Distinguishing Copenhagen and Many Worlds via experiment

Peter McCluskey pointed me to a nice explanation by Brian Greene of an experiment that could theoretically distinguish the Copenhagen and Many Worlds interpretations of quantum mechanics. This is from The Hidden Reality, ch. 8, endnote 12:

Here is a concrete in-principle experiment for distinguishing the Copenhagen and Many Worlds approaches. An electron, like all other elementary particles, has a property known as spin. Somewhat as a top can spin about an axis, an electron can too, with one significant difference being that the rate of this spin—regardless of the direction of the axis—is always the same. It is an intrinsic property of the electron, like its mass or its electrical charge. The only variable is whether the spin is clockwise or counterclockwise about a given axis. If it is counterclockwise, we say the electron’s spin about that axis is up; if it is clockwise, we say the electron’s spin is down. Because of quantum mechanical uncertainty, if the electron’s spin about a given axis is definite—say, with 100 percent certainty its spin is up about the z-axis—then its spin about the x- or y-axis is uncertain: about the x-axis the spin would be 50 percent up and 50 percent down; and similarly for the y-axis.

Imagine, then, starting with an electron whose spin about the z-axis is 100 percent up and then measuring its spin about the x-axis. According to the Copenhagen approach, if you find spin-down, that means the probability wave for the electron’s spin has collapsed: the spin-up possibility has been erased from reality, leaving the sole spike at spin-down. In the Many Worlds approach, by contrast, both the spin-up and spin-down outcomes occur, so, in particular, the spin-up possibility survives fully intact.

To adjudicate between these two pictures, imagine the following. After you measure the electron’s spin about the x-axis, have someone fully reverse the physical evolution. (The fundamental equations of physics, including that of Schrödinger, are time-reversal invariant, which means, in particular, that, at least in principle, any evolution can be undone. See The Fabric of the Cosmos for an in-depth discussion of this point.) Such reversal would be applied to everything: the electron, the equipment, and anything else that’s part of the experiment. Now, if the Many Worlds approach is correct, a subsequent measurement of the electron’s spin about the z-axis should yield, with 100 percent certainty, the value with which we began: spin-up. However, if the Copenhagen approach is correct (by which I mean a mathematically coherent version of it, such as the Ghirardi-Rimini-Weber formulation), we would find a different answer. Copenhagen says that upon measurement of the electron’s spin about the x-axis, in which we found spin-down, the spin-up possibility was annihilated. It was wiped off reality’s ledger. And so, upon reversing the measurement we don’t get back to our starting point because we’ve permanently lost part of the probability wave. Upon subsequent measurement of the electron’s spin about the z-axis, then, there is not 100 percent certainty that we will get the same answer we started with. Instead, it turns out that there’s a 50 percent chance that we will and a 50 percent chance that we won’t. If you were to undertake this experiment repeatedly, and if the Copenhagen approach is correct, on average, half the time you would not recover the same answer you initially did for the electron’s spin about the z-axis. The challenge, of course, is in carrying out the full reversal of a physical evolution. But, in principle, this is an experiment that would provide insight into which of the two theories is correct.

I’m not a physicist, and I don’t know whether this account is correct. Does anyone dispute it?

Further references on the subject are at Wikipedia.

In any case, such an experiment seems far beyond our reach. But since I’m Bayesian rather than Popperian, I put substantially more probability mass on MWI than Copenhagen even in the absence of definitive experiment. 😉

Lessons from Poor Economics

Poor Economics is the best book I’ve read on poverty reduction. The book ends with a summary of its key lessons. Here they are:

As this book has shown, although we have no magic bullets to eradicate poverty, no one-shot cure-all, we do know a number of things about how to improve the lives of the poor. In particular, five key lessons emerge.

First, the poor often lack critical pieces of information and believe things that are not true. They are unsure about the benefits of immunizing children; they think there is little value in what is learned during the first few years of education; they don’t know how much fertilizer they need to use; they don’t know which is the easiest way to get infected with HIV; they don’t know what their politicians do when in office. When their firmly held beliefs turn out to be incorrect, they end up making the wrong decision, sometimes with drastic consequences — think of the girls who have unprotected sex with older men or the farmers who use twice as much fertilizer as they should. Even when they know that they don’t know, the resulting uncertainty can be damaging. For example, the uncertainty about the benefits of immunization combines with the universal tendency to procrastinate, with the result that a lot of children don’t get immunized. Citizens who vote in the dark are more likely to vote for someone of their ethnic group, at the cost of increasing bigotry and corruption.

We saw many instances in which a simple piece of information makes a big difference. However, not every information campaign is effective. It seems that in order to work, an information campaign must have several features: It must say something that people don’t already know (general exhortations like “No sex before marriage” seem to be less effective); it must do so in an attractive and simple way (a film, a play, a TV show, a well-designed report card); and it must come from a credible source (interestingly, the press seems to be viewed as credible). One of the corollaries of this view is that governments pay a huge cost in terms of lost credibility when they say things that are misleading, confusing, or false.

Second, the poor bear responsibility for too many aspects of their lives. The richer you are, the more the “right” decisions are made for you. The poor have no piped water, and therefore do not benefit from the chlorine that the city government puts into the water supply. If they want clean drinking water, they have to purify it themselves. They cannot afford ready-made fortified breakfast cereals and therefore have to make sure that they and their children get enough nutrients. They have no automatic way to save, such as a retirement plan or a contribution to Social Security, so they have to find a way to make sure that they save. These decisions are difficult for everyone because they require some thinking now or some other small cost today, and the benefits are usually reaped in the distant future. As such, procrastination very easily gets in the way. For the poor, this is compounded by the fact that their lives are already much more demanding than ours: Many of them run small businesses in highly competitive industries; most of the rest work as casual laborers and need to constantly worry about where their next job will come from. This means that their lives could be significantly improved by making it as easy as possible to do the right thing — based on everything else we know — using the power of default options and small nudges: Salt fortified with iron and iodine could be made cheap enough that everyone buys it. Savings accounts, the kind that make it easy to put in money and somewhat costlier to take it out, can be made easily available to everyone, if need be, by subsidizing the cost for the bank that offers them. Chlorine could be made available next to every source where piping water is too expensive. There are many similar examples.

Third, there are good reasons that some markets are missing for the poor, or that the poor face unfavorable prices in them. The poor get a negative interest rate from their savings accounts (if they are lucky enough to have an account) and pay exorbitant rates on their loans (if they can get one) because handling even a small quantity of money entails a fixed cost. The market for health insurance for the poor has not developed, despite the devastating effects of serious health problems in their lives because the limited insurance options that can be sustained in the market (catastrophic health insurance, formulaic weather insurance) are not what the poor want.

In some cases, a technological or an institutional innovation may allow a market to develop where it was missing. This happened in the case of microcredit, which made small loans at more affordable rates available to millions of poor people, although perhaps not the poorest. Electronic money transfer systems (using cell phones and the like) and unique identification for individuals may radically cut the cost of providing savings and remittance services to the poor over the next few years. But we also have to recognize that in some cases, the conditions for a market to emerge on its own are simply not there. In such cases, governments should step in to support the market to provide the necessary conditions, or failing that, consider providing the service themselves.

We should recognize that this may entail giving away goods or services (such as bed nets or visits to a preventive care center) for free or even rewarding people, strange as it might sound, for doing things that are good for them. The mistrust of free distribution of goods and services among various experts has probably gone too far, even from a pure cost-benefit point of view. It often ends up being cheaper, per person served, to distribute a service for free than to try to extract a nominal fee. In some cases, it may involve ensuring that the price of a product sold by the market is attractive enough to allow the market to develop. For example, governments could subsidize insurance premiums, or distribute vouchers that parents can take to any school, private or public, or force banks to offer free “no frills” savings accounts to everyone for a nominal fee. It is important to keep in mind that these subsidized markets need to be carefully regulated to ensure they function well. For example, school vouchers work well when all parents have a way of figuring out the right school for their child; otherwise, they can turn into a way of giving even more of an advantage to savvy parents.

Fourth, poor countries are not doomed to failure because they are poor, or because they have had an unfortunate history. It is true that things often do not work in these countries: Programs intended to help the poor end up in the wrong hands, teachers teach desultorily or not at all, roads weakened by theft of materials collapse under the weight of overburdened trucks, and so forth. But many of these failures have less to do with some grand conspiracy of the elites to maintain their hold on the economy and more to do with some avoidable flaw in the detailed design of policies, and the ubiquitous three Is: ignorance, ideology, and inertia. Nurses are expected to carry out jobs that no ordinary human being would be able to complete, and yet no one feels compelled to change their job description. The fad of the moment (be it dams, barefoot doctors, microcredit, or whatever) is turned into a policy without any attention to the reality within which it is supposed to function. We were once told by a senior government official in India that the village education committees always include the parent of the best student in the school and the parent of the worst student in the school. When we asked how they decided who were the best and worst children, given that there are no tests until fourth grade, she quickly changed subjects. And yet even these absurd rules, once in place, keep going out of sheer inertia.

The good news, if that is the right expression, is that it is possible to improve governance and policy without changing the existing social and political structures. There is tremendous scope for improvement even in “good” institutional environments, and some margin for action even in bad ones. A small revolution can be achieved by making sure that everyone is invited to village meetings; by monitoring government workers and holding them accountable for failures in performing their duties; by monitoring politicians at all levels and sharing this information with voters; and by making clear to users of public services what they should expect—what the exact health center hours are, how much money (or how many bags of rice) they are entitled to.

Finally, expectations about what people are able or unable to do all too often end up turning into self-fulfilling prophecies. Children give up on school when their teachers (and sometimes their parents) signal to them that they are not smart enough to master the curriculum; fruit sellers don’t make the effort to repay their debt because they expect that they will fall back into debt very quickly; nurses stop coming to work because nobody expects them to be there; politicians whom no one expects to perform have no incentive to try improving people’s lives. Changing expectations is not easy, but it is not impossible: After seeing a female pradhan in their village, villagers not only lost their prejudice against women politicians but even started thinking that their daughter might become one, too; teachers who are told that their job is simply to make sure that all the children can read can accomplish that task within the duration of a summer camp. Most important, the role of expectations means that success often feeds on itself. When a situation starts to improve, the improvement itself affects beliefs and behavior. This is one more reason one should not necessarily be afraid of handing things out (including cash) when needed to get a virtuous cycle started.

Stewart and Dawkins on the unintended consequences of powerful technologies

Richard Dawkins and Jon Stewart discussed existential risk on the Sept. 24, 2013 edition of The Daily Show. Here’s how it went down:

STEWART: Here’s my proposal… for the discussion tonight. Do you believe that the end of our civilization will be through religious strife or scientific advancement? What do you think in the long run will be more damaging to our prospects as a human race?

In reply, Dawkins said that Martin Rees (of CSER) thinks humanity has a 50% chance of surviving the 21st century, and one cause for such worry is that powerful technologies could get into the hands of religious fanatics. Stewart replied:

STEWART: … [But] isn’t there a strong probability that we are not necessarily in control of the unintended consequences of our scientific advancement?… Don’t you think it’s even more likely that we will create something [for which] the unintended consequence… is worldwide catastrophe?

DAWKINS: That is possible. It’s something we have to worry about… Science is the most powerful way to do whatever you want to do. If you want to do good, it’s the most powerful way to do good. If you want to do evil, it’s the most powerful way to do evil.

STEWART: … You have nuclear energy and you go this way and you can light the world, but you go this [other] way, and you can blow up the world. It seems like we always try [the blow up the world path] first.

DAWKINS: There is a suggestion that one of the reasons that we don’t detect extraterrestrial civilizations is that when a civilization reaches the point where it could broadcast radio waves that we could pick up, there’s only a brief window before it blows itself up… It takes many billions of years for evolution to reach the point where technology takes off, but once technology takes off, it’s then an eye-blink — by the standards of geological time — before…

STEWART: … It’s very easy to look at the dark side of fundamentalism… [but] sometimes I think we have to look at the dark side of achievement… because I believe the final words that man utters on this Earth will be: “It worked!” It’ll be an experiment that isn’t misused, but will be a rolling catastrophe.

DAWKINS: It’s a possibility, and I can’t deny it. I’m more optimistic than that.

STEWART: … [I think] curiosity killed the cat, and the cat never saw it coming… So how do we put the brakes on our ability to achieve, or our curiosity?

DAWKINS: I don’t think you can ever really stop the march of science in the sense of saying “You’re forbidden to exercise your natural curiosity in science.” You can certainly put the brakes on certain applications. You could stop manufacturing certain weapons. You could have… international agreements not to manufacture certain types of weapons…

Bostrom’s unfinished fable of the sparrows

SuperintelligenceNick Bostrom’s new book — Superintelligence: Paths, Dangers, Strategies — was published today in the UK by Oxford University Press. It opens with a fable about some sparrows and an owl:

It was the nest-building season, but after days of long hard work, the sparrows sat in the evening glow, relaxing and chirping away.

“We are all so small and weak. Imagine how easy life would be if we had an owl who could help us build our nests!”

“Yes!” said another. “And we could use it to look after our elderly and our young.”

“It could give us advice and keep an eye out for the neighborhood cat,” added a third.

Then Pastus, the elder-bird, spoke: “Let us send out scouts in all directions and try to find an abandoned owlet somewhere, or maybe an egg. A crow chick might also do, or a baby weasel. This could be the best thing that ever happened to us, at least since the opening of the Pavilion of Unlimited Grain in yonder backyard.”

The flock was exhilarated, and sparrows everywhere started chirping at the top of their lungs.

Only Scronkfinkle, a one-eyed sparrow with a fretful temperament, was unconvinced of the wisdom of the endeavor. Quoth he: “This will surely be our undoing. Should we not give some thought to the art of owl-domestication and owl-taming first, before we bring such a creature into our midst?”

Replied Pastus: “Taming an owl sounds like an exceedingly difficult thing to do. It will be difficult enough to find an owl egg. So let us start there. After we have succeeded in raising an owl, then we can think about taking on this other challenge.”

“There is a flaw in that plan!” squeaked Scronkfinkle; but his protests were in vain as the flock had already lifted off to start implementing the directives set out by Pastus.

Just two or three sparrows remained behind. Together they began to try to work out how owls might be tamed or domesticated. They soon realized that Pastus had been right: this was an exceedingly difficult challenge, especially in the absence of an actual owl to practice on. Nevertheless they pressed on as best they could, constantly fearing that the flock might return with an owl egg before a solution to the control problem had been found.

It is not known how the story ends, but the author dedicates this book to Scronkfinkle and his followers.

For some ideas of what Scronkfinkle and his friends can work on before the others return with an owl egg, see here and here.

The Antikythera Mechanism

From Murray’s Human Accomplishment:

The problem with the standard archaeological account of human accomplishment from [the ancient world] is not that the picture is incomplete (which is inevitable), but that the data available to us leave so many puzzles.

The Antikythera Mechanism is a case in point… The Antikythera Mechanism is a bronze device about the size of a brick. It was recovered in 1901 from the wreck of a trading vessel that had sunk near the southern tip of Greece sometime around –65. Upon examination, archaeologists were startled to discover imprints of gears in the corroded metal. So began a half-century of speculation about what purpose the device might have served.

Finally, in 1959, science historian Derek de Solla Price figured it out: the Antikythera Mechanism was a mechanical device for calculating the positions of the sun and moon. A few years later, improvements in archaeological technology led to gamma radiographs of the Mechanism, revealing 22 gears in four layers, capable of simulating several major solar and lunar cycles, including the 19-year Metonic cycle that brings the phases of the moon back to the same calendar date. What made this latter feat especially astonishing was not just that the Mechanism could reproduce the 235 lunations in the Metonic cycle, but that it used a differential gear to do so. Until then, it was thought that the differential gear had been invented in 1575.

See also Wikipedia.

Stanovich on intelligence enhancement

From Stanovich’s popular book on the distinction between rationality and intelligence (p. 196):

In order to illustrate the oddly dysfunctional ways that rationality is devalued in comparison to intelligence…  Baron asks us to imagine what would happen if we were able to give everyone an otherwise harmless drug that increased their algorithmic-level cognitive capacities (for example, discrimination speed, working memory capacity, decoupling ability) — in short, that increased their intelligence…

Imagine that everyone in North America took the pill before retiring and then woke up the next morning with more memory capacity and processing speed. Both Baron and I believe that there is little likelihood that much would change the next day in terms of human happiness. It is very unlikely that people would be better able to fulfill their wishes and desires the day after taking the pill. In fact, it is quite likely that people would simply go about their usual business-only more efficiently. If given more memory capacity and processing speed, people would, I believe: carry on using the same ineffective medical treatments because of failure to think of alternative causes (Chapter 10); keep making the same poor financial decisions because of overconfidence (Chapter 8); keep misjudging environmental risks because of vividness (Chapter 6); play host to the contaminated mindware of Ponzi and pyramid schemes (Chapter 11); be wrongly influenced in their jury decisions by incorrect testimony about probabilities (Chapter 10); and continue making many other of the suboptimal decisions described in earlier chapters. The only difference would be that they would be able to do all of these things much more quickly!

This is part of why it’s not obvious to me that radical intelligence amplification (e.g. via IES) would increase rather than decrease our odds of surviving future powerful technologies.

Elsewhere (p. 171), Stanovich notes:

Mensa is a club restricted to high-IQ individuals, and one must pass IQ-type tests to be admitted. Yet 44 percent of the members of this club believed in astrology, 51 percent believed in biorhythms, and 56 percent believed in the existence of extraterrestrial visitors-all beliefs for which there is not a shred of evidence.

Nicely put, FHI

Re-reading Ross Andersen’s piece on Nick Bostrom and FHI for Aeon magazine, I was struck by several nicely succinct explanations given by FHI researchers — ones which I’ll borrowing for my own conversations with people about these topics:

“There is a concern that civilisations might need a certain amount of easily accessible energy to ramp up,” Bostrom told me. “By racing through Earth’s hydrocarbons, we might be depleting our planet’s civilisation startup-kit. But, even if it took us 100,000 years to bounce back, that would be a brief pause on cosmic time scales.”

“Human brains are really good at the kinds of cognition you need to run around the savannah throwing spears,” Dewey told me. “But we’re terrible at [many other things]… Think about how long it took humans to arrive at the idea of natural selection. The ancient Greeks had everything they needed to figure it out. They had heritability, limited resources, reproduction and death. But it took thousands of years for someone to put it together. If you had a machine that was designed specifically to make inferences about the world, instead of a machine like the human brain, you could make discoveries like that much faster.”

“The difference in intelligence between humans and chimpanzees is tiny,” [Armstrong] said. “But in that difference lies the contrast between 7 billion inhabitants and a permanent place on the endangered species list. That tells us it’s possible for a relatively small intelligence advantage to quickly compound and become decisive.”

“The basic problem is that the strong realisation of most motivations is incompatible with human existence,” Dewey told me. “An AI might want to do certain things with matter in order to achieve a goal, things like building giant computers, or other large-scale engineering projects. Those things might involve intermediary steps, like tearing apart the Earth to make huge solar panels. A superintelligence might not take our interests into consideration in those situations, just like we don’t take root systems or ant colonies into account when we go to construct a building.”

[Bostrom] told me that when he was younger, he was more interested in the traditional philosophical questions… “But then there was this transition, where it gradually dawned on me that not all philosophical questions are equally urgent,” he said. “Some of them have been with us for thousands of years. It’s unlikely that we are going to make serious progress on them in the next ten. That realisation refocused me on research that can make a difference right now. It helped me to understand that philosophy has a time limit.”

Why Engines before Nanosystems?

After Drexler published his 1981 nanotech paper in PNAS, and after it received some positive followups in Nature and in Science in 1983, why did Drexler next write a popular book like Engines of Creation (1986) instead of a technical account like Nanosystems (1992)? Ed Regis writes in Nano (p. 118):

The logical next step for Drexler… was to produce a full-blown account of his molecular-engineering scheme, a technical document that fleshed out the whole story in chapter and verse, with all the technical details. That was the obvious thing to do, anyway, if he wanted to convince the greater science and engineering world that molecular engineering was a real prospect and not just his own private fantasy.

… Drexler instead did something else, spending the next four years, essentially, writing a popular account of the subject in his book, Engines of Creation.

For a dyed-in-the-wool engineer such as himself, this was somewhat puzzling. Why go public with a scheme as wild and woolly as this one before the technical details were even passably well worked out? Why paint vivid word pictures of “the coming era of nanotechnology” before even so much as one paltry designer protein had been coaxed, tricked, or forced into existence? Why not nail down an ironclad scientific case for the whole thing first, and only then proceed to advertise its benefits?

Of course, there were answers. For one thing, Drexler was convinced that he’d already done enough in his PNAS piece to motivate a full course of research-and-development work in academia and industry. After all, he’d described what was possible at the molecular level and by what means, and he’d said what some of the benefits were. How could a bunch of forward-looking researchers, seeing all this, not go ahead and actually do it?…

The other reason for writing a popular book on the subject was to raise some of the economic and social issues involved. Scientists and engineers, it was commonly observed, did not have an especially good track record when it came to assessing the wider impact of what they’d wrought in the lab. Their attitude seemed to be: “We invent it, you figure out what to do with it.”

To Drexler, that was the height of social irresponsibility, particularly where nanotechnology was concerned, because its impacts would be so broad and sweeping…

If anything was clear to Eric Drexler, it was that if the human race was to survive the transition to the nanotech era, it would have to do a bit of thinking beforehand. He’d have to write the book on this because, all too obviously, nobody else was about to.

But there was yet a third reason for writing Engines of Creation, a reason that was, for Drexler, probably the strongest one of all. This was to announce to the world at large that the issue of “limits” [from Limits to Growth] had been addressed head-on…

It’s hard to contain information hazards

Laurie Garrett’s Foreign Affairs piece on synbio from a while back exaggerates the state of current progress, but it also contains some good commentary on the difficulty of containing hazardous materials when those hazardous materials — unlike the case of nuclear fissile materials — are essentially information:

Fouchier and Kawaoka drew the wrath of many national security and public health experts, who demanded to know how the deliberate creation of potential pandemic flu strains could possibly be justified… the National Science Advisory Board for Biosecurity… [ordered] that the methods used to create these new mammalian forms of H5N1 never be published. “It’s not clear that these particular [experiments] have created something that would destroy the world; maybe it’ll be the next set of experiments that will be critical,” [Paul] Keim told reporters. “And that’s what the world discussion needs to be about.”

In the end, however, the December 2011 do-not-publish decision… was reversed… [and] both papers were published in their entirety by Science and Nature in 2012, and [the] temporary moratorium on dual-use research on influenza viruses was eventually lifted… Osterholm, Keim, and most of the vocal opponents of the work retreated, allowing the advisory board to step back into obscurity.

… What stymies the very few national security and law enforcement experts closely following this biological revolution is the realization that the key component is simply information. While virtually all current laws in this field, both local and global, restrict and track organisms of concern (such as, say, the Ebola virus), tracking information is all but impossible. Code can be buried anywhere — al Qaeda operatives have hidden attack instructions inside porn videos, and a seemingly innocent tweet could direct readers to an obscure Internet location containing genomic code ready to be downloaded to a 3-D printer. Suddenly, what started as a biology problem has become a matter of information security.

See also Bostrom, “Information Hazards” (2011).

MIRI’s original environmental policy

Somehow MIRI’s mission comes in at #10 on this list of 10 responses to the technological unemployment problem.

I suppose technically, Friendly AI is a solution for all the things. 🙂

This reminds me of the first draft of MIRI’s environmental policy, which read:

[MIRI] exists to ensure that the creation of smarter than human intelligence benefits society. Because societies depend on their environment to thrive, one implication of our core mission is a drive to ensure that when advanced intelligence technologies become available, they are used to secure the continued viability and resilience of the environment.

Many advanced artificial intelligences (AIs) will have instrumental goals to capture as many resources as possible for their own use, because resources are useful for a broad range of possible AI goals. To ensure that Earth’s resources are used wisely despite the creation of advanced AIs, we must discover how to design these AIs so that they can be given final goals which accord with humane values.

Though poorly designed AIs may pose a risk to the resources and environment on which humanity depends, more carefully designed AIs may be our best solution to long-term environmental concerns. To whatever extent we have goals for environmental sustainability, they are goals that can be accomplished to greater degrees using sufficiently advanced intelligence.

To prevent environmental disasters caused by poorly designed AIs, and to ensure that we one day have the intelligence needed to solve our current environmental dilemmas, [MIRI] is committed to discovering the principles of safe, beneficial AI that will one day allow us all to safeguard our environment as well as our future.

In the end, though, we decided to go with a more conventional (super-boring) environmental policy, available here.

Another Cold War close call

From The Limits of Safety (p. 1):

On the night of October 25, 1962, an air force sentry was patrolling the perimeter of a military base near Duluth, Minnesota. It was the height of the Cuban missile crisis, and nuclear-armed bombers and interceptor aircraft, parked on air base runways and at commercial airports throughout the United States, were alert and ready for war. The sentry spotted someone climbing the fence, shot at the figure, and sounded the sabotage alarm. At airfields throughout the region, alarms went off, and armed guards rushed into the cold night to prevent Soviet agents from sabotaging U.S. nuclear forces.

At Volk Field in Wisconsin, however, the wrong alarm bell rang: the Klaxon signalling that nuclear had begun went off. Pilots ran to their nuclear-armed interceptors and started the engines. These men had been told that there would be no practice alert drills during the tense crisis, and they fully believed that a nuclear war was starting as they headed down the runway. Fortunately, the base commander contacted Duluth before the planes took off and discovered what had happened. An officer in the command post immediately drove his car onto the runway, flashing his lights and signaling the interceptors. The pilots saw him and stopped their aircraft. The suspected Soviet saboteur that caused the whole incident was, ironically, a bear.

 

Two innovative strategies in sports

From Gladwell’s David and Goliath:

A regulation basketball court is ninety-four feet long. Most of the time, a team would defend only about twenty-four feet of that, conceding the other seventy feet. Occasionally teams played a full-court press—that is, they contested their opponent’s attempt to advance the ball up the court. But they did it for only a few minutes at a time. It was as if there were a kind of conspiracy in the basketball world about the way the game ought to be played, Ranadivé thought, and that conspiracy had the effect of widening the gap between good teams and weak teams. Good teams, after all, had players who were tall and could dribble and shoot well; they could crisply execute their carefully prepared plays in their opponent’s end. Why, then, did weak teams play in a way that made it easy for good teams to do the very things that they were so good at?

Ranadivé looked at his girls. Morgan and Julia were serious basketball players. But Nicky, Angela, Dani, Holly, Annika, and his own daughter, Anjali, had never played the game before. They weren’t all that tall. They couldn’t shoot. They weren’t particularly adept at dribbling. They were not the sort who played pickup games at the playground every evening. Ranadivé lives in Menlo Park, in the heart of California’s Silicon Valley. His team was made up of, as Ranadivé put it, “little blond girls.” These were the daughters of nerds and computer programmers. They worked on science projects and read long and complicated books and dreamed about growing up to be marine biologists. Ranadivé knew that if they played the conventional way—if they let their opponents dribble the ball up the court without opposition—they would almost certainly lose to the girls for whom basketball was a passion. Ranadivé had come to America as a seventeen-year-old with fifty dollars in his pocket. He was not one to accept losing easily. His second principle, then, was that his team would play a real full-court press—every game, all the time. The team ended up at the national championships. “It was really random,” Anjali Ranadivé said. “I mean, my father had never played basketball before.”

From Brafman’s Sway:

The most flattering way to describe the Gator [football] team upon Spurrier’s arrival in 1990 was as a “fixer-upper.” The team had never won a conference title; in fact, it was on probation because of allegations of rule violations by the team’s former coach.

… Spurrier’s most important move was to identify a weak spot in the strategy employed by his opponents. For year the teams in the conference had adhered to a “war of attrition” game strategy: they called conservative plays and held on to the ball for as long as they could, hoping to win a defensive battle…

… Spurrier came to dominate the conference by… introducing what he called the ‘Fun-n-Gun” approach…

Spurrier mixed things up with a generous helping of “big chance plays, where you got to give your players a shot.” In other words, Spurrier’s team passed more often, played more aggressively, and tried to score more touchdowns.

..Spurrier gained an advantage because the other coaches were focused on trying to avoid a potential loss. Think of what it’s like to be a college football coach. As you walk around town, passing fans offer themselves up as instant experts on the game — never afraid to give you a piece of their minds on what you did wrong in yesterday’s match-up. You make one bad move and you get skewered by fans and commentators alike. Meanwhile, ticcket sale revenues, your school’s alumni fundraising, and your job all depend heavily on the football team’s success. All of that pressure adds up… the losses loom large…

You’d have thought that after losing a few games to a team like [the Gators]… the [other] coaches would have reevaluated their war-of-attrition model. But they didn’t. And so Spurrier and his Gators continued to dominate former powerhouses like Alabama, Tennessee, and Auburn. Over the next six years, the coach and his team went on to win four division titles, culminating in the national championship.

Feynman on dealing with nanotechnology risks

Nano (p. 113) quotes Eric Drexler describing the time he first met Richard Feynman at a party:

We talked about the PNAS article [on nanotechnology], and generally he indicated that, yeah, this was a sensible thing… at one point I was talking about the need for institutions to handle some of the problems [nanotechnology] raised, and [Feynman] remarked [that] institutions were made up of people and therefore of fools.

Feynman sounds downright Yudkowskian on this point, if you ask me. 🙂