined writing, she points out that “separate letters can seldom be as fast as joined ones.” So if joined handwriting is supposed to be faster, why would I switch away from it at a time when I most needed to write quickly? Given the amount of time I spend on computers, it would be easy for an opinionated observer to count my handwriting as another victim of computer technology. But I knew script, I used it throughout high school, and I shifted away from it during the time when I was writing most.
My experience with fountain pens suggests a new answer. Perhaps it’s not digital technology that hindered my handwriting, but the technology that I was holding as I put pen to paper. Fountain pens want to connect letters. Ballpoint pens need to be convinced to write, need to be pushed into the paper rather than merely touch it. The No.2 pencils I used for math notes weren’t much of a break either, requiring pressure similar to that of a ballpoint pen.
Moreover, digital technology didn’t really take off until the fountain pen had already begin its decline, and the ballpoint its rise. The ballpoint became popular at roughly the same time as mainframe computers. Articles about the decline of handwriting date back to at least the 1960s—long after the typewriter, but a full decade before the rise of the home computer.
Sassoon’s analysis of how we’re taught to hold pens makes a much stronger case for the role of the ballpoint in the decline of cursive. She explains that the type of pen grip taught in contemporary grade school is the same grip that’s been used for generations, long before everyone wrote with ballpoints. However, writing with ballpoints and other modern pens requires that they be placed at a greater, more upright angle to the paper—a position that’s generally uncomfortable with a traditional pen hold. Even before computer keyboards turned so many people into carpal-tunnel sufferers, the ballpoint pen was already straining hands and wrists. Here’s Sassoon:
We must find ways of holding modern pens that will enable us to write without pain. …We also need to encourage efficient letters suited to modern pens. Unless we begin to do something sensible about both letters and penholds we will contribute more to the demise of handwriting than the coming of the computer has done.
I wonder how many other mundane skills, shaped to accommodate outmoded objects, persist beyond their utility. It’s not news to anyone that students used to write with fountain pens, but knowing this isn’t the same as the tactile experience of writing with one. Without that experience, it’s easy to continue past practice without stopping to notice that the action no longer fits the tool. Perhaps “saving handwriting” is less a matter of invoking blind nostalgia and more a process of examining the historical use of ordinary technologies as a way to understand contemporary ones. Otherwise we may not realize which habits are worth passing on, and which are vestiges of circumstances long since past.
Or, better yet, reconsider the trailer park, whose stereotypical association with peeling paint and unemployed seniors is outdated.
The quiet story of trailer parks over the last two decades is their reinvention as “mobile home communities” by investors who saw a lucrative opportunity in providing housing to low-income Americans.
The billionaire investor and real estate mogul Sam Zell recently said of his investment fund that owns mobile home communities—some of which advertise amenities like pools and tennis clubs—that he doesn’t “know of any stock or property I’m involved in that has a better prospect.”
Since 2003, Warren Buffett has owned Clayton Homes, which builds houses destined for trailer parks across the country. At 1400 square feet, many of the homes don’t look like they were delivered on the back of a truck.
Franke Rolfe, a Stanford graduate who teaches people how to profit in the mobile home industry, buys dilapidated trailer parks, cleans them up, and rents mobile homes to the working poor. A 2014 New York Times Magazine article reported that he and a partner earned a 25% return on their investment.
Trailer parks’ appeal to these investors is simple. Millions of Americans struggle with rent payments, but still want a lawn. For them, mobile homes are the cheapest form of housing available. At the same time, it’s rare for someone to build a new mobile home park, because no homeowner wants a trailer park nearby. An industry with healthy demand but a fixed supply attracts the country’s capitalists.
These capitalists realized that trailer parks are an undervalued asset. But maximizing profits at a mobile home park isn’t pretty. It means taking advantage of the lack of supply and the expense of moving a mobile home to raise rents every year. These investors avoid states with rent control, and they’re attuned to just how much a family can pay without becoming insolvent.
But in their pursuit of profit, investors also dramatically increased the stock of well managed, affordable housing. And they’d create a lot more—at better prices—if America’s homeowners weren’t dead set against trailer parks.
Building the Affordable House
During his presidency, Bill Clinton championed efforts to “steadily expand the dream of homeownership to all Americans.” George W. Bush, too, promoted an “ownership society.” Helping Americans to own their homes, he said, would “put light where there’s darkness.”
Neither president could change the reality that many Americans cannot afford a house. The percentage of homeowners increased from 64% to a peak of 69% during their tenures. But the bump relied on no money down mortgages and irresponsible lending—the phenomenon satirized in The Big Short when the character played by Steve Carell tells a stripper in Florida that she really shouldn’t have five home loans. (In real life, it happened in Vegas.) Since the housing bubble burst, the homeownership rate has returned to 64%.
Why can’t we build affordable homes? America is full of gargantuan houses that are customized like each owner is a reality TV contestant. It sure seems like more people could afford homes if we made them smaller and more efficiently.
But according to Witold Rybczynski, an emeritus professor of architecture at the University of Pennsylvania, that is not the case.
An old picture of Levittown, Pennsylvania, which features Levitt and Sons standardized, one-story homes.
Writing in The Wilson Quarterly, Rybczynski cites the famous case of the “Levittowns” built for newly married GIs after World War II. Levitt and Sons constructed houses like Henry Ford built cars. “Teams of workers performed repetitive tasks,” Rybczynski writes, and every house was a one-story with the kitchen and bathroom facing the street to reduce the length of the pipes.
Each “Levittowner” was identical except for its paint job, and thanks to the cold efficiency of the process, they cost $9,900 in the 1950s. That’s around $90,000 in 2016 dollars. A new home today is more than twice as large and sells for $300,000.
So if we made ‘em like we did in the old days, could we slash the price? Rybczynski says no.
The modern McMansion seems like an expensive, bespoke product. But its construction is actually a triumph of industrial efficiency. Windows, doors, and other parts arrive prefabricated, Rybczynski writes, so labor costs have actually halved since 1949. Levitt and Sons spent $4 to $5 per square foot building Levittowners, and, adjusted for inflation, builders today spend the same amount.
Instead the problem is almost wholly that land is too expensive. Reduce the size of a new, modern house by 50%, Rybczynski notes, and houses in metropolitan areas will still cost over $200,000.
That’s the secret to the extreme affordability of a mobile home—take land out of the equation.
The Extreme Profitability of Mobile Homes
Franke Rolfe is the landlord for tens of thousands of people. Along with a business partner and his backers in private equity, he co-owns mobile home communities in 16 states.
But, he explains, “a mobile home park is by definition a parking lot. Legally, our parks are no different from a parking lot by an airport.”
This is why used mobile homes only cost $10,000-$20,000. They make it possible for someone to buy a home but not the earth it’s parked on. As a Times profile of Rolfe reported, his average tenant pays $250 to $300 in monthly rent. If the tenant doesn’t own her home, she might pay another $200 or $300, with the option to apply half of that toward purchasing a mobile home.
“We’re the cheapest form of detached housing there is,” says Rolfe. “You can’t do cheaper.”
Harvard's Joint Center for Housing recently reported that one in five renters earns less than $15,000 a year. For this group, paying more than $400 a month in rent is unaffordable. Especially for a family, finding an apartment is tough, and renting a typical house may be impossible—the Harvard report notes that “single-family homes have among the highest median rents of any type of rental housing.”
Buying a mobile home also compares favorably with a mortgage: According to a 2015 U.S. Census survey, only 3.4% of Americans with a mortgage paid less than $600 in monthly housing costs.
The economics of mobile homes has attracted new residents. When Times reporter Gary Rivlin attended Rolfe’s class on the trailer park industry, which Rolfe calls Mobile Home University, a manager explained that his tenants were once all retirees. But the park was now full of two-income families “making minimum wage at Taco Bell.”
So why do investors like Rolfe and Warren Buffett see gold in these cash-strapped Americans?
When a business makes boatloads of money from poor customers, the answer can be unseemly if not illegal. In the subprime auto loan industry, executives offer low-income Americans car loans with such high fees that 1 in 4 customers default. Hidden fees are common, and when a customer fails to pay, companies still profit by repossessing and re-lending the car. The LA Times found that one Kia Optima was lent out and repossessed eight times in under three years.
Warren Buffett’s mobile home construction business, Clayton Homes, has been accused of using a similar, exploitative business model. According to reporting by the Seattle Times and the Center for Public Integrity, Clayton Homes lent customers money to buy their mobile homes at above-average rates and unexpectedly added fees or changed the terms of the loan. When low income buyers fell behind on their mobile home payments, Clayton Homes profited by repossessing the house and re-selling it.
The situation at mobile home parks like Rolfe’s, however, looks more like the poor’s experience with financial services. Since their meager savings aren’t profitable for banks, they pay for services wealthier Americans get for free: a few dollars to cash a check, a few dollars to send money to an aunt. And since they can’t afford a mortgage, they pay more dearly for the land under their mobile home.
As Rivlin recounts of his time at Rolfe’s Mobile Home University, he learned that “one of the best things about investing in trailer parks is that ambitious landlords can raise the rent year after year without losing tenants. The typical resident is more likely to endure the increase than pay a trucking company the $3,000 it can easily cost to move even a single-wide trailer to another park.” A 30% increase in rent “might sound steep,” but Rolfe says residents “can always pick up extra hours.”
This realization has earned Rolfe, his partners, and his fellow mobile home moguls handsome returns: poor Americans could afford to pay much more for a taste of homeownership.
American Dream; American Reality
Rolfe bought his first trailer park in 1996 from an owner who, he told the Times, “would open the door just wearing his underwear, totally hungover.”
You’ll find more Stanford graduates like Rolfe selling software than mobile homes. But Rolfe saw that the park had unrealized, financial potential. His business partner, Dave Reynolds, had the same epiphany in 1993. This has now become a formula they teach at Mobile Home University: identify promising trailer parks and buy them from their mom-and-pop owners.
But when savvy investors like Rolfe and Reynolds buy a mobile home park, they do not just passively collect rent payments. “The parks they take over tend to be in lousy shape,” Rivlin writes, “and they spend hundreds of thousands of dollars fixing them up.” They also hire tough managers who pay equal attention to keeping the grass mowed and kicking out tenants who break the law.
“There’s more money in decent than slumlording,” Rivlin quotes Rolfe telling a Mobile Home U class. He wants responsible tenants who will see the value in paying increasing rent payments.
A mobile home park In the UK. Copyright Clive Perrin and licensed for reuse.
The result is that their tenants have a safe place to live (and a lawn) at a low price point. Some parks are easily identified by the occasional beat up trailer, but others are easy to mistake for a cookie cutter neighborhood of small to mid-size houses. In his visits to Rolfe’s trailer parks, Rivlin was struck by how many tenants said they were satisfied with the landlord and pleased with their home.
One resident said her only complaint was “the redneck jokes I’ve been hearing since the day I moved in.”
***
The phrase affordable housing evokes New York City’s projects and government subsidies. But as emeritus architecture professor Witold Rybczynski likes to point out, affordable housing “once meant commercially built houses that ordinary working people could afford.”
A profit motive is pushing Franke Rolfe and Dave Reynolds and Sam Zell and private equity partners to invest in turning rundown trailer parks into safe, decent, affordable housing.
It’s not pretty, but it gets results. In the Times, Rivlin noted that as of 2014, Reynolds and Rolfe’s 10,000 mobile home lots made them “about equivalent in size to a public-housing agency in a midsize city.” Sam Zell’s Equity Lifestyle Properties owns around 140,000 lots.
They are responding to an unmet need. Limited government funding for affordable housing means that only one in four eligible households receive assistance. California’s governor has noted that it takes a $5 billion subsidy to provide 100 people with affordable housing in San Francisco, where units are distributed by lottery. And according to a Harvard housing report, public, affordable housing is (on average) in the worst shape of all of the country’s rental properties.
But the market mechanism that drives investors to turn trailer parks into decent, affordable housing is half broken.
One reason Rolfe, Zell, and others invest in mobile home parks is that it’s nearly impossible to build a new one. “Cities fight tooth and nail,” says Rolfe. “In Louisiana, we drew a standing room only crowd [at a public hearing] to fight an expansion of twenty lots to our trailer park.” With residents and city officials blocking construction, investors like Rolfe can raise their tenants’ rents without worrying about a competitor popping up nearby.
Rolfe is the first to say that residents’ concerns about mobile home parks are “valid.” Trailer parks drag down property values, often due to the expectation that they’ll bring crime. (“It would be nice if television showed something positive happening in a mobile home park,” Rolfe says.) Since mobile homes are cheap and taxed like cars, their owners don’t pay much in taxes even as they send their children to the local school.
“From a financial perspective,” says Rolfe, “it’s simple to see why cities don’t want mobile home parks.”
But just because it’s understandable, that doesn’t make it a good idea.
Few Americans would cop to wanting to live in a town without poor people, but that’s the effect of their actions when they oppose a trailer park or dense or affordable housing. And while residents may not want to subsidize newcomers, our tax code is progressive because rich people benefit when their taxes fund the school attended by a poor but brilliant young girl. Saying “not in my backyard” is also the exact reason that land and single-family homes are so expensive in the first place.
California governor Jerry Brown recently proposed legislation that would limit the ability of locals to block the development of new (and denser) housing. But it’s unlikely someone will champion trailer parks—even though they’ll be immediately affordable.
They have good reasons. Unlike a typical house, mobile homes decrease in value over time, so many are worth little once families pay off their loans. Nor does a home offer much security if you can be evicted from the land it sits on. It’s also not good politics to suggest Americans settle for housing that is synonymous with “trailer trash.”
That’s too bad. Clinton and Bush’s dream of every American owning a home ended in tragedy. But driven by profits, trailer park moguls are meeting America’s fast food workers and low-income retirees where they live.
Our next article explores what a baboon massacre at the London Zoo tells us about human nature. To get notified when we post it → join our email list.
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"The problem with Wikipedia is that it only works in practice; in theory it’s a total disaster." Good one :)
Photo via Gareth Owen
Gareth Owen is one of the earliest contributors to Wikipedia—his user ID is 151, and his first edit was to create the “Hobbits” article in March 2001.
He has seen Wikipedia grow “in just a couple of years from a sparse website to something where you could look something up with a reasonable chance of getting a non-terrible response.” As described in his own voice.
Owen, a native of North West England who now lives just outside Manchester in the United Kingdom, has been using the internet when he was a student in the early 90s. He discovered Wikipedia in its earliest days, when the site was just a “silly little spin-off” from a less-collaborative wiki called Nupedia. Owen was most active during Wikipedia’s first few years. Collaborating with people from different places on providing information to the public about topics of interest to him was his motivating force.
“I enjoyed doing research on my favourite topics,” Owen explains. “I enjoyed the collaborative process and watching people devote their time to something really worthwhile—essentially altruistically—and expecting little in return.”
So far, Owen has edited Wikipedia over 6,000 times and has created 113 new articles. He has been most interested in editing articles about music, sports and mathematics, his field of study. He has started some important articles about music, covering bands like The Beatles and The Velvet Underground, and he has rewritten articles about Bob Dylan, Miles Davis, and The Rolling Stones.
“Everything was up for grabs back then and there was so much to be done,” Owen elaborated. “If you started working on an area, you could expand an entry with a few token sentences to something with a larger overview of a big subject. And if you did a good job, Larry Sanger or Jimmy Wales would add your article to the “Brilliant Prose” list, which was a pretty good feeling.”
The Wikipedia quality standards have changed over the years. The “brilliant prose” selection system has since been replaced with new criteria for selecting Wikipedia’s best articles, which are now called “featured articles.” Some of Owen’s articles that were cited in the “brilliant prose” list in the early 2000s now appear as featured articles, thanks to the efforts of other Wikipedians. Some examples include The Beatles, Sandy Koufax and Babe Ruth.
During this time, Wikipedia was very quiet with a minimal rate of spam and edit wars. Owen remembers that “the rate of editing was slow enough that only a few people would keep an eye on anon edits and correct the most egregious damage manually. Jimmy Wales would arbitrate anything that ran on too long. Obviously that didn’t scale very well, and extra layers of administrative oversight came in by the mid-2000s.”
A couple of years ago, Owen and his family were surprised by a show host who quoted Owen on BBC Radio 4. The show had been discussing Wikipedia when the host John Lloyd closed by saying, “In the words of an original Wikipedian, Gareth Owen, ‘The problem with Wikipedia is that it only works in practice; in theory it’s a total disaster.’” The quote has been used several times, including once by the New York Times.
“This remark has cropped up in a number of articles and features (sometimes credited to me, sometimes others). I wonder if in 100 years it’ll be the only trace of me left on the internet.”
Samir Elsharbaty, Digital Content Intern Wikimedia Foundation
“The decade” is a new blog series that profiles Wikipedians who have spent ten years or more editing Wikipedia. If you know of a long-time editor who we should talk to, send us an email at blogteam[at]wikimedia.org.
In 1932, Solly Zuckerman sat down to write a book about a baboon massacre at the London Zoo.
The carnage in question had started seven years earlier when the Zoological Society of London opened a new baboon exhibit. The enclosure, called “Monkey Hill,” was state-of-the-art: an open-air rock cliff with simian-friendly amenities designed to keep the resident primates happy and healthy.
But something had gone terribly wrong.
As soon as the first batch of hamadryas baboons were ushered onto the artificial rock face, war broke out. By the end of the decade, two-thirds had been killed.
The seven-year bloodbath was a hit with the viewing public, and the misdeeds of these murderous monkeys made a splash in papers on both sides of the Atlantic.
For Zuckerman, who dissected and studied animal carcasses at the zoo, the violence provided an important insight into primate behavior. Ape and monkey society is built on violence and sexual dominance, he theorized. Humanity’s closest relatives were creatures of chaos, lust, and slaughter. This insight launched Zuckerman’s career and defined the early scientific field of primatology.
For many, the theory also offered an appealing explanation for human behavior. In political science, psychiatry, and the popular press, the slaughter at Monkey Hill was taken as evidence of the inherent depravity of humanity.
There was just one problem: the science was bunk. Baboons do not routinely butcher one another in the wild, nor do all primates behave like hamadryas baboons.
Primatologists have long since dismissed Zuckerman’s theory of primate behavior. But for decades, the mistaken lessons of Monkey Hill defined primatology, permeated popular culture, and contributed to a widespread view of humanity as a species on the brink of mayhem.
The Benefits of Outdoor Living
Monkey Hill was supposed to save the baboons.
Until the 1920s, the London Zoo housed most of its animals indoors, in the dark, and behind bars. But the sickly, sad-looking creatures depressed the zoo visitors and dropped dead of preventable illnesses at alarming rates. The primates were of particular concern. Pneumonia, tuberculosis, and vitamin-D deficiency were the scourge of the Monkey House.
Taking a cue from German zookeepers, the London Zoological Society designed an outdoor enclosure called Monkey Hill in 1924—a place where primates could roam about and live as if they were in their native habitat. Well, nearly. The zookeepers used shelters, heaters, and UV-lights to combat the perennial gloom of fog-swaddled London.
As science writer Jonathan Burt explains, the open-air exhibit was “intended to showcase the benefits of outdoor living for animal health.” Plus, he adds, from behind the 12-foot outer wall that surrounded the enclosure zoo, visitors were afforded a much better show.
They got one.
In 1925, a shipment of ninety-seven hamadryas baboons arrived by boat from the Horn of Africa. They were all supposed to be male. As Jane Goodall’s biographer Dale Peterson writes, the zoo’s gender preference was “based on the idea that the males—big and dramatically fanged and caped, with pink buttocks—would appeal to a zoo-going public more than the smaller and less gaudy females.” But whether by neglect or indifference, six females were included in the shipment. The result was a bloodbath.
Once the exhibit opened, the males immediately went to war over access to the females. With the former outnumbering the latter 15-to-1, the competition was ferocious. Caught in a constant tug-of-war between dozens of brawny, sharp-fanged males, most of the females were killed over the coming months. Even so, the males fought over their bodies. The violence was sometimes so fierce that zookeepers had to wait days before they could scale Monkey Hill and retrieve a carcass. Within two years, nearly half of the baboons were dead.
But rather than remove the remaining females from the enclosure, the Zoological Society of London thought that they could quell the violence by adding more. Just as the fighting began to simmer down in 1927, the zoo introduced 30 additional females and five adolescent males. The violence exploded anew.
By 1931, 64% of all the males and 92% of the females that had been brought to Monkey Hill had died. While some of the males had died of disease, virtually all of the females died violent deaths. Of the 15 infants born in the enclosure, only one managed to survive.
This all came as a shock to the zookeepers. Instead of a sanctuary, they had inadvertently created a fighting pit—a gladiator arena with sex. And there was a lot of sex. In 1929, one member of the Zoological Society worried that the constant baboon copulation—violent, polygamous, and occasionally necrophilic—would have a “demoralizing” effect on the public.
Just the opposite was true. The sex and violence on Monkey Hill was a draw for zoo visitors. The tabloid press in England took a prurient interest in the sorry state of the females on the hill, with one describing “meek, subdued, tractable creatures” who “live on the leavings and take life sadly.” In 1930, even Time magazine profiled the “wife-stealer” primates at the London Zoo.
The same year, the zoo superintendent finally removed the surviving females. It was a moral choice, but not a shrewd business decision: the violence dropped along with attendance at the exhibit. To at least one tabloid, the conclusion was obvious: “men are a peaceable race, once you eliminate the women.”
This was only the first of many flawed conclusions to be drawn from Monkey Hill.
Red in Claw and Fang
When Solly Zuckerman was hired by the London Zoo to dissect baboon carcasses, he came with experience.
Born in South Africa, where baboons were regarded as a pest, he had spent his teenage years shooting the animals for bounty and dissecting their bodies for fun. This odd adolescent hobby notwithstanding, Zuckerman had very little experience observing how baboon troops behaved in the wild. He wasn’t alone. Very little was known about the social lives of nonhuman primates.
The exhibit at Monkey Hill gave Zuckerman an opportunity to watch a group of monkeys being monkeys. What he saw, both on the hill and the autopsy table, was a revelation. After a few years of observation, lab work, and a short stint in the field back in South Africa, Zuckerman published his grand theory on primate society: The Social Life of Monkeys and Apes.
According to Zuckerman, life in the jungle is nasty, brutish, and short. All “sub-human” primate relationships fit into strict, male-dominated hierarchies that are maintained through coercion, intimidation, and bloodshed. The only thing that prevents the chest-thumping testosterone fest from descending into absolute chaos is the prospect of copulation. Whenever conflict arises within a troop, females offer sex to paper things over. When that fails, the alpha males resort to murder. Such is the way not only of baboons, wrote Zuckerman, but all non-human primates.
Male hamadryas baboons are considerably larger than the females. Photo by Ruben Undheim.
This conclusion was based on his observations at Monkey Hill, but it was also, according to Zuckerman, an inescapable result of primate biological characteristics. Males dominate females because they are bigger, and they keep females as permanent members of their troops because they are fertile year-round. “Reproductive physiology is the fundamental mechanism of society,” he wrote. Violent behavior is baked in.
The Social Life of Monkeys and Apes was published in 1932 (over the objections of the zoo management, who found Zuckerman’s lengthy descriptions of baboon sex unseemly). This Clockwork Orange-view of ape and monkey behavior dominated the field of primatology for the next three decades.
To his credit, Zuckerman was careful to say that his theory only explained non-human primate behavior. But not everyone got the memo. Social theorists, journalists, and the public at large took Monkey Hill and Zuckerman’s grand theory as a description of humanity unencumbered by law and social mores.
In their political tract, Personal Aggressiveness and War, the English politician Evan Durbin and psychologist John Bowlby used the story of Monkey Hill as evidence that human beings had a natural propensity towards war. “Fighting is infectious in the highest degree,” they wrote in 1938. “It is one of the most dangerous parts of our animal inheritance.”
This must have been a compelling conclusion at the time. This was the same year that Germany annexed Austria, laying the groundwork for the Second World War.
In the following decades, scientists came to doubt Zuckerman’s theory. But in popular culture, the idea stuck around.
In 1957, the popular science magazine, New Scientist, wrote the “sadistic society of the totalitarian monkeys” on Monkey Hill and drew a parallel to the mutiny on the Bounty. This was the infamous maritime rebellion in which men, adrift upon the lawless sea, seized the HMS Bounty and settled as outlaws in the South Pacific. Some 30 men took up residence on Pitcairn Island in particular.
“In 10 years all the men had been killed except one,” the article explained. “The principal difference between Pitcairn Island and Monkey Hill seemed to be that the abnormal social conditions resulted more lethally for the males in the human colony and for females in the sub-human colony.”
The public’s infatuation with this theory of the violent primate came at an odd time. As the primatologist Shirley Strum and William Mitchell wrote in the 1980s, “just as specialists were abandoning [Zuckerman’s] baboon model, the popular press and nonspecialists interested in interpreting human evolution adopted and championed that view of primate society.”
These nonspecialists included writers like Robert Ardrey, who began championing the so-called “killer ape theory”—the idea that the evolutionary success of homo sapiens was the result of our inherent aggression. Thus, 2001: A Space Odyssey depicts the “dawn of man” as an early hominid learning how to use a weapon and beat a cow skeleton to bits in a fit of rage.
The idea that the violence at Monkey Hill reflected our natural state contributed not only to a grim view of human nature, but of the natural world as a whole.
“The hamadryas colony at the London Zoo reinforced a widespread belief in an unconstrained Darwinian struggle for existence,” write Carl Sagan and Ann Druyan in their 1993 book, Shadows of Forgotten Ancestors. “Many people felt that they had now glimpsed Nature in the raw, a brutal Nature, red in claw and fang, a Nature from which we humans are insulated and protected by our civilized institutions and sensibilities.”
There but for the grace of God, law, and authority go we to Monkey Hill.
Lab versus Field
But, of course, this was all based on bad science.
As anyone who has watched nature documentaries on bonobos can tell you, not all primates are patriarchal killing machines. And even the male-centric hamadryas baboons only live up to Zuckerman’s hyper-violent description in certain, artificial circumstances.
Circumstances like Monkey Hill.
First, there was the issue of space. A typical troop of 100 baboons in the scrublands of Ethiopia will range over an area of roughly 50,000 square meters. The enclosure at the London Zoo was a little over 500 square meters, nearly one-hundredth the size.
Beyond the crowding, the exhibit’s extreme gender lopsidedness was far from anything that might be observed in the wild. Hamadryas baboons are the only primate species besides gorillas that maintain harems: family units that consist of a single male and up to ten females and infants. These harems form together into clans. Overtime, these clans establish a clear hierarchy of dominance. If that hierarchy is violated, the culprit will be severely punished by the various males.
But the London Zoo had penned nearly one hundred males with no prior social ties together with half a dozen unfortunate females.
In short, trying to generalize about primate behavior based on Monkey HiIll would be like trying to learn about human nature by watching a prison riot.
Still, Zuckerman’s grand theory of primate behavior had staying power because it tapped into a key bias within the biological sciences: work in the lab outranked research in the field.
When other primatologists, like Clarence Ray Carpenter, offered contradictory accounts of monkeys in Panama notably not murdering one another with abandon, much of the research community looked down upon these observations as second-class science. How could observations made by a sweaty, exhausted, mosquito-bitten field worker compare to the conclusions of a sober-minded scientist in the lab?
Solly Zuckerman, 1943.
It wasn’t until the early 1960s that Solly Zuckerman’s theoretical superstructure finally came toppling down.
By then, Zuckerman had been knighted, had served as chief scientific adviser to the Ministry of Defense (alongside primate anatomy, he took an interest in ballistics), and was serving as Secretary of the London Zoological Society.
As an elder zoologist, he was particularly dismissive of a young “amateur” scientist named Jane Goodall. With few credentials to her name, Goodall had spent months observing chimpanzees at Gombe National Park in Tanzania. This was an “act of radical immersion” that was unheard of in the primatology community, writes Goodall’s biographer, Dale Peterson. Returning from East Africa, she published findings in which she observed that chimpanzees, unlike their baboon cousins, did not form harems. More generally, they didn’t seem to behave as the violent patriarches Zuckerman insisted they were.
Though Zuckerman never admitted that he was wrong, in the words of Dale Peterson, this showed that primate life was not solely a “masculine melodrama on the themes of sex and violence.” Through field observations, Goodall and a new generation of primatologists, showed that primate behavior is complex, varied, and heavily influenced by environment. It was, in other words, immune to the sweeping generalizations put forward by Zuckerman.
The end of the Monkey Hill era, writes Peterson, marked “the debut of primatology as a modern science.”
The Moral of Monkey Hill
Humans are suckers for a good animal allegory.
When Ivan Pavlov learned that he could trick his dog into salivating at the sound of a bell, “Pavlov’s dog” became cultural shorthand for the mechanical naiveté of human behavior.
When B.F. Skinner discovered that birds could be taught to bob their heads in a certain way to receive food, “Skinner’s pigeons” likewise became a reference for the universality of human superstition.
And when animal behaviorist John Calhoun created an overpopulated mouse enclosure at the National Institute of Mental Health—and watched as the rodents descended into a “behavioral sink” of asexualism, cannibalism, and violence—John Calhoun’s “rats of NIMH” became a modern parable about overcrowding in urban centers.
As Eric Michael Johnson writes in Scientific American, Monkey Hill is now its own kind of a parable.
The case of Zuckerman and the baboons of London, he writes, is “a zoological case study that reveals the danger of embracing a faulty assumption about ‘natural’ behavior.” The baboons on Monkey Hill were not emblematic of all apes and monkeys. They certainly weren’t emblematic of humans. Trapped, overcrowded, and placed within an unnatural social environment, they weren’t even emblematic of their own species.
If there is a lesson to be learned from the story of Monkey Hill, it is that we are too eager to learn lessons from the animal kingdom.
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As mudanças nos gastos foram bem curiosas, eu diria.
O fim do financiamento empresarial funcionou. Ainda não se conhece o preço total da eleição, porque as prestações de contas definitivas ainda estão por vir, mas as campanhas ficaram mais baratas. Podem ter custado menos da metade, talvez até um terço das de 2012. E isso é bom? Menor a necessidade de pedir dinheiro para empresas, menores as oportunidades para corrupção.
Tirando os sócios de uma ou outra construtora local, não se viu empreiteiros entre os doadores de 2016, por exemplo. Aumentou a participação do financiamento público, é fato. As contribuições de pequenos valores de pessoas físicas pela internet beiraram o irrisório, também é verdade. Mas diminuiu muito o peso e, portanto, a influência do capital empresarial sobre as urnas.
Do lado das despesas, houve um barateamento generalizado do marketing eleitoral. Marqueteiros precisaram trabalhar em mais campanhas para ganhar um pedaço do que costumavam receber. Serviços e equipamentos também passaram por um enxugamento.
Em 2012, gabavam-se de usar a RED – empregada em Hollywood para filmar longas metragens – ao custo de R$ 7,5 mil por dia de aluguel da câmera. Em 2016, a vedete foi a DJI Osmo, uma portátil com estabilização de imagem para tomadas em movimento e que usa o celular do fotógrafo como tela para ver as imagens. Preço: R$ 2,5 mil. Não para alugá-la, mas para comprá-la.
Mudaram também os profissionais. Até 2012, diretores de filmes de publicidade comercial eram os mais requisitados para gravar os candidatos das cidades mais populosas para suas aparições no programa eleitoral e nos spots de TV. Em 2016, seu preço ficou alto demais para as campanhas. Entraram em cena diretores de filmagem de casamento, que cobram um décimo. Não fez diferença visível nem na urna. Vários “noivos” acabaram eleitos.
Do lado da receita, o fim das doações empresarias foi ainda mais importante. Não houve nada parecido com a churrascada eleitoral promovida pela JBS em 2014. O frigorífico doou mais de R$ 350 milhões naquela eleição, e ajudou a eleger mais de 180 deputados federais – foi, disparada, a maior bancada eleita na Câmara. Nenhum doador universal se destacou em 2016. Só os partidos.
As direções partidárias exerceram uma influência maior no destino da eleição, ao decidir quais candidatos seriam privilegiados com mais recursos e quais ficariam por conta própria. As estratégias variaram de agremiação para agremiação.
O PRB, presidido por um bispo licenciado da Igreja Universal do Reino de Deus, concentrou a liberação de recursos no diretório nacional. Foram quase R$ 50 milhões, metade disse oriunda do Fundo Partidário – ou seja, recursos públicos. Marcelo Crivella, que lidera as pesquisas no segundo turno no Rio de Janeiro, foi quem mais recebeu. Logo a seguir, ficou Celso Russomanno, que terminou em terceiro lugar para prefeito paulistano.
Já o PMDB dispersou os recursos entre centenas de diretórios locais, como era esperado. Ao contrário do centralizado PRB, o PMDB é uma confederação de partidos estaduais que funciona como condomínio, e onde as decisões, inclusive as financeiras, dependem de acordo entre os seus vários caciques.
Os auto-financiados, como João Doria (PSDB), levaram vantagem, porque a legislação ainda é falha em muitos aspectos. Candidatos ricos podem tirar quanto quiserem do próprio bolso e colocar na campanha. Não deixa de ser um financiamento empresarial. A diferença é que a empresa pertence ao candidato.
Outra falha é não haver limite absoluto para as doações individuais, apenas uma proporção da renda do doador. Quanto mais rico é, mais ele pode doar e influir na campanha.
Mesmo assim, foi melhor do que a farra das doações empresariais. Por isso é temerário quando políticos começam a falar em reforma eleitoral. Sabe-se lá quais contrabandos passarão através dela.
I work as a software developer. A few years ago I had no idea what “operations” was. I had
never met anybody whose job it was to operate software. What does that even mean? Now I
know a tiny bit more about it so I want to write down what I’ve figured out.
operations: what even is it?
I made up these 3 stages of operating software. These are stages of understanding about operations I am going through.
Stage 1: your software just works. It’s fine.
You’re a software developer. You are running software on computers. When you write your software, it generally works okay – you write tests, you make sure it works on localhost, you push it to production, everything is fine. You’re a good programmer!
Sometimes you push code with bugs to production. Someone tells you about the bugs, you fix
them, it’s not a big deal.
I used to work on projects which hardly anyone used. It wasn’t a big deal if there was a
small bug! I had no idea what operations was and it didn’t matter too much.
Stage 2: omg anything can break at any time this is impossible
I think if in my “what even is operations” state somebody had told me “julia!! your site needs to be up 99.95% of the time” I would have just have hid under the bed.
Like, how can you make sure your site is up 99.95% of the time? ANYTHING CAN HAPPEN. You could have spikes in traffic, or some random piece of critical software you use could just stop working one day, or your database could catch fire. And what if I need to upgrade my database? How do I even do that safely? HELP.
I definitely went from “operations is trivial, whatever, how hard can keeping a site up be?” to “OMG THIS IS IMPOSSIBLE HOW DOES ANYONE EVER DO THIS”.
Stage 2.5: learn to be scared
I think learning to be scared is a really important skill – you should be worried
about upgrading a database safely, or about upgrading the version of Ruby you’re using in
production. These are dangerous changes!
But you can’t just stop at being scared – you need to learn to have a healthy concern about complex parts of your system, and then learn how to take the appropriate precautionary steps and then confidently make the upgrade or deploy the big change of whatever the thing you are appropriately scared of is.
If you stop here then you just end up using a super-old Ruby version for 4 years
because you were too scared to upgrade it. That is no good either!
Stage 3: keeping your site up is possible
So, it turns out that there is a huge body of knowledge about keeping your site up!
There are people who, when you show them a large complicated software system
running on thousands or tens of thousands of computers, and tell them “hey, this needs to
be up 99.9% of the time”, they’re like “yep, that is a normal problem I have worked on! Here’s the first step we can take!”
These people sometimes have the job title “operations engineer” or “SRE” or “devops engineer” or “software engineer” or “system administrator”. Like all things, it’s a skillset that you can learn, not a magical innate quality.
Charity is one of these people! That blog post (”The Accidental
DBA”)) I linked to before has a bunch
of extremely practical advice about how to upgrade a database safely. If you’re running a
database and you’re scared – you’re right! But you can learn about how to upgrade it from
someone like Charity and then it will go a lot better.
getting started with operations
So, we’ve convinced ourselves that operations is important.
Last year I was on a team that had some software. It mostly ran okay, but infrequently it
would stop working or get super slow. There were a bunch of different reasons it had
problems! And it wasn’t a disaster, but it also wasn’t as awesome as we wanted it to be.
For me this was a really cool way to get a little bit better at operations! I worked on
making the service faster and more reliable. And it worked! I made a couple of good
improvements, and I was happy.
Some stuff that helped:
work on a dashboard for the service that clearly shows its current state (this is surprisingly hard!)
move some complicated code that did a lot of database operations into a separate webservice so we could easily time it out if something went wrong
do some profiling and remove some unnecessarily slow code
The most cool part of this, though, is that a much more experienced SRE later came in to
work with the team on making the same service operate better, and I got to see what he did
and what his process for improving things looked like!
It’s really helped me to realize that you don’t turn into a Magical Operations Person overnight. Instead, I can take whatever I’m working on right now, and make small improvements to make it operate better! That makes me a better programmer.
you can make operations part of your job
As an industry, we used to have “software development” teams who wrote code and threw it over the wall to “operations teams” who ran that code. I feel like we’ve collectively decided that we want a different model (“devops”) – that we should have teams who both write code and know how to operate it. And there are a lot of details of how that works exactly (do you have “SRE”s?)
But as an individual software engineer, what does that mean for you? I thiiink it means that you get to LEARN COOL STUFF. You can learn about how to deploy changes safely, and observe what your code is doing. And then when something has gone wrong in production, you’ll both understand what the code is doing (because you wrote it!!) and you’ll have the skills to figure it out and systematically prevent it in the future (because you are better at operations!).
I have a lot more to say about this (how I really love being a generalist, how doing some operations work has been an awesome way to improve my debugging skills and my ability to reason about complex systems and plan how to build complicated software). And I need to write in the future about super useful Ideas For Operating Software Safely I’ve learned about (like dark reads and circuit breakers). But I’m going to stop here for now. If you want more reading The Ops Identity Crisis is a good post about software developers doing operations, from the point of view of an ops person.
This is my favorite paragraph from Charity’s “WTF is operations?” blog post (which you should just go read instead of reading me):
The best software engineers I know are the ones who consistently value the impact and lifecycle of the code they ship, and value deployment and instrumentation and observability. In other words, they rock at ops stuff.
There are a lot of “12 CS books every programmer must read” lists floating around out there. That's nonsense. The field is too broad for almost any topic to be required reading for all programmers, and even if a topic is that important, people's learning preferences differ too much for any book on that topic to be the best book on the topic for all people.
This is a list of topics and books where I've read the book, am familiar enough with the topic to say what you might get out of learning more about the topic, and have read other books and can say why you'd want to read one book over another.
Algorithms / Data Structures / Complexity
Why should you care? Well, there's the pragmatic argument: even if you never use this stuff in your job, most of the best paying companies will quiz you on this stuff in interviews. On the non-bullshit side of things, I find algorithms to be useful in the same way I find math to be useful. The probability of any particular algorithm being useful for any particular problem is low, but having a general picture of what kinds of problems are solved problems, what kinds of problems are intractable, and when approximations will be effective, is often useful.
Some problems and solutions, with explanations, matching the level of questions you see in entry-level interviews at Google, Facebook, Microsoft, etc. I usually recommend this book to people who want to pass interviews but not really learn about algorithms. It has just enough to get by, but doesn't really teach you the why behind anything. If you want to actually learn about algorithms and data structures, see below.
Everything about this book seems perfect to me. It breaks up algorithms into classes (e.g., divide and conquer or greedy), and teaches you how to recognize what kind of algorithm should be used to solve a particular problem. It has a good selection of topics for an intro book, it's the right length to read over a few weekends, and it has exercises that are appropriate for an intro book. Additionally, it has sub-questions in the middle of chapters to make you reflect on non-obvious ideas to make sure you don't miss anything.
I know some folks don't like it because it's relatively math-y/proof focused. If that's you, you'll probably prefer Skiena.
The longer, more comprehensive, more practical, less math-y version of Dasgupta. It's similar in that it attempts to teach you how to identify problems, use the correct algorithm, and give a clear explanation of the algorithm. Book is well motivated with “war stories” that show the impact of algorithms in real world programming.
This book somehow manages to make it into half of these “N books all programmers must read” lists despite being so comprehensive and rigorous that almost no practitioners actually read the entire thing. It's great as a textbook for an algorithms class, where you get a selection of topics. As a class textbook, it's nice bonus that it has exercises that are hard enough that they can be used for graduate level classes (about half the exercises from my grad level algorithms class were pulled from CLRS, and the other half were from Kleinberg & Tardos), but this is wildly impractical as a standalone introduction for most people.
Just for example, there's an entire chapter on Van Emde Boas trees. They're really neat -- it's a little surprising that a balanced-tree-like structure with O(lg lg n) insert, delete, as well as find, successor, and predecessor is possible, but a first introduction to algorithms shouldn't include Van Emde Boas trees.
Same comments as for CLRS -- it's widely recommended as an introductory book even though it doesn't make sense as an introductory book. Personally, I found the exposition in Kleinberg to be much easier to follow than in CLRS, but plenty of people find the opposite.
This is a set of lectures and notes and not a book, but if you want a coherent (but not intractably comprehensive) set of material on data structures that you're unlikely to see in most undergraduate courses, this is great. The notes aren't designed to be standalone, so you'll want to watch the videos if you haven't already seen this material.
Fun to work through, but, unlike the other algorithms and data structures books, I've yet to be able to apply anything from this book to a problem domain where performance really matters.
For a couple years after I read this, when someone would tell me that it's not that hard to reason about the performance of purely functional lazy data structures, I'd ask them about part of a proof that stumped me in this book. I'm not talking about some obscure super hard exercise, either. I'm talking about something that's in the main body of the text that was considered too obvious to the author to explain. No one could explain it. Reasoning about this kind of thing is harder than people often claim.
A gentle introduction to functional programming that happens to use Perl. You could probably work through this book just as easily in Python or Ruby.
If you keep up with what's trendy, this book might seem a bit dated today, but only because so many of the ideas have become mainstream. If you're wondering why you should care about this "functional programming" thing people keep talking about, and some of the slogans you hear don't speak to you or are even off-putting (types are propositions, it's great because it's math, etc.), give this book a chance.
I ordered this off amazon after seeing these two blurbs: “Other learning-enhancement features include chapter summaries, hints to the exercises, and a detailed solution manual.” and “Student learning is further supported by exercise hints and chapter summaries.” One of these blurbs is even printed on the book itself, but after getting the book, the only self-study resources I could find were some yahoo answers posts asking where you could find hints or solutions.
I ended up picking up Dasgupta instead, which was available off an author's website for free.
I've probably gotten more mileage out of this than out of any other algorithms book. A lot of randomized algorithms are trivial to port to other applications and can simplify things a lot.
The text has enough of an intro to probability that you don't need to have any probability background. Also, the material on tails bounds (e.g., Chernoff bounds) is useful for a lot of CS theory proofs and isn't covered in the intro probability texts I've seen.
Classic intro to theory of computation. Turing machines, etc. Proofs are often given at an intuitive, “proof sketch”, level of detail. A lot of important results (e.g, Rice's Theorem) are pushed into the exercises, so you really have to do the key exercises. Unfortunately, most of the key exercises don't have solutions, so you can't check your work.
For something with a more modern topic selection, maybe see Aurora & Barak.
Covers a few theory of computation highlights. The explanations are delightful and I've watched some of the videos more than once just to watch Bernhardt explain things. Targeted at a general programmer audience with no background in CS.
Classic, but dated and riddled with errors, with no errata available. When I wanted to learn this material, I ended up cobbling together notes from a couple of courses, one by Klivans and one by Blum.
Operating Systems
Why should you care? Having a bit of knowledge about operating systems can save days or week of debugging time. This is a regular theme on Julia Evans's blog, and I've found the same thing to be true of my experience. I'm hard pressed to think of anyone who builds practical systems and knows a bit about operating systems who hasn't found their operating systems knowledge to be a time saver. However, there's a bias in who reads operating systems books -- it tends to be people who do related work! It's possible you won't get the same thing out of reading these if you do really high-level stuff.
This was what we used at Wisconsin before the comet book became standard. I guess it's ok. It covers concepts at a high level and hits the major points, but it's lacking in technical depth, details on how things work, advanced topics, and clear exposition.
This book is great! It explains how you can actually implement things in a real system, and it comes with its own implementation of an OS that you can play with. By design, the authors favor simple implementations over optimized ones, so the algorithms and data structures used are often quite different than what you see in production systems.
This book goes well when paired with a book that talks about how more modern operating systems work, like Love's Linux Kernel Development or Russinovich's Windows Internals.
Nice explanation of a variety of OS topics. Goes into much more detail than any other intro OS book I know of. For example, the chapters on file systems describe the details of multiple, real, filessytems, and discusses the major implementation features of ext4. If I have one criticism about the book, it's that it's very *nix focused. Many things that are described are simply how things are done in *nix and not inherent, but the text mostly doesn't say when something is inherent vs. when it's a *nix implementation detail.
The title can be a bit misleading -- this is basically a book about how the Linux kernel works: how things fit together, what algorithms and data structures are used, etc. I read the 2nd edition, which is now quite dated. The 3rd edition has some updates, but introduced some errors and inconsistencies, and is still dated (it was published in 2010, and covers 2.6.34). Even so, it's a nice introduction into how a relatively modern operating system works.
The other downside of this book is that the author loses all objectivity any time Linux and Windows are compared. Basically every time they're compared, the author says that Linux has clearly and incontrovertibly made the right choice and that Windows is doing something stupid. On balance, I prefer Linux to Windows, but there are a number of areas where Windows is superior, as well as areas where there's parity but Windows was ahead for years. You'll never find out what they are from this book, though.
The most comprehensive book about how a modern operating system works. It just happens to be about Windows. Coming from a *nix background, I found this interesting to read just to see the differences.
This is definitely not an intro book, and you should have some knowledge of operating systems before reading this. If you're going to buy a physical copy of this book, you might want to wait until the 7th edition is released (early in 2017).
Takes a topic that's normally one or two sections in an operating systems textbook and turns it into its own 300 page book. The book is a series of exercises, a bit like The Little Schemer, but with more exposition. It starts by explaining what semaphore is, and then has a series of exercises that builds up higher level concurrency primitives.
This book was very helpful when I first started to write threading/concurrency code. I subscribe to the Butler Lampson school of concurrency, which is to say that I prefer to have all the concurrency-related code stuffed into a black box that someone else writes. But sometimes you're stuck writing the black box, and if so, this book has a nice introduction to the style of thinking required to write maybe possibly not totally wrong concurrent code.
I wish someone would write a book in this style, but both lower level and higher level. I'd love to see exercises like this, but starting with instruction-level primitives for a couple different architectures with different memory models (say, x86 and Alpha) instead of semaphores. If I'm writing grungy low-level threading code today, I'm overwhelmingly likely to be using c++11 threading primitives, so I'd like something that uses those instead of semaphores, which I might have used if I was writing threading code against the Win32 API. But since that book doesn't exist, this seems like the next best thing.
Why should you care? The specific facts and trivia you'll learn will be useful when you're doing low-level performance optimizations, but the real value is learning how to reason about tradeoffs between performance and other factors, whether that's power, cost, size, weight, or something else.
In theory, that kind of reasoning should be taught regardless of specialization, but my experience is that comp arch folks are much more likely to “get” that kind of reasoning and do back of the envelope calculations that will save them from throwing away a 2x or 10x (or 100x) factor in performance for no reason. This sounds obvious, but I can think of multiple production systems at large companies that are giving up 10x to 100x in performance which are operating at a scale where even a 2x difference in performance could pay a VP's salary -- all because people didn't think through the performance implications of their design.
Hennessy & Patterson; Computer Architecture: A Quantitative Approach
This book teaches you how to do systems design with multiple constraints (e.g., performance, TCO, and power) and how to reason about tradeoffs. It happens to mostly do so using microprocessors and supercomputers as examples.
New editions of this book have substantive additions and you really want the latest version. For example, the latest version added, among other things, a chapter on data center design, and it answers questions like, how much opex/capex is spent on power, power distribution, and cooling, and how much is spent on support staff and machines, what's the effect of using lower power machines on tail latency and result quality (bing search results are used as an example), and what other factors should you consider when designing a data center.
Assumes some background, but that background is presented in the appendices (which are available online for free).
Presents most of what you need to know to architect a high performance Pentium Pro (1995) era microprocessor. That's no mean feat, considering the complexity involved in such a processor. Additionally, presents some more advanced ideas and bounds on how much parallelism can be extracted from various workloads (and how you might go about doing such a calculation). Has an unusually large section on value prediction, because the authors invented the concept and it was still hot when the first edition was published.
For pure CPU architecture, this is probably the best book available.
Read for historical reasons and to see how much better we've gotten at explaining things. For example, compare Amdahl's paper on Amdahl's law (two pages, with a single non-obvious graph presented, and no formulas), vs. the presentation in a modern textbook (one paragraph, one formula, and maybe one graph to clarify, although it's usually clear enough that no extra graph is needed).
This seems to be worse the further back you go; since comp arch is a relatively young field, nothing here is really hard to understand. If you want to see a dramatic example of how we've gotten better at explaining things, compare Maxwell's original paper on Maxwell's equations to a modern treatment of the same material. Fun if you like history, but a bit of slog if you're just trying to learn something.
Algorithmic game theory / auction theory / mechanism design
Why should you care? Some of the world's biggest tech companies run on ad revenue, and those ads are sold through auctions. This field explains how and why they work. Additionally, this material is useful any time you're trying to figure out how to design systems that allocate resources effectively.1
In particular, incentive compatible mechanism design (roughly, how to create systems that provide globally optimal outcomes when people behave in their own selfish best interest) should be required reading for anyone who designs internal incentive systems at companies. If you've ever worked at a large company that "gets" this and one that doesn't, you'll see that the company that doesn't get it has giant piles of money that are basically being lit on fire because the people who set up incentives created systems that are hugely wasteful. This field gives you the background to understand what sorts of mechanisms give you what sorts of outcomes; reading case studies gives you a very long (and entertaining) list of mistakes that can cost millions or even billions of dollars.
The last time I looked, this was the only game in town for a comprehensive, modern, introduction to auction theory. Covers the classic second price auction result in the first chapter, and then moves on to cover risk aversion, bidding rings, interdependent values, multiple auctions, asymmetrical information, and other real-world issues.
Relatively dry. Unlikely to be motivating unless you're already interested in the topic. Requires an understanding of basic probability and calculus.
Seems designed as an entertaining introduction to auction theory for the layperson. Requires no mathematical background and relegates math to the small print. Covers maybe, 1/10th of the material of Krishna, if that. Fun read.
Discusses things like how FCC spectrum auctions got to be the way they are and how “bugs” in mechanism design can leave hundreds of millions or billions of dollars on the table. This is one of those books where each chapter is by a different author. Despite that, it still manages to be coherent and I didn't mind reading it straight through. It's self-contained enough that you could probably read this without reading Krishna first, but I wouldn't recommend it.
The title is the worst thing about this book. Otherwise, it's a nice introduction to algorithmic game theory. The book covers basic game theory, auction theory, and other classic topics that CS folks might not already know, and then covers the intersection of CS with these topics. Assumes no particular background in the topic.
A survey of various results in algorithmic game theory. Requires a fair amount of background (consider reading Shoham and Leyton-Brown first). For example, chapter five is basically Devanur, Papadimitriou, Saberi, and Vazirani's JACM paper, Market Equilibrium via a Primal-Dual Algorithm for a Convex Program, with a bit more motivation and some related problems thrown in. The exposition is good and the result is interesting (if you're into that kind of thing), but it's not necessarily what you want if you want to read a book straight through and get an introduction to the field.
A description of how Google handles operations. Has the typical Google tone, which is off-putting to a lot of folks with a “traditional” ops background, and assumes that many things can only be done with the SRE model when they can, in fact, be done without going full SRE.
Fowler, Beck, Brant, Opdyke, and Roberts; Refactoring
At the time I read it, it was worth the price of admission for the section on code smells alone. But this book has been so successful that the ideas of refactoring and code smells have become mainstream.
When I read this book for the first time, in October 2003, I felt this horrid cold feeling, the way you might feel if you just realized you've been coming to work for 5 years with your pants down around your ankles. I asked around casually the next day: "Yeah, uh, you've read that, um, Refactoring book, of course, right? Ha, ha, I only ask because I read it a very long time ago, not just now, of course." Only 1 person of 20 I surveyed had read it. Thank goodness all of us had our pants down, not just me.
...
If you're a relatively experienced engineer, you'll recognize 80% or more of the techniques in the book as things you've already figured out and started doing out of habit. But it gives them all names and discusses their pros and cons objectively, which I found very useful. And it debunked two or three practices that I had cherished since my earliest days as a programmer. Don't comment your code? Local variables are the root of all evil? Is this guy a madman? Read it and decide for yourself!
This book seemed convincing when I read it in college. It even had all sorts of studies backing up what they said. No deadlines is better than having deadlines. Offices are better than cubicles. Basically all devs I talk to agree with this stuff.
But virtually every successful company is run the opposite way. Even Microsoft is remodeling buildings from individual offices to open plan layouts. Could it be that all of this stuff just doesn't matter that much? If it really is that important, how come companies that are true believers, like Fog Creek, aren't running roughshod over their competitors?
This book agrees with my biases and I'd love for this book to be right, but the meta evidence makes me want to re-read this with a critical eye and look up primary sources.
This book explains how Microsoft's aggressive culture got to be the way it is today. The intro reads:
Microsoft didn't necessarily hire clones of Gates (although there were plenty on the corporate campus) so much as recruiter those who shared some of Gates's more notable traits -- arrogance, aggressiveness, and high intelligence.
…
Gates is infamous for ridiculing someone's idea as “stupid”, or worse, “random”, just to see how he or she defends a position. This hostile managerial technique invariably spread through the chain of command and created a culture of conflict.
…
Microsoft nurtures a Darwinian order where resources are often plundered and hoarded for power, wealth, and prestige. A manager who leaves on vacation might return to find his turf raided by a rival and his project put under a different command or canceled altogether
On interviewing at Microsoft:
“What do you like about Microsoft?”
“Bill kicks ass”, St. John said. “I like kicking ass. I enjoy the feeling of killing competitors and dominating markets”.
…
He was unsure how he was doing and thought he stumbled then asked if he was a "people person".
"No, I think most people are idiots", St. John replied.
These answers were exactly what Microsoft was looking for. They resulted in a strong offer and an aggresive courtship.
On developer evangalism at Microsoft:
At one time, Microsoft evangelists were also usually chartered with disrupting competitors by showing up at their conferences, securing positions on and then tangling standards commitees, and trying to influence the media.
…
"We're the group at Microsoft whose job is to fuck Microsoft's competitors"
Read this book if you're considering a job at Microsoft. Although it's been a long time since the events described in this book, you can still see strains of this culture in Microsoft today.
An entertaining book about the backstabbing, mismangement, and random firings that happened in Twitter's early days. When I say random, I mean that there were instances where critical engineers were allegedly fired so that the "decider" could show other important people that current management was still in charge.
I don't know folks who were at Twitter back then, but I know plenty of folks who were at the next generation of startups in their early days and there are a couple of companies where people had eerily similar experiences. Read this book if you're considering a job at a trendy startup.
This book is about art and how productivity changes with age, but if its thesis is valid, it probably also applies to programming. Galenson applies statistics to determine the "greatness" of art and then uses that to draw conclusions about how the productivty of artists change as they age. I don't have time to go over the data in detail, so I'll have to remain skeptical of this until I have more free time, but I think it's interesting reading even for a skeptic.
Math
Why should you care? From a pure ROI perspective, I doubt learning math is “worth it” for 99% of jobs out there. AFAICT, I use math more often than most programmers, and I don't use it all that often. But having the right math background sometimes comes in handy and I really enjoy learning math. YMMV.
Introductory undergrad text that tends towards intuitive explanations over epsilon-delta rigor. For anyone who cares to do more rigorous derivations, there are some exercises at the back of the book that go into more detail.
Has many exercises with available solutions, making this a good text for self-study.
This is one of those books where they regularly crank out new editions to make students pay for new copies of the book (this is presently priced at a whopping $174 on Amazon)2. This was the standard text when I took probability at Wisconsin, and I literally cannot think of a single person who found it helpful. Avoid.
Brualdi is a great lecturer, one of the best I had in undergrad, but this book was full of errors and not particularly clear. There have been two new editions since I used this book, but according to the Amazon reviews the book still has a lot of errors.
For an alternate introductory text, I've heard good things about Camina & Lewis's book, but I haven't read it myself. Also, Lovasz is a great book on combinatorics, but it's not exactly introductory.
Volume 1 covers what you'd expect in a calculus I + calculus II book. Volume 2 covers linear algebra and multivariable calculus. It covers linear algebra before multivariable calculus, which makes multi-variable calculus a lot easier to understand.
It also makes a lot of sense from a programming standpoint, since a lot of the value I get out of calculus is its applications to approximations, etc., and that's a lot clearer when taught in this sequence.
This book is probably a rough intro if you don't have a professor or TA to help you along. The Spring SUMS series tends to be pretty good for self-study introductions to various areas, but I haven't actually read their intro calculus book so I can't actually recommend it.
Another one of those books where they crank out new editions with trivial changes to make money. This was the standard text for non-honors calculus at Wisconsin, and the result of that was I taught a lot of people to do complex integrals with the methods covered in Apostol, which are much more intuitive to many folks.
This book takes the approach that, for a type of problem, you should pattern match to one of many possible formulas and then apply the formula. Apostol is more about teaching you a few tricks and some intuition that you can apply to a wide variety of problems. I'm not sure why you'd buy this unless you were required to for some class.
Hardware basics
Why should you care? People often claim that, to be a good programmer, you have to understand every abstraction you use. That's nonsense. Modern computing is too complicated for any human to have a real full-stack understanding of what's going on. In fact, one reason modern computing can accomplish what it does is that it's possible to be productive without having a deep understanding of much of the stack that sits below the level you're operating at.
That being said, if you're curious about what sits below software, here are a few books that will get you started.
If you only want to read one single thing, this should probably be it. It's a “101” level intro that goes down to gates and Boolean logic. As implied by the name, it takes you from NAND gates to a working tetris program.
Much more detail on gates and logic design than you'll see in nand2tetris. The book is full of exercises and appears to be designed to work for self-study. Note that the link above is to the 5th edition. There are newer, more expensive, editions, but they don't seem to be much improved, have a lot of errors in the new material, and are much more expensive.
One level below Boolean gates, you get to VLSI, a historical acronym (very large scale integration) that doesn't really have any meaning today.
Broader and deeper than the alternatives, with clear exposition. Explores the design space (e.g., the section on adders doesn't just mention a few different types in an ad hoc way, it explores all the tradeoffs you can make. Also, has both problems and solutions, which makes it great for self study.
Kang & Leblebici; CMOS Digital Integrated Circuits
This was the standard text at Wisconsin way back in the day. It was hard enough to follow that the TA basically re-explained pretty much everything necessary for the projects and the exams. I find that it's ok as a reference, but it wasn't a great book to learn from.
Compared to West et al., Weste spends a lot more effort talking about tradeoffs in design (e.g., when creating a parallel prefix tree adder, what does it really mean to be at some particular point in the design space?).
One level below VLSI, you have how transistors actually work.
Really beautiful explanation of solid state devices. The text nails the fundamentals of what you need to know to really understand this stuff (e.g., band diagrams), and then uses those fundamentals along with clear explanations to give you a good mental model of how different types of junctions and devices work.
One level below transistors, you have electromagnetics.
Two to three times thicker than other intro texts because it has more worked examples and diagrams. Breaks things down into types of problems and subproblems, making things easy to follow. For self-study, A much gentler introduction than Griffiths or Purcell.
Unlike the other books in this section, this book is about practice instead of theory. It's a bit like Windows Internals, in that it goes into the details of a real, working, system. Topics include hardware bus protocols, how I/O actually works (e.g., APIC), etc.
The problem with a practical introduction is that there's been an exponential increase in complexity ever since the 8080. The further back you go, the easier it is to understand the most important moving parts in the system, and the more irrelevant the knowledge. This book seems like an ok compromise in that the bus and I/O protocols had to handle multiprocessors, and many of the elements that are in modern systems were in these systems, just in a simpler form.
Not covered
Of the books that I've liked, I'd say this captures at most 25% of the software books and 5% of the hardware books. On average, the books that have been left off the list are more specialized. This list is also missing many entire topic areas, like PL, practical books on how to learn languages, networking, etc.
The reasons for leaving off topic areas vary; I don't have any PL books listed because I don't read PL books. I don't have any networking books because, although I've read a couple, I don't know enough about the area to really say how useful the books are. The vast majority of hardware books aren't included because they cover material that you wouldn't care about unless you were a specialist (e.g., Skew-Tolerant Circuit Design or Ultrafast Optics). The same goes for areas like math and CS theory, where I left off a number of books that I think are great but have basically zero probability of being useful in my day-to-day programming life, e.g., Extremal Combinatorics. I also didn't include books I didn't read all or most of, unless I stopped because the book was atrocious. This means that I don't list classics I haven't finished like SICP and The Little Schemer, since those book seem fine and I just didn't finish them for one reason or another.
This list also doesn't include many books on history and culture, like Inside Intel or Masters of Doom. I'll probably add more at some point, but I've been trying an experiment where I try to write more like Julia Evans (stream of consciousness, fewer or no drafts). I'd have to go back and re-read the books I read 10+ years ago to write meaningful comments, which doesn't exactly fit with the experiment. On that note, since this list is from memory and I got rid of almost all of my books a couple years ago, I'm probably forgetting a lot of books that I meant to add.
_Thanks to @tytrdev for comments/corrections/discussion.
Also, if you play board games, auction theory explains why fixing game imbalance via an auction mechanism is non-trivial and often makes the game worse.
[return]
I talked to the author of one of these books. He griped that the used book market destroys revenue from textbooks after a couple years, and that authors don't get much in royalties, so you have to charge a lot of money and keep producing new editions every couple of years to make money. That griping goes double in cases where a new author picks up a book classic book that someone else originally wrote, since the original author often has a much larger share of the royalties than the new author, despite doing no work no the later editions.
[return]
I. The pencil had a life of its own A few years ago Burrell Webb, a retired landscape artist living in Oregon, discovered that a poem he wrote and never copyrighted had become one of the most widely circulated verses in the English language. He says he composed the lines in 1958, after leaving the navy and being dumped by his girlfriend. “I was stressed, distressed, and single,” he says. “When I received those divine words, I broke up the lines and made a kind of poem out of it.” The finished product, which he published anonymously in a local newspaper—he felt it was God’s work, not his—tells the story of a man who has a dream that he and God are walking along the beach. When the man asks why sometimes there is one set of footprints and other times there are two, the Lord says he has been carrying him through his struggles.
Forty years later, Webb was alarmed when his son informed him that the poem was on napkins, calendars, posters, gift cards, and teacups. Usually “Footprints” was signed “Author Unknown,” but other times the credit was given to Mary Stevenson, Margaret Fishback Powers, or Carolyn Joyce Carty, who have all registered copyrights for the poem. (Registration does not require proof of originality.) The three versions differ mostly in tense, word order, and line breaks. With no way to prove that the work was actually his, Webb paid $400 to take a polygraph test. Now he routinely sends the results (“No deception indicated”) to those who question his claim.
Although several people have suggested to Webb, as consolation, that God gave the idea to multiple authors in order to more efficiently spread His Word, Webb is unsettled by the idea that “the Lord would be the author of confusion.” However the verse came into being, its message has reached all over the world. “Footprints” is the kind of poem we all seem to know without remembering when or where we first saw it. We’ve read it dozens of times, never paying attention. The verse is dislocated from context, so familiar and predictable that the boundary between writing and reading seems to disappear.
Yet the authors who claim to have composed "Footprints" have memories of the precise moment when they dreamed up these lines. Mary Stevenson, a former showgirl and nurse, said she composed the verse in 1936, following the death of her mother and brother. According to Gail Giorgio's 1995 biography Footprints in the Sand: The Life Story of Mary Stevenson, Author of the Immortal Poem, Stevenson was inspired by a cat's footprints in the snow and scrawled out twenty lines, as if the "pencil had a life of its own." She was so pleased with her work that she handed out the poem heedlessly, jotting it down for anyone she met without thinking to sign her name. (Early in the book her father tells her, “Poetry’s nice to read, but essentially it’s just rambling words on a piece of paper.”)
Powers, a Baptist children's evangelist, was more savvy about licensing the verse—she sold it to HarperCollins Canada in 1993—and she describes “Footprints” as the culmination of a life of religious devotion. In her memoir, Footprints: The True Story behind the Poem That Inspired Millions, she enthusiastically recounts all the tragedies she endured while never losing her belief in the Lord. In the course of 100 pages, she gets struck by lightning, develops spinal meningitis, gets hit by a truck, and has a near-death experience with a bumblebee. Her daughter gets crushed by a motorcycle and later slips down a 68-foot waterfall while her husband, watching, has a heart attack. In the hospital room a nurse pulls out “a little piece I have here in my pocket” and recites “Footprints” to ease the family’s pain. When she casually mentions what a shame it is that no one knows the poem’s author, Powers’ husband croaks from his bed, “It’s my wife.”
Far from dead, Powers currently travels around the world giving sermons about the power of faith. She has licensed the poem to nearly 30 companies, including Hallmark Cards and Lenox Gifts. Her lawyer, John A. Hughes, a self-described atheist, won’t say how much Powers has earned from her publications, except to guess that “Footprints” might be the “best-remunerated poem in history.” When pressed, he compares its success to that of “The Star-Spangled Banner.” He has written more than 100 companies, requesting that they replace “Author Unknown” with his client’s name. “I am completely satisfied factually that Margaret is telling the truth,” he says. He acknowledges that “Footprints” is not entirely consistent with Powers’ other poems, which are composed of rhyming couplets, but he’s confident it’s within her range. (To prove that “Footprints” couldn’t be written by Stevenson, he contemplated hiring Donald Foster, the forensic literary analyst who studied the letters of the Unabomber.)
"Footprints" is far less of a stylistic aberration for Powers than it is for Mary Stevenson, who wrote sporadically, or Carolyn Joyce Carty, who struggles with punctuation and spelling. Carty is the most hostile of the contenders and she frequently issues error-ridden cease-and-desist letters to those who post the poem online. (She signs her e-mails “World Renowned Poet.”)
Carty wrote “Footprints” in 1963, when she was six. She says she based the idea on a poem written by her great-great-aunt, a Sunday school teacher. More than 20 years later, she copyrighted the verse as part of an 11-page document of stream-of-consciousness prose (“the gift, who are you, where have you come from, where are you going! I am a writers inkhorn that stands beside the sea”), which concluded with the text of “Footprints.” She declined to be interviewed but characterized her writing style in an e-mail: “I like common denominators in subjects, I always look for the common bond when trying to create a universal message.”
In describing her literary taste, Carty also articulates the intangible draw of “Footprints.” The poem reads as if it were written by consensus. Light, peppy, and moderately Christian, “Footprints” succinctly dramatizes an idea that will never be original: When we think we’re alone, we’re not. God is here. The footprints metaphor is so ubiquitous that perhaps the authors absorbed the message at some point without realizing it, then later sat down and wrote it out again, seeking to appeal to the largest number of people.
II. Do I know you? In “Cryptomnesia” (1905), a paper about accidental plagiarism, Carl Jung argues that it’s impossible to know for certain which ideas are one’s own. “Our unconsciousness . . . swarms with strange intruders,” he writes. He accuses Nietzsche of unwittingly copying another’s work, and urges all writers to sift through their memories and locate the origin of every idea before putting it to paper: “Ask each thought: Do I know you, or are you new?”
In the realm of Christian poetry, the process of distinguishing which ideas are original is significantly harder—the same body of collective epiphanies has been passed down for years. When artists open themselves up to the inspiration of the Lord, it’s not surprising that sometimes they produce sentences that sound as if they’ve been uttered before. The first line of “Footprints,” which varies slightly among versions, seems to announce the authors’ access to the collective unconscious: “I had a dream,” “One night a man had a dream,” “One night I dreamed a dream.”
One of the earliest articulations of the poem’s premise—the idea that God reveals his presence through marks in the sand—comes from an 1880 sermon by Charles Haddon Spurgeon, a noted Baptist preacher.
And did you ever walk out upon that lonely desert island upon which you were wrecked, and say, “I am alone, — alone, — alone, — nobody was ever here before me”? And did you suddenly pull up short as you noticed, in the sand, the footprints of a man? I remember right well passing through that experience; and when I looked, lo! it was not merely the footprints of a man that I saw, but I thought I knew whose feet had left those imprints; they were the marks of One who had been crucified, for there was the print of the nails. So I thought to myself, “If he has been here, it is a desert island no longer.”
Spurgeon’s formulation, more nuanced than the Footprints poem, rehearses the same fear of being “alone, — alone, —alone,” and then happily resolves it.
In other uses of the metaphor, the footprints image speaks to man’s omnipresence, not God’s. This seemingly banal metaphor has become a truism in secular writing as well. In an 1894 essay about composing his first book, Robert Louis Stevenson (whom Mary Stevenson, coincidentally, claims as a relative, and whom Carty cites as an influence) refers to footprints in the sand when acknowledging how hard it is to avoid borrowing from previously published work. After admitting adopting characters from Washington Irving (“But I had no guess of it then as I sat writing by the fireside”), as well as “trifles and details” from Daniel Defoe and Edgar Allan Poe, he invokes the footprints image. It’s as if he already associates the phrase with authorial confusion:
I am now upon a painful chapter. No doubt the parrot once belonged to Robinson Crusoe. No doubt the skeleton is conveyed from Poe. . . . These useful writers had fulfilled the poet’s saying: departing, they had left behind them Footprints on the sands of time, Footprints which perhaps another—and I was the other!
The “poet’s saying,” which Stevenson refers to, is Henry Wadsworth Longfellow’s“A Psalm of Life”: “Lives of great men all remind us / We can make our lives sublime, / And, departing, leave behind us / Footprints on the sands of time.” It’s fitting that in defending himself against plagiarism, Stevenson deploys a quote that has spawned so many interpretations. “Footprints on the sands of time” is a perfect image for cliché: terrain trod over and retraced, flattened with overuse.
But those claiming to have written “Footprints” argue that the image came to them as suddenly and surprisingly as a new gift. Burrell Webb rejects the notion that he somehow inherited an existing metaphor. It’s far more likely, he says, that people are trying to profit from his work. “I’ve never heard of the fellow [Spurgeon], so he couldn’t have possibly inspired me,” Webb says. “That allegorical poem was strictly a prayer relationship with myself and the Lord when I was feeling bad and crying for help and whining a little bit, which everybody goes through.”
Although nearly all of these authors claim they wrote the poem in longhand, dictated by God, the controversy didn’t surface until everyone began putting their versions online. There are hundreds of “Footprints”-inspired Web sites. One has a soundtrack of waves lapping against the shore; another features lines of the poem jiggling to the beat of Christmas songs. In Andrew Keen’s 2007 book The Cult of the Amateur, he writes that the Internet has induced a state of communal amnesia; we’ve lost “our memory for things learnt, read, experienced, or heard.” Perhaps the "Footprints" writers are living a version of this peculiar situation. There's not only an abundance of amateur authors, but they've all written the exact same thing.
Along with Webb, Carty, Stevenson, and Powers, at least a dozen other people have claimed, less rigorously, to have penned this poem. None of their accounts are particularly convincing, yet they all seem to genuinely believe they wrote the poem. They describe the words coming out effortlessly, even uncontrollably, as if they were finally articulating something they’d always known.
Princeton mathematician John Horton Conway investigated this curious permutation:
3n ↔ 2n
3n ± 1 ↔ 4n ± 1
It’s a simple set of rules for creating a sequence of numbers. In the words of University of Calgary mathematician Richard Guy, “Forwards: if it divides by 3, take off a third; if it doesn’t, add a third (to the nearest whole number). Backwards: if it’s even, add 50%; if it’s odd, take off a quarter.”
If we start with 1, we get a string of 1s: 1, 1, 1, 1, 1, …
If we start with 2 or 3 we get an alternating sequence: 2, 3, 2, 3, 2, 3, …
If we start with 4 we get a longer cycle that repeats: 4, 5, 7, 9, 6, 4, 5, 7, 9, 6, …
And if we start with 44 we get an even longer repeating cycle: 44, 59, 79, 105, 70, 93, 62, 83, 111, 74, 99, 66, 44, …
But, curiously, these four are the only loops that anyone has found — start with any other number and it appears you can build the sequence indefinitely in either direction without re-encountering the original number. Try starting with 8:
Paradoxically, the sequence climbs in both directions: Going forward we multiply by 2/3 a third of the time and by roughly 4/3 two-thirds of the time, so on average in three steps we’re multiplying by 32/27. Going backward we multiply by 3/2 half the time and by roughly 3/4 half the time, so on average in two steps we’re multiplying by 9/8. And every even number is preceded by a multiple of three — half the numbers are multiples of three!
What happens to these chains? Will the sequence above ever encounter another 8 and close up to form a loop? What about the sequences based on 14, 40, 64, 80, 82 … ? “Again,” writes Guy, “there are many more questions than answers.”
(Richard K. Guy, “What’s Left?”, Math Horizons 5:4 [April 1998], 5-7; and Richard K. Guy, Unsolved Problems in Number Theory, 2004.)
‘The Present’ é um curta produzido na Alemanha e que já conquistou mais de 50 prêmios ao redor do mundo em festivais, entre eles o prêmio de Melhor Curta Infantil na última edição do AnimaMundi.
Na história, Jake é um menino que passa a maior parte do tempo jogando videogames. Até que, um dia, sua mãe traz um presente muito especial.
A trama emocionante do curta é baseada em uma pequena história em quadrinhos do brasileiro Fábio Coala, ilustrador responsável pelo site Mentirinhas.com. A tira viralizou na internet até chegar nas mãos de Jacob Frey, que decidiu entrar em contato com o criador do HQ e depois disso foi responsável pela direção e animação do curta.
O contato entre os dois aconteceu graças a Natália Freitas, brasileira que conseguiu entrar na conceituada escola de cinema alemã Filmakademie Baden-Wuerttemberg – a mesma onde Frey estudou.
‘The Present’ foi exibido em mais de 180 festivais ao redor do mundo, recebendo mais de 50 prêmios. Com o enorme sucesso, o diretor decidiu disponibilizar o curta em sua página oficial do Vimeo. Assista:
Any body suspended in space will remain in space until made aware of its situation. Daffy Duck steps off a cliff, expecting further pastureland. He loiters in midair, soliloquizing flippantly, until he chances to look down. At this point, the familiar principle of 32 feet per second per second takes over.
Any body in motion will tend to remain in motion until solid matter intervenes suddenly. Whether shot from a cannon or in hot pursuit on foot, cartoon characters are so absolute in their momentum that only a telephone pole or an outsize boulder retards their forward motion absolutely. Sir Isaac Newton called this sudden termination of motion the stooge’s surcease.
Any body passing through solid matter will leave a perforation conforming to its perimeter. Also called the silhouette of passage, this phenomenon is the specialty of victims of directed-pressure explosions and of reckless cowards who are so eager to escape that they exit directly through the wall of a house, leaving a cookie-cutout-perfect hole. The threat of skunks or matrimony often catalyzes this reaction.
The time required for an object to fall twenty stories is greater than or equal to the time it takes for whoever knocked it off the ledge to spiral down twenty flights to attempt to capture it unbroken. Such an object is inevitably priceless, the attempt to capture it inevitably unsuccessful.
There are 10 laws altogether, including “9. Everything falls faster than an anvil.” As early as 1956 Walt Disney was describing the “plausible impossible.” In Who Framed Roger Rabbit, Eddie Valiant says, “Do you mean to tell me you could’ve taken your hand out of that cuff at any time?” Roger answers, “Not at any time! Only when it was funny!”
That title is NOT dig against XKCD. We love XKCD, but XKCD has been one of the top Old Reader feeds almost since our beginning. If you’re not an XKCD reader, we definitely recommend it. But today we want to highlight as many other comics as possible.
To start, we want to point everyone to one of our personal heroes,the anonymous programmer behind ComicSyndicate. If you love newspaper comics like Doonesbury, Foxtrot, or archived Calvin and Hobbes, the comic syndicates that put them online often make them hard to subscribe. Thankfully, the ComicSyndicate has links to put hundreds of syndicated and independent comics in your feed.
Crude line art done in Microsoft Paint about heavy themes including depression and mental illness might not sound like fun reading, but Allie Brosh’s blog is still one of the most interesting and insightful reads online.
The Perry Bible Fellowship is updated irregularly, but delivers beautiful art and dark humor with every new edition.
Not a comic, per se, but if you like funny and clever charts, graphs, and Venn Diagrams on index cards, Indexed is the blog you’ve been waiting for.
Silly, clever, weird, and funny, Tree Lobsters nails all four quadrants.
PHD Comics is obviously written for grad students of the world, but we think it’s funny, too.
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I love it because it's an articulation of a serious argument that I respect but still end up ultimately opposed to.
I've spent a lot of time considering "What should a person do about weird claims?" The stuff that *sounds* like the ideas of a crackpot, but potentially a crackpot so clever that you can't see a hole in his reasoning -- and, also, potentially not a crackpot at all but an insightful, correct thinker. I used to have roughly the same conclusion as you. And roughly the same problem with a tendency to believe the last thing I read, and along with it, a fear of reading things that might delude me.
But the thing is, I've come to the conclusion that it's not actually that hard to make your own judgments about ideas. I was confused about strong AI for a while. What did I do? I read a bunch of papers and textbooks. I talked to my friends who were AI researchers. I still don't *really* know what's going on because I never really learned mathematical logic, but it's a hell of a lot better than a black box. I know *some* mathematics, and I can tell the difference between a proof and a hand-wavy argument, and I've had independent confirmation of the falseness of the ideas I was skeptical about...I'm pretty sure, sure enough to go on with my life, that my picture of "what's up with AI" is more or less accurate.
I'm learning how to do this with biomedical research papers. I am not a biologist so I have to black-box a lot, but not *everything*. I can tell that claims with five conjunctive hypotheses are less likely than claims with one. I can tell when a study was done with 15 subjects or 15,000. I can certainly evaluate statistical methodology. I can come to estimates of my true beliefs -- not high confidence, but not all that biased, and way better than learned helplessness.
I don't go to the trouble of doing this with everything. I haven't checked out climate change skeptics, because I don't know fluid dynamics and I'm a little scared of the work involved in learning. But mostly, my heuristic is, "When confronted with a weird claim that would be really interesting if true and isn't immediately obvious as bullshit, it's worth checking Wikipedia and reading one scholarly paper. If I'm still uncertain and still interested, it's worth reading several more scholarly papers and asking experts I know."
A lot of bunk is not that hard to debunk. I looked through an 1880 book of materia medica (herbal medicine) once; most treatments were not just useless but poisonous, and it took 30 seconds of googling to find that out. (Oil of tansy will *fuck you up*, ladies and gentlemen.)
A good all-purpose scientist can more or less trust his/her bullshit-o-meter. You should know where you're least able to evaluate claims explicitly (for me, that's physics, chemistry, and anything to do with war or foreign policy) and use implicit meta-techniques (were their results reproducible? do they make a lot of conjunctive claims? that sort of thing). But often, I can just *go in and check the math.* Tim Ferriss makes arithmetic errors in his books. You don't have to be a fitness expert to catch them.
I'm no longer afraid of being deluded by charlatans. I wouldn't go to a Scientology meeting, because they engage in physical brainwashing, but I can read racists without becoming a racist, read homeopaths without becoming a homeopath, and so on. I've banged my brain against a *lot* of things, and come out more or less clean.
Maybe not everyone can do this (my education certainly helped a lot), but it is *possible*, and I think most people who are comparably educated and bright (e.g. you) can get better at evaluating weird claims themselves and do better than they would with epistemic learned helplessness.
But I know people with science PhDs who sound as self-aware and confident but they think global warming and Keynesianism are hoaxes and that there's some huge cover-up going on regarding Benghazi and Obama's coming for our guns any day now. (This before the election, so before the Sandy mass shooting.)
>Jonah tells me of a guy in Seattle who is now living according to the principles of Islam
I heard it was Catholicism. (Unless there's a second guy in Seattle who believes in Pascal's Wager and destroying nature to reduce animal suffering, which would be...surprising.) But he's taken down that page on his site, so he might have changed his mind.
I've never met him, but as far as I can tell, he does take his ideas seriously.
I thought I heard Islam...or, actually I think I just inferred he chose Islam from hearing the general story and then a separate comment that he's keeping halal, but he might be a Catholic who keeps halal to hedge his bets.
"Bostrom's simulation argument, the anthropic doomsday argument, Pascal's Mugging "
The doomsday argument doesn't belong on this list. If you follow what Bostrom calls the "self-indication assumption" then the doomsday argument is obviously false. The alternative to the self-indication assumption that Bostrom uses to make the argument seems non-sensical, note for example that if there is another civilization in parallel with the one you care about, the probabilities change using his alternative.
The trouble with rationalist skills is that the opposite of every rationalist skill is also a rationalist skill. We have the Inside View, and the Outside View. Overconfidence is a problem, but so is underconfidence. You're supposed to listen to the tiniest note of mental discord, yet sometimes it's necessary to shut loud mental voices out. And while knowing the standard catalog of biases is obviously crucial for the aspiring rationalist, it can also hurt you. Et cetera, et cetera.
Furthermore, everything exists for a reason -- including things we've decided are bad. Which means that bad things are inevitably -- or at least typically -- going to be good for something, some of the time. Yet they're still bad.
Epistemic learned helplessness may have its uses, but it's certainly not something I would want to celebrate, or -- heaven forbid -- teach. "Normal" people have it by default already, and they already err too much in that direction (to the point, some would argue, of literally killing themselves, e.g. by not signing up for cryonics). I think I'd gladly accept an increased number of homeopaths and terrorists in order to gain an increase in the average rationality of the population as a whole.
"Think for yourself" is still a good meme, despite the fact that for most people it's actually a bad idea and they would do better by just following the right guru. (How do you know which guru is the right one in the first place?)
""Normal" people have it by default already, and they already err too much in that direction (to the point, some would argue, of literally killing themselves, e.g. by not signing up for cryonics). I think I'd gladly accept an increased number of homeopaths and terrorists in order to gain an increase in the average rationality of the population as a whole."
I think your argument that they err too much in that direction requires more support than you give it here. I think if we relaxed the average person's epistemic helpfulness we would get many new terrorists and homeopaths for each new better-than-average person we got.
"When some lines of argument point one way and some another, don't give up or take a vote. Instead, notice that you're confused, and (while guarding against confirmation bias!) seek follow-up information."
Edited at 2013-01-03 02:53 pm (UTC)
Thomas Aquinas deliberately wrote in the flattest style he could muster, so that his errors would not be swept along in rhetorical charms.
I think you're making this into something bigger than it is. Arguments are mental models of reality. Mental models are incredibly error prone. Don't trust a mental model of reality that hasn't been tested against reality. Know how to test a mental model against reality. (Caveat: some mental models are designed such that their flaws are made obvious, like math but not like formal logic with inductive premises.)
In software engineering, this is called unit testing.
Unfortunately, testing against reality is exactly the problem. Usually the evidence gives a certain number of degrees of freedom (which of various conflicting studies you believe were done well vs. poorly, how you interpret evidence, etc).
I agree the questions you can trivially test against reality (like simple physics questions) are the ones that are least vulnerable to crackpottery.
On "destroy nature guy": I've previously had the thought that maybe the world would be a better place with far fewer non-human animals in it. What kept me from exploring this possibility further is that, if I'm honest with myself, I don't care all that much about animal suffering.
To give you a better idea of the extent of my (non-)caring: I care enough to have been a lacto-ovo vegetarian for a few years, but then someone persuaded me that eggs may contribute more to animal suffering than beef, and I said, "okay... I care about animal suffering, but not badly enough to go full vegan" and went back to being an omnivore.
Oops. That was my comment. I failed to select my usual "use Facebook to post" option by accident.
>"If you have a good argument that the Early Bronze Age worked completely differently from the way mainstream historians believe, I just don't want to hear about it."
Hey, wait a minute -- didn't you say somewhere before that you liked reading contrarian arguments?
I'm not sure what exact quote you're thinking of, but it seems plausible. But I mostly like them when I expect to learn something from them, not when I expect to be bewildered by them.
For 99% of the cases you're worried about, I think a better solution than, "don't trust your own reason" is "remember that sound pure *a prior* arguments are very rare, and that believing one person's argument without further investigation is just trusting them to get the empirical stuff right, not only by not saying anything false but also by not omitting relevant evidence."
But it seems we have very different formative experiences in this area. My experiences reading replies and counter-replies with things like the evolution-creationism debate or Christian apologetics more generally is that it does eventually become clear who's right and who's full of shit.
My experiences are similar to celandine13's in this way. I wouldn't necessarily say it's "not that hard," as she does, but "doable eventually with time," yeah.
We may also differ psychologically, in that if I read one thing and *don't* have time to read the replies and counter-replies I find it easy to suspend judgment. Your previous comments about your reluctance to read "Good Calories, Bad Calories" suggest you find this hard, so I'd point out that what you need to do to compensate for that problem doesn't necessarily apply to other people.
The evolution/creation debate is a special case for a few reasons.
First, the prior is so skewed in favor of evolution that it's hard to take creationism seriously. Even on the rare cases there's a superficially good creationist argument (right now this and my uncle's version of irreducible complexity are my two go-to examples of creationists who at least seem to be putting a little effort into their sophistry) I've never been at risk of taking it seriously; I always just think "Wow, these people are quite skilled at sophistry". Other fields where I am less certain of the consensus position do not give me that feeling and so I get less of an advantage from hindsight bias.
Second, there is a really good community of evolutionists, some of them experts in the field, who devote a lot of effort to point-by-point rebuttals of creationist arguments. This is incredibly valuable; some of the better arguments I don't think I would be able to rebut on my own without a daunting amount of work and research. But this is pretty uncommon; real historians rarely address pseudohistorians (Sagan's critique of Velikovsky was a welcome counterexample), and I've never been able to find a mainstream nutritionist really address the paleo people. I am constantly disappointed in the skeptic community, who tend to be domain non-experts in these fields who fail to take them seriously, who just use ad hominems, or who don't even bother to understand the opposing arguments (for example, the number of people who try to tell homeopaths they're wrong because their concoctions don't even have an atom of the active ingredient, even though homeopaths understand this and their theories actually depend upon it, is amazing) So the arguments on many of these topics are very one-sided, which isn't a problem evolution arguments have.
But last of all, I'm surprised you've found Christian apologetics in general to be an easy issue. I've been constantly impressed with tektonics.org, and every time I look at them I end up thinking their defenses of certain Biblical points are much stronger than the atheist attacks upon them (this could be because atheists massively overattack the Bible; the Bible being mostly historically accurate, or not having that many contradictions, is perfectly consistent with religion being wrong in general). The camel issue comes to mind as the last time I had this feeling, although apparently that's not tektonics at all and I might be confusing my apologetics sites.
>Also, he wants to destroy nature in order to decrease animal suffering.
I don't. But I do think that what to do about the "Darwinian holocaust" is a troubling problem for consequentialism.
> (This is the correct Bayesian action, by the way. If I know that a false argument sounds just as convincing as a true argument, argument convincingness provides no evidence either way, and I should ignore it and stick with my prior.)
It's correct, I suspect, only with additional assumptions, like assuming you are either average or above-average so accepting new arguments at random hurts you. If you aren't, then you can do better. For example, if you hold 50% false beliefs, but 90% of arguments you are given are true and 10% are false, and the false are exactly as convincing as the true, then you'll still improve your 50% falsity by ignoring convincingness and believing everything you're told.
It would be a neat trick to acquire 50% false beliefs in an environment where 90% of what you're told is true.
The basic defense against Pascal's Mugging and such is to treat "epsilon" probabilities as equal to zero. So it doesn't matter how severe the offered consequence is since it's getting multiplied by zero anyway.
One of my preferred approaches is construction of a Pascal's Mugging compelling a conflicting course of action. If there's no practical way to judge which "infinity is larger", inaction wins by default.
I very much agree with this post!
Another point that complements yours: people often rationalize to convince themselves of something. People also love to argue and to convince others of things. Smart people are better at this, so they do it more.
So smart people are open to good arguments, because the best arguments they hear are usually their own. They not only lack negative associations from harmful arguments that convinced them in the past, but they have positive associations with arguments they themselves made up, which convinced others.
How high a level did your business friend want to work at? I mean, there's certainly plenty of room to argue about capitalism (I've seen otherwise rational-seeming people passionately arguing that the only possible economic system is free market capitalism, which if done properly is completely impeccable and divinely preserved from all sin - presumably courtesy of the 'invisible hand' - and is the only one true way to liberty, happiness, democracy and all good things) but perhaps your friend just means he wants people who will believe, after being presented with the evidence, that option A is the only one that will work in this situation and that no, it is not because "You don't care about social justice!" or whatever.
Bostrom's simulation argument, the anthropic doomsday argument, Pascal's Mugging - I've never heard anyone give a coherent argument against any of these, but I've also never met anyone who fully accepts them and lives life according to their implications.
When I think about these arguments, I don't actually see how I'd change my life if I believed them, not in any meaningful way.
I actually do believe in Bostrom's simulation argument, in the sense that my prior for that was ~0%, but now it's more like 60%, which is a huge move. How has it changed my life?
It means I can argue with singulitarian atheists in a more entertaining way, by pointing out that if they are in a sim that someone created it, and that someone can be considered our God for all intents and purposes.
But other than debates, I don't think my life is much different. I also don't believe in free will, but there's no particular way to operationalize that belief. (And if there were, could I do it?)
The others are pretty similar. Pascal's Mugging, which I cheerfully fail to believe because human reasoning about morality is completely horrible when the numbers get big, so I don't even try, doesn't effect me in any real way regardless of what I believe. If someone actually tries to pascal's mug me, I think that would be an entertaining novelty.
And I can't think of why the anthropic doomsday argument should change my behavior either, though I'm very suspicious of an argument that would have been just as convincing but totally wrong in recent history.
So what am I missing? If someone believed those things, how could you tell from their behavior?
If you really think you're likely living in a simulation, this essay by Robin Hanson about how you should change your behaviour if you are may interest you.
A most excellent post, that's something I've been thinking about recently too, and I've come to the conclusion that in many cases it's perfectly okay to be close-minded, or to reject an argument without having a good counter-argument. I hadn't made the link with why atheists and skeptics should probably mellow out when making fun of religious people.
I think *everybody* should study crackpots (or at least, everybody who cares about ideas); so that everybody gets a better idea of how it feels to be convinced by bullshit. That would probably increase the crackpots' audience, but on the other hand might make people less likely to turn crackpot.
You could probably make interesting exercises by mixing crackpot arguments and mainstream-but-old arguments (so that they may not use the latest vocabulary), and have a CFAR exercise about distinguishing them.
------
I don't think the simulation argument is *wrong* as much as irrelevant - as for Boltzmann brains, even if it's true my decisions should be the same, so I don't see why I should care. Sure, on one level it's kind of interesting to know that I might be being simulated, but it's not as if it mattered much.
I agree. I was thinking of following this up by posting links to some of the most reasonable-sounding and convincing crackpots who have short, accessible persuasive arguments online. Steven from Black Belt Bayesian linked to this a while back, which is a decent example of the sort of thing I'd be looking for. You have any suggestions?
As for the exercise, I kind of intended my hermeneutics game to work kind of like this, in making it clear how convincing an argument even smart people could come up with for even randomly chosen positions in a short amount of time.
Your story about Velikovsky is pretty much exactly the same as my father's story about reading "Chariots of the Gods".
Logically valid arguments are only sound if the premises are true. Most crackpot arguments are indeed pretty close to valid, but they're not sound because they have a false premise.
Von Daniken is a special case in that AFAIK he actually did completely make up some data (eg he talked about caves with certain artifacts that were just totally imaginary).
Most of the good crackpots I have read avoid that, and are just very good at interpreting real data to fit their theories. Dealing with data-fabricators seems to require a totally new level of paranoia, although luckily convincing ones seem to be rare.
I never found anything by von Daniken at all convincing, and his theme park was kind of a disappointment.
I was confused to notice you assign female gender to the average high school dropout. Normally people default to male gender unless talking about a population dominated by women; I websearched for "high school dropout rates by gender" and the first hit suggests the gender ratio is pretty even. Have you had a different experience?
(Oh -- maybe high school dropouts visiting hospitals are mostly female?)
I assume he was just hewing to the trend of using the female gender pronoun in a gender-neutral sense, and did not mean anything in particular by it.
Everything in this post strikes me as basically correct. The one awful thing I would add is that when most people adopt epistemic learned helplessness, they don't believe it's possible for *anyone* to do better. In particular they don't believe it's possible for you to do better, and that you're stupid for trying, and that if you think you can do better you're claiming social status above theirs, and so on. They have given up on Reason itself, not on their own use of it, and if you try they will smile down upon you superiorly - or for those of a kinder nature, take you aside and give you worried advice about how that whole Reason stuff doesn't actually work. The novice goes astray and says "The Art failed me", the master goes astray and says "I failed my Art".
My father's response would be, basically, that yes, you *can* Do Better, but only if you go to the effort to become an expert in the domain you're trying to form an opinion on - which, on many topics, would take years of study. Being able to present an argument that a smart layperson would find convincing isn't very good Bayesian evidence; being able to present an argument that a fellow expert would find convincing is both a much harder task and is much stronger evidence in favor of the argument's conclusion.
(Also, as far as I can tell, "become an expert yourself" is a bar that you, Eliezer, appear to have met in your own field(s), despite your lack of formal credentials.)
Yeah. I've basically decided my argument-evaluator is likely quite stupid unless and until its results show definite good results of some sort, even aesthetic. Until then it's just being played by other people's superior simulations of me. Many of the stupidest things I've ever done have basically been because I was convinced of something that I later realised was utter tosh.
My first thought upon reading this was the LW post on "Reason as memetic immune disorder (http://lesswrong.com/lw/18b/reason_as_memetic_immune_disorder/)."
Edited at 2013-01-06 01:54 am (UTC)
From:(Anonymous) 2013-01-06 04:00 pm (UTC)
Well, I'm quite glad that you came around to sanity.
A brief remark on the "Even the smartest people I know have a commendable tendency not to take certain ideas seriously. Bostrom's simulation argument, the anthropic doomsday argument, Pascal's Mugging - I've never heard anyone give a coherent argument against any of these, but I've also never met anyone who fully accepts them and lives life according to their implications."
That's because those arguments truly are of bullshit-grade reliability.
E.g. in the simulation argument, you make some very fishy assumptions - such as an assumption that probability of your existence is equal among all copies of 'something like you'. It would be highly likely to be wrong via a mere lack of reason why that would be so - but there's more - you should already start smelling the overpowering stench of bullshit because your conclusion depends on arbitrary and fuzzy choice.
That is far more than sufficient argument to dismiss persuasiveness of simulation argument entirely.
But some people have poor understanding of what is required for dismissal, in the far mode. E.g. they require a persuasive argument in favour of some other set of assumptions. That puts bullshit at too much advantage.
The doomsday argument is even worse in this regard.
The problem with this is that often totally valid conclusions are explained by bullshitting, and due to the social vetting process, people tend to be exposed to a bunch of true conclusions supported by bullshit.
Taking ideas seriously while being ignorant and/or stupid is like driving while intoxicated. Nothing to be glad about. It is a bit difficult to ingrain into people - in their own minds, the drunks are sober...
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It's nice to think one can easily go from being dirt poor to filthy rich, but it doesn't usually work that way.
Of people born into lower income households, few will ever make it into the middle class, according to a recent study from Pew Charitable Trust. Only a tiny percentage rise into the highest income bracket.
Of those that did move into at least the middle class, they had these traits in common:
The report noted a strong correlation between those able to move up the income ladder and family wealth -- having things like home equity, stocks, vehicles and other assets.
Median family wealth of those who made it to middle class was $94,586, while the median wealth of those stuck at the bottom was just $8,892.
While this might seem obvious -- of course people with a higher income will have more wealth -- the report said the two actually feed each other. The higher a family's wealth, the greater ability they have to invest in things like education or job training, which in turn boosts their income.
"Building savings is a tremendous tool for promoting upward mobility but it is largely ignored by policymakers," said Justin King, policy director of the Asset Building Program at the New America Foundation.
King said that while the government promotes wealth building for some -- largely through the mortgage tax deduction and other tax loopholes used mainly by the middle and upper class -- it actually discourages wealth building for the poor. Many government assistance programs take wealth into account when determining eligibility.
"They have to trade their long-term well-being for short-term assistance," he said.
The Pew data is from a study that has followed families since 1968. It uses 2009 numbers.
Lesser Beasts (Essig) A fun little book on the history of the relationship between humans and pigs. The use of pigs as a tool for conquest (really!) was especially interesting.
Weapons of Math Destruction (O’Neil) This is a great book. O'Neil is a mathematician who went to finance and was appalled by some of the things she saw. The topic of the book in particular is the way we create mathematical models and then become beholden to their weird results, in many areas ranging from finance to education.
We (Zamyatin) A really interesting novel, written in the 1920s, and which may be an early entry in the genre we now think of as Orwellian dystopia. It's one of those books that's both an enjoyable read and an interesting look into historical views of the organization of society.
Arms and the Man (Lowther) Probably the best book on Gerald Bull, whose life I've been really into lately.
The Mind Club (Wegner, Gray) Another great book! This is a book on the philosophy and neuroscience that goes into how humans decided what counts as a conscious mind, and what creatures thereby derive ethical rights. It's not just reporting on what scientists and philosophers think, either - this is a theoretical framework for how we make those judgments.
Dmytry Lavrov
Of those that did move into at least the middle class, they had these traits in common:
