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General Discussion / If minimum wages, why not maximum wages?
« on: July 29, 2014, 09:09:02 AM »
I was in a gathering of academics the other day, and we were discussing minimum wages. The debate moved on to increasing inequality, and the difficulty of doing anything about it. I said why not have a maximum wage? To say that the idea was greeted with incredulity would be an understatement. So you want to bring back price controls was once response. How could you possibly decide on what a maximum wage should be was another.

So why the asymmetry? Why is the idea of setting a maximum wage considered outlandish among economists?

The problem is clear enough. All the evidence, in the US and UK, points to the income of the top 1% rising much faster than the average. Although the share of income going to the top 1% in the UK fell sharply in 2010, the more up to date evidence from the US suggests this may be a temporary blip caused by the recession. The latest report from the High Pay Centre in the UK says:

“Typical annual pay for a FTSE 100 CEO has risen from around £100-£200,000 in the early 1980s to just over £1 million at the turn of the 21st century to £4.3 million in 2012. This represented a leap from around 20 times the pay of the average UK worker in the 1980s to 60 times in 1998, to 160 times in 2012 (the most recent year for which full figures are available).”

I find the attempts of some economists and journalists to divert attention away from this problem very revealing. The most common tactic is to talk about some other measure of inequality, whereas what is really extraordinary and what worries many people is the rise in incomes at the very top. The suggestion that we should not worry about national inequality because global inequality has fallen is even more bizarre.

What lies behind this huge increase in inequality at the top? The problem with the argument that it just represents higher productivity of CEOs and the like is that this increase in inequality is much more noticeable in the UK and US than in other countries, yet there is no evidence that CEOs in UK and US based firms have been substantially outperforming their overseas rivals. I discussed in this post a paper by Piketty, Saez and Stantcheva which set out a bargaining model, where the CEO can put more or less effort into exploiting their monopoly power within a company. According to this model, CEOs in the UK and US have since 1980 been putting more bargaining effort than their overseas counterparts. Why? According to Piketty et al, one answer may be that top tax rates fell in the 1980s in both countries, making the returns to effort much greater.

If you believe this particular story, then one solution is to put top tax rates back up again. Even if you do not buy this story, the suspicion must be that this increase in inequality represents some form of market failure. Even David Cameron agrees. The solution the UK government has tried is to give more power to the shareholders of the firm. The High Pay Centre notes that: “Thus far, shareholders have not used their new powers to vote down executive pay proposals at a single FTSE 100 company.”, although as the FT report shareholder ‘revolts’ are becoming more common. My colleague Brian Bell and John Van Reenen do note in a recent study “that firms with a large institutional investor base provide a symmetric pay-performance schedule while those with weak institutional ownership protect pay on the downside.” However they also note that “a specific group of workers that account for the majority of the gains at the top over the last decade [are] financial sector workers .. [and] .. the financial crisis and Great Recession have left bankers largely unaffected.”

So increasing shareholder power may only have a small effect on the problem. So why not consider a maximum wage? One possibility is to cap top pay as some multiple of the lowest paid, as a recent Swiss referendum proposed. That referendum was quite draconian, suggesting a multiple of 12, yet it received a large measure of popular support (35% in favour, 65% against). The Swiss did vote to ban ‘golden hellos and goodbyes’. One neat idea is to link the maximum wage to the minimum wage, which would give CEOs an incentive to argue for higher minimum wages! Note that these proposals would have no disincentive effect on the self-employed entrepreneur.

If economists have examined these various possibilities, I have missed it. One possible reason why many economists seem to baulk at this idea is that it reminds them too much of the ‘bad old days’ of incomes policies and attempts by governments to fix ‘fair wages’. But this is an overreaction, as a maximum wage would just be the counterpart to the minimum wage. I would be interested in any other thoughts about why the idea of a maximum wage seems not to be part of economists’ Overton window.

from economist Simon Wren Lewis's blog

Germany is the global leader in energy efficiency, and the U.S., with its ingrained car culture, is among the least energy efficient of the world’s largest economies.

That’s the conclusion of a new report released by the American Council for an Energy-Efficient Economy, which ranks the world’s 16 largest economies based on 31 different measurements of efficiency, including national energy savings targets, fuel economy standards for vehicles, efficiency standards for appliances, average vehicle mpg, and energy consumed per square foot of floor space in residential buildings, among other metrics.

The ACEEE report ranked the U.S. 13th overall, with Germany, Italy, smaller European Union nations, France and China making up the top five most energy efficient economies in the world.

Using energy more efficiently is a critical step countries can take to reduce their fossil fuels consumption and its related climate change-driving carbon dioxide and methane emissions. The U.S. Environmental Protection Agency used state energy efficiency standards to help set CO2 emissions reductions goals for each state in the agency’s proposed Clean Power Plan, announced in June.

The U.S. was the 9th most energy-efficient economy in the ACEEE’s 2012 ranking, which criticized the country for focusing more on road construction than expanding public transportation.

Since then, the U.S. has made very little progress toward using energy more efficiently, the 2014 report says.This year, the U.S. took a major hit for its lack of a national energy savings plan or national greenhouse gas reduction plan, and its ongoing resistance to public transit.

Americans drive more than 9,300 miles per year, more than citizens in any other major world economy, according to the report. Australians, ranking second-to-last for annual per-capita vehicle miles traveled, drive 6,368 miles per year. India tops the list, driving 85 miles per year per capita, followed by China with 513 miles per year.

Americans also ranked last for the percentage of their travel accomplished using public transit — 10 percent, tying with Canada. Residents of China use transit 72 percent of the time, followed by Indians, who use transit 65 percent of the time.

The U.S. scored well for its energy efficiency tax credit and loan programs. And, it scored well for efficient ovens and refrigerators.

“We’re a leader in appliance and equipment standards,” said the report’s lead author, ACEEE national policy research analyst Rachel Young.The report called EnergyGuide appliance labels and Energy Star labels “best practices” for voluntary appliance and equipment standards.

The ACEEE gave the U.S. credit for energy efficiency standards included in residential and commercial building codes in many states, but criticized the country for not having adequate national building standards in place.

Young said the U.S. may improve in the energy efficiency rankings if the Clean Power Plan is finalized because a state may be able to increase the efficiency of its power plants and buildings as ways to reduce carbon dioxide emissions from existing power plants.

“The rule could spur greater investment in energy efficiency throughout the country,” she said.

By contrast, Germany scored well in nearly every category in the survey, including spending on energy efficiency measures, aggressive building codes, and the country’s tax credit and loan programs.

Germany has set a national target of a 20 percent reduction in primary energy consumption below 2008 levels by 2020 and 50 percent by 2050.

The U.S. is one of only two countries in the survey with no national energy savings plan or greenhouse gas emissions reduction plan.

General Discussion / AZ takes nearly 2 hours to execute prisoner...
« on: July 25, 2014, 01:10:39 PM »
In January the state of Ohio executed the convicted rapist and murderer Dennis McGuire. As in the other 31 U.S. states with the death penalty, Ohio used an intravenously injected drug cocktail to end the inmate's life. Yet Ohio had a problem. The state had run out of its stockpile of sodium thiopental, a once common general anesthetic and one of the key drugs in the executioner's lethal brew. Three years ago the only U.S. supplier of sodium thiopental stopped manufacturing the drug. A few labs in the European Union still make it, but the E.U. prohibits the export of any drugs if they are to be used in an execution.

Ohio's stockpile of pentobarbital, its backup drug, expired in 2009, and so the state turned to an experimental cocktail containing the sedative midazolam and the painkiller hydromorphone. But the executioner was flying blind. Execution drugs are not tested before use, and this experiment went badly. The priest who gave McGuire his last rites reported that McGuire struggled and gasped for air for 11 minutes, his strained breaths fading into small puffs that made him appear “like a fish lying along the shore puffing for that one gasp of air.” He was pronounced dead 26 minutes after the injection.

There is a simple reason why the drug cocktail was not tested before it was used: executions are not medical procedures. Indeed, the idea of testing how to most effectively kill a healthy person runs contrary to the spirit and practice of medicine. Doctors and nurses are taught to first “do no harm”; physicians are banned by professional ethics codes from participating in executions. Scientific protocols for executions cannot be established, because killing animal subjects for no reason other than to see what kills them best would clearly be unethical. Although lethal injections appear to be medical procedures, the similarities are just so much theater.

Yet even if executions are not medical, they can affect medicine. Supplies of propofol, a widely used anesthetic, came close to being choked off as a result of Missouri's plan to use the drug for executions. The state corrections department placed an order for propofol from the U.S. distributor of a German drug manufacturer. The distributor sent 20 vials of the drug in violation of its agreement with the manufacturer, a mistake that the distributor quickly caught. As the company tried in vain to get the state to return the drug, the manufacturer suspended new orders. The manufacturer feared that if the drug was used for lethal injection, E.U. regulators would ban all exports of propofol to the U.S. “Please, Please, Please HELP,” wrote a vice president at the distributor to the director of the Missouri corrections department. “This system failure—a mistake—1 carton of 20 vials—is going to affect thousands of Americans.”

This was a vast underestimate. Propofol is the most popular anesthetic in the U.S. It is used in some 50 million cases a year—everything from colonoscopies to cesareans to open-heart surgeries—and nearly 90 percent of the propofol used in the U.S. comes from the E.U. After 11 months, Missouri relented and agreed to return the drug.

Such incidents illustrate how the death penalty can harm ordinary citizens. Supporters of the death penalty counter that its potential to discourage violent crime confers a net social good. Yet no sound science supports that position. In 2012 the National Academies' research council concluded that research into any deterrent effect that the death penalty might provide is inherently flawed. Valid studies would need to compare homicide rates in the same states at the same time, but both with and without capital punishment—an impossible experiment. And it is clear that the penal system does not always get it right when meting out justice. Since 1973 the U.S. has released 144 prisoners from death row because they were found to be innocent of their crimes.

Concerns about drug shortages for executions have led some states to propose reinstituting the electric chair or the gas chamber—methods previously dismissed by the courts as cruel and unusual. In one sense, these desperate states are on to something. Strip off its clinical facade, and death by intravenous injection is no less barbarous.

Spamalot / hey AD
« on: July 24, 2014, 12:04:47 AM »
pyopencl & mpmath were waaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaay easier to install in ubuntu than windows

suuuuuuuck it bro

although i still have no idea what made pyopencl finally start working. the 'easier' install still took 7 hours, woo

General Discussion / 10 Things Millennials Won’t Spend Money On
« on: July 23, 2014, 12:13:04 PM »
By 2017, millennials will have more buying power than any other generation. But so far, they're not spending like their parents did.

Getting Some Financial Help From Mom and Dad? Tell Us Your Story.
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Millennials are often maligned for their lack of financial literacy, but there is one money skill the younger generation has in spades: saving. After growing up during the Great Recession, millennials want to keep every cent they can. (If you don’t believe us, just check out this Reddit Frugal thread inspired by our recent post on millennial retirement super-saving.)

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This generation may be way ahead of where their parents were at the same age when it comes to preparing for retirement, but the frugality doesn’t end there. Kids these days also aren’t making the same buying decisions our parents made. Here are 10 things that a disproportionate number of today’s young adults won’t shell out for.

Eat Butter Fat Time Magazine Cover
Ending the War on Fat
The End of Iraq
How Many People Watched Orange Is the New Black? No One Knows
1. Pay TV
The average American still consumes 71% of his or her media on television, but for people age 14-24, it’s only 46%—with the lion’s share being consumed on phone, tablet, or PC. Many young people aren’t getting a TV at all. Nielsen found that most “Zero-TV” households tended toward the younger set, with adults under 35 making up 44% of all television teetotalers.

Millennials aren’t the only ones tuning out the tube. In 2013, Nielsen reported aggregate TV watching time shrank for the first time in four years.

2. Investments
By all accounts, young people should be investing in equities. Those just entering the work force have plenty of time before retirement to ride out market blips, and experts recommend younger investors place 75% to 90% of their portfolio in stocks or stock funds.

Unfortunately, after growing up in the Great Recession, millennials would rather put their money in a sock drawer than on Wall Street. When Wells Fargo surveyed roughly 1,500 adults between 22 and 32 years of age, 52% stated they were “not very” or “not at all” confident in the stock market as a place to invest for retirement.

Of those surveyed, only 32% said they had the majority of their savings in stocks or mutual funds. (Too be fair, an equal number admitted to having no clue what they were invested in, so hopefully their trust fund advisors are making good decisions.)

3. Mass-Market Beer
Bud. Coors. Miller. When parents want a drink, they reach for the classics. Maybe a Heineken for a little extra adventure. Millennials? Not so much. When Generation Now (thank god that moniker didn’t catch on) wants to get boozy, the data says we prefer indie brews.

According to one recent study, 43% of millennials say craft beer tastes better than mainstream beers, while only 32% of baby boomers said the same. And 50% of millennials have consumed craft brew, versus 35% of the overall population. Even Pete Coors, CEO of guess-which-brand, blames pesky kids for his beer’s declining sales.

4. Cars
Back when the Beach Boys wrote Little Deuce Coupe in 1963, there was a whole genre called “Car Songs.” Nowadays you’d be hard pressed to find someone under 35 who knows what a “competition clutch with the four on the floor” even means.

The sad fact is that American car culture is dying a slow death. Yahoo Finance reports the percentage of 16-to-24-year-olds with a driver’s license has plummeted since 1997 and is now below 70% for the first time since Little Deuce Coupe’s release. According to the Atlantic, “In 2010, adults between the ages of 21 and 34 bought just 27 percent of all new vehicles sold in America, down from the peak of 38 percent in 1985.”

5. Homes
It’s not that millennials don’t want to own homes—nine in ten young people do—it’s that they can’t afford them. Harvard’s Joint Center for Housing Studies found that homeownership rate among adults younger than 35 fell by 12 percent between 2006 and 2011, and 2 million more were living with Mom and Dad.

It’s going to be a while before young people start purchasing homes again. The economic downturn set this generation’s finances back years, and reforms like the Dodd-Frank Act have made it even more difficult for the newly employed to get credit. Now that unemployment is decreasing, working millennials are still renting before they buy.

6. Bulk Warehouse Club Goods
This one initially sounds weird, but remember: millennials don’t own cars or homes. So a Costco membership doesn’t make much sense. It’s not easy to bring home a year’s supply of Nesquik and paper towels without a ride, and even if you take a bus, there’s no room to stash hoards of kitchen supplies in a studio apartment.

Responding to tepid millennial demand, the big box giant is trying to win over youngsters by partnering with Google to deliver certain items right to your home. However, even Costco doesn’t seem all that excited about its new strategy.

“Don’t expect us to go to everybody’s doorstep,” Richard Galanti, Costco’s chief financial officer, told Bloomberg Businessweek. “Delivering small quantities of stuff to homes is not free. Ultimately, somebody’s got to pay for it.”

7. Weddings
Getting hitched early in life used to be something of a right of passage into adulthood. A full 65% of the Silent Generation married at age 18 to 32. Since then, though, Americans have been waiting longer and longer to tie the knot. Pew Research found 48% of boomers were married while in that age range, compared to 35% in Gen X. Millennials are bringing up the rear at just 26%.

Just like with homes, it’s not that today’s youth just hates wedding dresses—far from it. Sixty-nine percent of millennials told Pew they would like to marry, but many are waiting until they’re more financially stable before doing so.

8. Children
It’s hard to spend money on children if you don’t have any.

After weddings, you probably saw this one coming, but millennials’ procreation abstention isn’t only because they’re not married. Many just aren’t planning on having kids. In a 2012 study, fewer than half of millennials (42%) said they planned to have children. That’s down from 78% 20 years ago.

Stop me if you heard this one: it’s not that millennials don’t want children (or homes, or weddings, or ponies), it’s that this whole recession thing has really scared them off any big financial or life commitments. Most young people in the above study hoped to have kids one day, but didn’t think their economic stars would align to make it happen.

9. Health insurance
According the Kaiser Family Foundation, adults ages 18 to 34 made up 40% of the uninsured population in the pre-Obamacare world. Why don’t young people get health coverage? Because they’re probably not going to get sick. This demographic is so healthy that those in the health insurance game refer to them as “invincibles.”

Since the Affordable Care Act, more millennials are gradually buying insurance. Twenty-eight percent of Obamacare’s 8 million new enrollees were 18-34 year-olds. That’s well short of the 40% the Congressional Budget Office wanted in order to subsidize older Americans’ plans, but better than the paltry number of millennials who signed up before Zach Galifianakis got involved.

10. Anything you tell them to buy
When buying a product, older Americans tend to trust the advice of people they know. Sixty-six percent of boomers said the recommendations of friends and family members influences their purchasing decisions more than a stranger’s online review.

Most millennials, on the other hand, don’t want their parent’s or peer’s help. Fifty-one percent of young adults say they prefer product reviews from people they don’t know.

A reporter asked me for a quote regarding the importance of statistics. But, after thinking about it for a moment, I decided that statistics isn’t so important at all. A world without statistics wouldn’t be much different from the world we have now.

What would be missing, in a world without statistics?

Science would be pretty much ok. Newton didn’t need statistics for his theories of gravity, motion, and light, nor did Einstein need statistics for the theory of relativity. Thermodynamics and quantum mechanics are fundamentally statistical, but lots of progress could’ve been made in these areas without statistics. The second law of thermodynamics is an observable fact, ditto the two-slit experiment and various experimental results revealing the nature of the atom. The A-bomb and, almost certainly, the H-bomb, maybe these would never have been invented without statistics, but on balance I think most people would feel that the world would be a better place without these particular scientific developments. Without statistics, we could forget about discovering the Hibbs boson etc, but that doesn’t seem like such a loss for humanity.

At a more applied level, statistics helped to win World War 2, most notably in cracking the Enigma code but also in various operations-research efforts. And it’s my impression that “our” statistics were better than “their” statistics. So that’s something.

Where would civilian technology be without statistics? I’m not sure. I don’t have a sense of how necessary statistics was for quantum theory. In a world without statistics, would the study of quantum physics have progressed far enough so that transistors were invented? This one, I don’t know. And without statistics we wouldn’t have modern quality control, so maybe we’d still be driving around in AMC Gremlins and the like. Scary thought, but not a huge deal, I’d think. No transistors, though, that would make a difference in my life. No transistors, no blogging! And I guess we could also forget about various unequivocally beneficial technological innovations such as modern pacemakers, hearing aids, cochlear implants, and Clippy.

Modern biomedicine uses lots and lots of statistics, but would medicine be so much worse without it? I don’t think so, at least not yet. You don’t need statistics to see that penicillin works, nor to see that mosquitos transmit disease and that nets keep the mosquitos out. Without statistics, I assume that various mistakes would get into the system, various ineffective treatments that people think are effective, etc. But on balance I doubt these would be huge mistakes, and the big ones would eventually get caught, with careful record-keeping even without statistical inference and adjustments. Without statistics, biologists would not be able to sequence the gene, and I assume they’d be much slower at developing tools such as tests that allow you to check for chromosomal abnormalities in amnio. I doubt all these things add up to much yet, but I guess there’s promise for the future. Statistics is also necessary for a lot of drug development—right now my colleagues and I are working on a pharmacodynamic model of dosing—but, again, without any of this, it’s not clear the world would be so much different.

The Poverty Lab team use statistics and randomized experiments to see what works to help the lives of poor people around the world. That’s cool but I’m not ultimately convinced this all makes a difference in the big picture. Or, to put it another way, I suspect that the statistical validation serves mostly as a way to build political consensus for economic policies that will be effective in sharing the wealth. By demonstrating in a scientific way that Treatment X is effective, this supports the idea that there is a way to help the sort of people who live in what Nicholas Wade would describe as “tribal” societies. So, sure, fine, but in this case the benefits of the statistical methods are somewhat indirect.

Without statistics, we wouldn’t have most of the papers in “Psychological Science,” but I could handle that. Piaget didn’t need any statistics, and I think the modern successors of Piaget could’ve done pretty much what they’ve done without statistics, just by carefully observation of major transitions.

Careful observation and precise measurement can be done, with or without statistical methods. Indeed, researchers often use statistics as a substitute for careful observation and precise measurement. That is a horrible thing to do, and if you have a clear understanding of statistical theory, you can see why. But statistics is hard, and lots of researchers (and journal editors, news reporters, etc.) don’t have that understanding. When statistics is used as a substitute for, rather than an adjunct to, scientific measurement, we get problems.

OK, here’s another one: no statistics, no psychometrics. That’s too bad but one could make the argument that, on the whole, psychometrics has done more harm than good (value-added assessment, anyone?). Don’t get me wrong—I like psychometrics, and a strong argument could be made that it’s done more good than harm—but my point here is that the net benefit is not clear; a case would have to be made.

Polling. Can’t do it well without statistics. But, would a world without polling be so horrible? Much as I hate to admit it, I don’t think so. Don’t get me wrong, I think polling is on balance a good thing—I agree with George Gallup that measurement of public opinion is an important part of the modern democratic process—but I wouldn’t want to hang too much of the benefits of statistics on this one use, given that I expect lots of people would argue that opinion polls do more harm than good in politics.

The alternative to good statistics is . . .

Perhaps the most important benefits of statistics come not from the direct use of statistical methods in science and technology, but rather in helping us learn about the world. Statisticians from Francis Galton and Ronald Fisher onward have used statistics to give us a much deeper understanding of human and biological variation. I can’t see how any non-statistical, mechanistic model of the world could reproduce that level of understanding. Forget about p-values, Bayesian inference, and the rest: here I’m simply talking about the nature of correlation and variation.

For a more humble example, consider Bill James. Baseball is a silly example, sure, but the point is to see how much understanding has been gained in this area through statistical measurement and comparison. As James so memorably wrote, the alternative to good statistics is not “no statistics,” it’s “bad statistics.” James wrote about baseball commentators who would make asinine arguments which they would back up by picking out numbers without context. In politics, the equivalent might be a proudly humanistic columnist such as David Brooks supporting his views by just making up numbers or featuring various “too good to be true” statistics and not checking them.

So here’s one benefit to the formal study of statistics: Without any statistics, there still would be numbers, along with people trying to interpret them.

Could governments and large businesses be managed well without statistics? I’m not sure. Given that half the U.S. Congress seems willing to shut down the government from time to time, it’s not clear than any agreement on the numbers will have much to do with political action. Similarly, all the statistics in the world don’t seem to be stopping the euro-zone from drifting. But maybe things would be much worse without a common core of statistical agreement. I don’t know; unfortunately this seems like the sort of causal question that is too difficult for statistics to answer.

Finally, one way that statistics is potentially having a huge impact in our lives is through the measurement of global warming and all the rest. But I’m guessing that a lot of this could be done with a pre-statistical understanding. The basic physics is already there, as would be the careful measurements. Statistical modeling is certainly relevant to the study of climate change—if you’re trying to reconstruct historical climate conditions from tree-ring data, it’s tough enough to do it with statistical modeling, I can’t imagine how it could be done otherwise—but the basic patterns of carbon dioxide, temperature, melting ice, etc., are apparent in any case. And, even with statistics, much uncertainty remains.


When I started writing this post, I was thinking that statistics doesn’t really matter, but I think that’s because I was focusing on some of the more highly-publicized by less beneficial applications of statistics: the use of statistical experimentation and inference to get p-values for tabloid-bait scientific papers, or for Google, Amazon, etc., to perfect their techniques for squeezing money out of their customers or, even at best, to test a medical treatment that increases survival rate for some rare disease by 2 percentage points. But statistics is central to how we think about the world. I still think that statistics is much less central to our lives than, say, chemistry. But it ain’t nothing.

General Discussion / Basilisk Gedankenexperiment Freaks out Futurists
« on: July 21, 2014, 08:34:34 PM »
Slender Man. Smile Dog. Goatse. These are some of the urban legends spawned by the Internet. Yet none is as all-powerful and threatening as Roko’s Basilisk. For Roko’s Basilisk is an evil, godlike form of artificial intelligence, so dangerous that if you see it, or even think about it too hard, you will spend the rest of eternity screaming in its torture chamber. It's like the videotape in The Ring. Even death is no escape, for if you die, Roko’s Basilisk will resurrect you and begin the torture again.

Are you sure you want to keep reading? Because the worst part is that Roko’s Basilisk already exists. Or at least, it already will have existed—which is just as bad.

Roko’s Basilisk exists at the horizon where philosophical thought experiment blurs into urban legend. The Basilisk made its first appearance on the discussion board LessWrong, a gathering point for highly analytical sorts interested in optimizing their thinking, their lives, and the world through mathematics and rationality. LessWrong’s founder, Eliezer Yudkowsky, is a significant figure in techno-futurism; his research institute, the Machine Intelligence Research Institute, which funds and promotes research around the advancement of artificial intelligence, has been boosted and funded by high-profile techies like Peter Thiel and Ray Kurzweil, and Yudkowsky is a prominent contributor to academic discussions of technological ethics and decision theory. What you are about to read may sound strange and even crazy, but some very influential and wealthy scientists and techies believe it.

One day, LessWrong user Roko postulated a thought experiment: What if, in the future, a somewhat malevolent AI were to come about and punish those who did not do its bidding? What if there were a way (and I will explain how) for this AI to punish people today who are not helping it come into existence later? In that case, weren’t the readers of LessWrong right then being given the choice of either helping that evil AI come into existence or being condemned to suffer?

You may be a bit confused, but the founder of LessWrong, Eliezer Yudkowsky, was not. He reacted with horror:

Listen to me very closely, you idiot.


You have to be really clever to come up with a genuinely dangerous thought. I am disheartened that people can be clever enough to do that and not clever enough to do the obvious thing and KEEP THEIR IDIOT MOUTHS SHUT about it, because it is much more important to sound intelligent when talking to your friends.

This post was STUPID.

Yudkowsky said that Roko had already given nightmares to several LessWrong users and had brought them to the point of breakdown. Yudkowsky ended up deleting the thread completely, thus assuring that Roko’s Basilisk would become the stuff of legend. It was a thought experiment so dangerous that merely thinking about it was hazardous not only to your mental health, but to your very fate.

Some background is in order. The LessWrong community is concerned with the future of humanity, and in particular with the singularity—the hypothesized future point at which computing power becomes so great that superhuman artificial intelligence becomes possible, as does the capability to simulate human minds, upload minds to computers, and more or less allow a computer to simulate life itself. The term was coined in 1958 in a conversation between mathematical geniuses Stanislaw Ulam and John von Neumann, where von Neumann said, “The ever accelerating progress of technology ... gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.” Futurists like science-fiction writer Vernor Vinge and engineer/author Kurzweil popularized the term, and as with many interested in the singularity, they believe that exponential increases in computing power will cause the singularity to happen very soon—within the next 50 years or so. Kurzweil is chugging 150 vitamins a day to stay alive until the singularity, while Yudkowsky and Peter Thiel have enthused about cryonics, the perennial favorite of rich dudes who want to live forever. “If you don't sign up your kids for cryonics then you are a lousy parent,” Yudkowsky writes.

If you believe the singularity is coming and that very powerful AIs are in our future, one obvious question is whether those AIs will be benevolent or malicious. Yudkowsky’s foundation, the Machine Intelligence Research Institute, has the explicit goal of steering the future toward “friendly AI.” For him, and for many LessWrong posters, this issue is of paramount importance, easily trumping the environment and politics. To them, the singularity brings about the machine equivalent of God itself.

Yet this doesn’t explain why Roko’s Basilisk is so horrifying. That requires looking at a critical article of faith in the LessWrong ethos: timeless decision theory. TDT is a guideline for rational action based on game theory, Bayesian probability, and decision theory, with a smattering of parallel universes and quantum mechanics on the side. TDT has its roots in the classic thought experiment of decision theory called Newcomb’s paradox, in which a superintelligent alien presents two boxes to you:

The alien gives you the choice of either taking both boxes, or only taking Box B. If you take both boxes, you’re guaranteed at least $1,000. If you just take Box B, you aren’t guaranteed anything. But the alien has another twist: Its supercomputer, which knows just about everything, made a prediction a week ago as to whether you would take both boxes or just Box B. If the supercomputer predicted you’d take both boxes, then the alien left the second box empty. If the supercomputer predicted you’d just take Box B, then the alien put the $1 million in Box B.

So, what are you going to do? Remember, the supercomputer has always been right in the past.

This problem has baffled no end of decision theorists. The alien can’t change what’s already in the boxes, so whatever you do, you’re guaranteed to end up with more money by taking both boxes than by taking just Box B, regardless of the prediction. Of course, if you think that way and the computer predicted you’d think that way, then Box B will be empty and you’ll only get $1,000. If the computer is so awesome at its predictions, you ought to take Box B only and get the cool million, right? But what if the computer was wrong this time? And regardless, whatever the computer said then can’t possibly change what’s happening now, right? So prediction be damned, take both boxes! But then …

The maddening conflict between free will and godlike prediction has not led to any resolution of Newcomb’s paradox, and people will call themselves “one-boxers” or “two-boxers” depending on where they side. (My wife once declared herself a one-boxer, saying, “I trust the computer.”)

TDT has some very definite advice on Newcomb’s paradox: Take Box B. But TDT goes a bit further. Even if the alien jeers at you, saying, “The computer said you’d take both boxes, so I left Box B empty! Nyah nyah!” and then opens Box B and shows you that it’s empty, you should still only take Box B and get bupkis. (I’ve adopted this example from Gary Drescher’s Good and Real, which uses a variant on TDT to try to show that Kantian ethics is true.) The rationale for this eludes easy summary, but the simplest argument is that you might be in the computer’s simulation. In order to make its prediction, the computer would have to simulate the universe itself. That includes simulating you. So you, right this moment, might be in the computer’s simulation, and what you do will impact what happens in reality (or other realities). So take Box B and the real you will get a cool million.

What does all this have to do with Roko’s Basilisk? Well, Roko’s Basilisk also has two boxes to offer you. Perhaps you, right now, are in a simulation being run by Roko’s Basilisk. Then perhaps Roko’s Basilisk is implicitly offering you a somewhat modified version of Newcomb’s paradox, like this:

Roko’s Basilisk has told you that if you just take Box B, then it’s got Eternal Torment in it, because Roko’s Basilisk would really you rather take Box A and Box B. In that case, you’d best make sure you’re devoting your life to helping create Roko’s Basilisk! Because, should Roko’s Basilisk come to pass (or worse, if it’s already come to pass and is God of this particular instance of reality) and it sees that you chose not to help it out, you’re screwed.

You may be wondering why this is such a big deal for the LessWrong people, given the apparently far-fetched nature of the thought experiment. It’s not that Roko’s Basilisk will necessarily materialize, or is even likely to. It’s more that if you’ve committed yourself to timeless decision theory, then thinking about this sort of trade literally makes it more likely to happen. After all, if Roko’s Basilisk were to see that this sort of blackmail gets you to help it come into existence, then it would, as a rational actor, blackmail you. The problem isn’t with the Basilisk itself, but with you. Yudkowsky doesn’t censor every mention of Roko’s Basilisk because he believes it exists or will exist, but because he believes that the idea of the Basilisk (and the ideas behind it) is dangerous.

Now, Roko’s Basilisk is only dangerous if you believe all of the above preconditions and commit to making the two-box deal with the Basilisk. But at least some of the LessWrong members do believe all of the above, which makes Roko’s Basilisk quite literally forbidden knowledge. I was going to compare it to H. P. Lovecraft’s horror stories in which a man discovers the forbidden Truth about the World, unleashes Cthulhu, and goes insane, but then I found that Yudkowsky had already done it for me, by comparing the Roko’s Basilisk thought experiment to the Necronomicon, Lovecraft’s fabled tome of evil knowledge and demonic spells. Roko, for his part, put the blame on LessWrong for spurring him to the idea of the Basilisk in the first place: “I wish very strongly that my mind had never come across the tools to inflict such large amounts of potential self-harm,” he wrote.

If you do not subscribe to the theories that underlie Roko’s Basilisk and thus feel no temptation to bow down to your once and future evil machine overlord, then Roko’s Basilisk poses you no threat. (It is ironic that it’s only a mental health risk to those who have already bought into Yudkowsky’s thinking.) Believing in Roko’s Basilisk may simply be a “referendum on autism,” as a friend put it. But I do believe there’s a more serious issue at work here because Yudkowsky and other so-called transhumanists are attracting so much prestige and money for their projects, primarily from rich techies. I don’t think their projects (which only seem to involve publishing papers and hosting conferences) have much chance of creating either Roko’s Basilisk or Eliezer’s Big Friendly God. But the combination of messianic ambitions, being convinced of your own infallibility, and a lot of cash never works out well, regardless of ideology, and I don’t expect Yudkowsky and his cohorts to be an exception.

I worry less about Roko’s Basilisk than about people who believe themselves to have transcended conventional morality. Like his projected Friendly AIs, Yudkowsky is a moral utilitarian: He believes that that the greatest good for the greatest number of people is always ethically justified, even if a few people have to die or suffer along the way. He has explicitly argued that given the choice, it is preferable to torture a single person for 50 years than for a sufficient number of people (to be fair, a lot of people) to get dust specks in their eyes. No one, not even God, is likely to face that choice, but here’s a different case: What if a snarky Slate tech columnist writes about a thought experiment that can destroy people’s minds, thus hurting people and blocking progress toward the singularity and Friendly AI? In that case, any potential good that could come from my life would far be outweighed by the harm I’m causing. And should the cryogenically sustained Eliezer Yudkowsky merge with the singularity and decide to simulate whether or not I write this column … please, Almighty Eliezer, don’t torture me.

General Discussion / "Kafka-esque" Comcast CS Call
« on: July 15, 2014, 05:20:35 PM »
"When a customer service call is described as "Kafkaesque" and "hellish," you pretty much know how it's going to go down before even taking a listen. But in case you haven't heard the condescending, tedious call that's lit up the Internet, here it is: ..."

We are in the process of researching this issue, but it looks like the domain registration for the domain expired this morning, reverting back to being the property of NetworkSolutions. While SOE did not use the domain publicly, preferring, the aforementioned domain contains all of the nameservers (,, which route users to SOE’s websites and forums, as well as connecting to its games.

For the last 20 minutes or so, we have been monitoring the situation. We’ve seen the forums and websites briefly become accessible before going dark again. It’s possible that conflicting DNS information is propagating out there, preventing users from reliably connecting to SOE’s websites, forums, and games.

It seems plausible that the expiration notices from NetworkSolutions have been going to an unread e-mail address at SOE for the last few weeks and NS finally decided to reclaim this one. The expiration for was set for 26-may-2014, while today, July 15th, is some 7 weeks later. That’s some grace period!

UPDATE: Although there don’t seem to have been any changes behind the scenes,,, and other SOE websites all seem to be loading “domain parked” pages full of advertisements now.

UPDATE from EverQuest Next and Landmark Community Manager Colette “Dexella” Murphy who is likely in need of coffee at 5:30am PDT:

We’re working on the SOE games/website/forum issues people are reporting. More news when it’s available! Thanks, everyone.

— Colette (Dexella) (@DexellaCM) July 15, 2014

General Discussion / Have Anti-ACA Ads generated greater enrollment?
« on: July 11, 2014, 06:33:02 PM »
According to the recent report of nonpartisan analysts Kantar Media CMAG, ACA opponents have spent 450 million dollars on anti-Obamacare ads so far. Spending on negative ads outpaced positive ones by more than 15 to 1. This map shows the spending on negative ads in each state.

How Have Ads Impacted the ACA Enrollment in Different States?

I used the ACA enrollment data released by the Department of Health and Human Services, to calculate the ACA enrollment ratio as the number of enrollees divided by the total number of people who could have potentially enrolled in the ACA. This number includes the ones who were either uninsured or had purchased private insurance. Although more than 8 million Americans have signed-up to purchase health insurance through the marketplaces during the first open enrollment period, this nationwide number masks tremendous variation in participation across states. While the enrollment percentage in Minnesota is slightly above five percent, in Vermont, close to fifty percent of all eligible individuals have signed up for the ACA.

ACA Enrollment Ratios by State


I also calculated the per capita spending on anti-Obamacare ads as the total amount of spending in each state divided by its population. By spending close to a dollar per resident, District of Columbia outpaced all of the fifty states in per capita spending on anti-Obamacare ads, yet over 11% of its eligible population signed-up for Obamacare.

The following plot compares the per capita spending on anti-ACA ads and the enrollment ratio in 49 states. I removed DC and Vermont since they had abnormally high ad spending or enrollment ratios.

Enrollment Ratio and Per Capita Anti-ACA Advertising

The blue dots represent the states in which Senate Democrats are up for re-election in 2014, while the red dots represent the states in which Republican Senators are running for re-election. The states in which no Senate midterm elections are held are shown in green.

The four states with the highest per capita spending on anti-ACA ads are Kentucky, Arkansas, Louisiana, and North Carolina. Interestingly, in all of these four states, the midterm Senate elections are expected to be very competitive. Although the volume of spending on anti-ACA ads is driven by the competitiveness of the Senate midterm elections and may be effective in reducing the votes for the targeted political figure, they may not necessarily reduce the popularity of the ACA. The blue and red lines show the association between the anti-ACA ads spending and the ACA enrollment ratio in states with Democratic and Republican Senators running for re-election. While the negative ads reduce the enrollment in red states, they have an opposite effect in blue states.

In fact, after controlling for other state characteristics such as low per capita income population and average insurance premiums, I observe a positive association between the anti-ACA spending and ACA enrollment. This implies that anti-ACA ads may unintentionally increase the public awareness about the existence of a governmentally subsidized service and its benefits for the uninsured. On the other hand, an individual’s prediction about the chances of repealing the ACA may be associated with the volume of advertisements against it. In the states where more anti-ACA ads are aired, residents were on average more likely to believe that Congress will repeal the ACA in the near future. People who believe that subsidized health insurance may soon disappear could have a greater willingness to take advantage of this one time opportunity.

General Discussion / The World Cup Can Help Test Economic Theories
« on: July 11, 2014, 06:07:34 PM »
THE World Cup is finally underway. At long last, soccer fans can don their team colors, head down to the local pub — and begin collecting data to test economic theories.

Or at least, some of us will.

For instance, I’m interested in penalty kicks. In addition to being an exciting part of the game, penalty kicks present an opportunity to test an important idea in economics: the Nash equilibrium.

The economist John Forbes Nash Jr. analyzed how people should behave in strategic situations in which it is not optimal to repeatedly make the same move — like the children’s game rock, paper, scissors, in which selecting one move again and again (rock, rock, rock ...) makes you easy to beat. According to Mr. Nash’s theory, in a zero-sum game (i.e., where a win for one player entails a corresponding loss for the other) the best approach is to vary your moves unpredictably and in such proportions that your probability of winning is the same for each move. In rock, paper, scissors, for example, the optimal strategy is to mix your choices randomly among the three options.

To test this theory in the real world, we can study penalty kicks, which are zero-sum games in which it is not optimal to repeatedly choose the same move. (The goalie has an easier time stopping your shot if you always kick to the same side of the net.) Unlike complex real-world strategic situations involving firms, banks or countries, penalty kicks are relatively simple, and data about them are readily available.

I analyzed 9,017 penalty kicks taken in professional soccer games in a variety of countries from September 1995 to June 2012. I found, as Mr. Nash’s theory would predict, that players typically distributed their shots unpredictably and in just the right proportions. Specifically, roughly 60 percent of kicks were made to the right of the net, and 40 percent to the left. The proportions were not 50-50 because players have unequal strengths in their legs and tend to shoot better to one side. Shooting 50-50, in other words, would not take full advantage of their better leg, while shooting any more often to the stronger side would have been too predictable.

In accordance with Mr. Nash’s theory, penalty kicks shot to the left were successful with the same frequency as kicks shot to the right — roughly 80 percent of the time.

Penalty kicks are just one example. Data from soccer can also illuminate one of the most prominent theories of the stock market: the efficient-market hypothesis. This theory posits that the market incorporates information so completely and so quickly that any relevant news is integrated into a stock’s price before anyone has a chance to act on it. This means that unless you have insider information, no stock is a better buy (i.e., undervalued) when compared with any other.

If this theory is correct, the price of an asset should jump up or down when news breaks and then remain perfectly flat until there is more news. But to test this in the real world is difficult. You would need to somehow stop the flow of news while letting trading continue. That seems impossible, since everything that happens in the real world, however boring or uneventful, counts as news.

This is where soccer is useful. In a study published earlier this year in The Economic Journal, the economists Karen Croxson and J. James Reade analyzed live soccer betting markets, looking at second-by-second betting activity around goals scored just seconds before halftime and betting activity during halftime. Their data, which concerned 1,206 Premier League soccer matches in England, contained 160 such “cusp” goals scored within seconds of the end of the first half.

The break in play at halftime provided a golden opportunity to study market efficiency because the playing clock stopped but the betting clock continued. Any drift in halftime betting values would have been evidence against market efficiency, since efficient prices should not drift when there is no news (or goals, in this case). It turned out that when goals arrived within seconds of the end of the first half, betting continued heavily throughout halftime — but the betting values remained constant, a necessary condition to prove that those markets were indeed efficient.

Other research by me and others has shown that data from soccer can shed light on the economics of discrimination, fear, corruption and the dark side of incentives in organizations. In other words, aspects of the beautiful game that are less than beautiful from a fan’s perspective can still be illuminating for economists.

But perhaps most beautiful of all, for me, is that the core principles of my beloved professional discipline are exemplified by my beloved game.

Last month, the inaugural Breakthrough Prizes in mathematics, founded and partially funded by internet billionaires Yuri Milner and Mark Zuckerberg, were awarded to five people: Simon Donaldson, Maxim Kontsevich, Jacob Lurie, Terence Tao, and Richard Taylor. The prize is $3 million per person, and the first five winners will be on the committee for the selection of future winners. (In the future, there will be only one prize awarded per year.)

I was a bit surprised that there hasn’t been much talk on blogs about the prizes, but there has been a bit. Peter Woit wrote about the prize on Not Even Wrong, and the comments to his post are interesting. “Shecky Riemann” also has a post on Math-Frolic.

I must admit that I am somewhat cynical about the prize. (Now might be a good time to reiterate the disclaimer that appears on the sidebar of this blog: my opinions do not necessarily reflect the opinions of the AMS.) The five winners are all productive, brilliant mathematicians who have enhanced their fields immensely, and they deserve to be recognized. But $3 million is just so much money! It’s hard for me to see how concentrating that much money in the hands of so few people is an efficient way to support mathematics.

Woit’s post voices some similar concerns. He writes,

“…it’s still debatable whether this is a good way to encourage mathematics research. The people chosen are already among the most highly rewarded in the subject, with all of them having very well-paid positions with few responsibilities beyond their research, as well as access to funding of research expenses. The argument for the prize is mainly that these sums of money will help make great mathematicians celebrities, and encourage the young to want to be like them. I can see this argument and why some people find it compelling. Personally though, I think our society in general and academia in particular is already suffering a great deal as it becomes more and more of a winner-take-all, celebrity-obsessed culture, with ever greater disparities in wealth, and this sort of prize just makes that worse. It’s encouraging to see that most of the prize winners have already announced intentions to redirect some of the prize moneys for a wider benefit to others and the rest of the field.

In fact, the New York Times reports that Tao, one of the winners, has similar feelings:

“Dr. Tao tried to talk Mr. Milner out of it, and suggested that more prizes of smaller amounts might be more effective in supporting mathematics. ‘The size of the award, I think it’s ridiculous,’ he said. ‘I didn’t feel I was the most qualified for this prize.’

“But Dr. Tao added: ‘It’s his money. He can do whatever he wants with it.’

“Dr. Tao said he might use some of the prize money to help set up open-access mathematics journals, which would be available free to anyone, or for large-scale collaborative online efforts to solve important problems.”

As a young academic who has seen postdoc positions seem to dry up since the beginning of the financial crisis, I can’t help but do a little arithmetic. $50,000 is a nice round salary for a postdoc. Before benefits are factored in, that makes each $3 million prize the equivalent of 60 postdoc years. Even if we add another $50,000 a year for health insurance, travel, and other research expenses, that money could fund 30 postdocs a year, or create 10 three-year postdoc positions each year.

But 30 postdocs a year wouldn’t make a good press release. The New York Times wouldn’t write an article about their multimillion dollar minds. And the funders of the Breakthrough Prize want to encourage mathematical celebrity, which supposedly will lead to public awareness, not to fund worthwhile math research in the most efficient way possible. In a Scientific American article about the prize, Ben Fogelson writes,

“Milner’s goal, however, is to increase the popularity of science by celebrating the scientists. ‘Dividing [money] in small pieces and distributing it widely has been tried before and it works,’ Milner says. ‘I think the idea behind this initiative is to really focus on raising public awareness.’”

A commenter on Woit’s post suggested that each year, the prize money could be used to endow a research position at a university, noting that at MIT, you can endow a professorship for $3 million. Would that be high-profile enough? I think you could still write a press release about it!

I had some interesting discussions about the prize on Twitter after the prizewinners were announced, mainly focused on the utility of mathematical celebrity. Those discussions helped me frame a few questions about celebrity and public awareness. I’ve tried to figure out some analogous questions about movies and the Oscars because the Breakthrough Prizes have been described as the Oscars of science.

Will people think mathematics is more valuable because a few people can earn giant prizes from it? (Do people think filmmaking is more valuable because the Oscars exist?)
Will people want to become mathematicians because they think they could earn a big prize from it? (Do people become actors or filmmakers because they think they could win an Oscar?)
If the ultimate goal of the prize is to raise public awareness of math, what is a more effective way to do that: tell them about a successful mathematician, or tell them about an idea in math? (If someone doesn’t know much about cinema, would it be more effective to tell them about an Oscar-winning actor or show them a movie?)
Are these even the right questions and analogies?
This post might sound like I’m saying, “I don’t like this new prize because I’m never going to get it, but I would like it if it funded people more like me.” But I don’t think I’m quite there either. I have reservations about the suggested alternate uses of the prize money as well, thanks largely to two posts by Cathy O’Neil about billionaire money in mathematics and in academia in general.

On a lighter note, if you are a mathematician who is a bit embarrassed about a recent windfall, Persiflage suggests that “a bottle of Chateau d’Yquem 1967 does wonders to wash away any last remaining vestiges of embarrassment…”

- See more at:

Reporters for BBC News are being directed to significantly curb the amount of air time they give to people with anti-science viewpoints — including people who deny climate change exists — in order to improve the accuracy and fairness of the network’s news coverage, according to a report released by the BBC’s governing body on Thursday.

The BBC Trust’s report was designed to assess the network’s impartiality in science coverage, in other words, whether it is staying neutral on critical issues. In order to be neutral when covering science, however, the BBC noted it needs to avoid “false balance,” a fallacy that occurs when two sides of an argument are assumed to have equal value.

“Science coverage does not simply lie in reflecting a wide range of views but depends on the varying degree of prominence such views should be given,” the report said.

The type of “false balance” news segment that the BBC is now actively trying to avoid is one that is fairly common in American network news’ climate change coverage. It involves putting one person who is well-versed on climate science next to a person who denies climate science, and having them debate.

Editorially, this type of debate makes the network look like it’s being balanced, giving equal opportunity to opposite viewpoints. However, because 95 to 97 percent of climate scientists agree that man-made greenhouse gas emissions are causing the planet to warm, that balance is false, giving disproportionate time to a viewpoint that is widely rejected in the scientific community.

In order to have a truly balanced and statistically representative debate about climate change, television news networks would have to pit 97 climate scientists against three climate deniers. Because that likely wouldn’t work very well, the BBC is favoring an approach that instead severely limits the amount of air time climate deniers are given.

So far, the report said, approximately 200 staff members have attended seminars and workshops aimed at improving the balance of their science coverage.

The BBC Trust’s report did note that climate deniers wouldn’t be completely excluded from the conversation. “The Trust also would like to reiterate that … ‘this does not mean that critical opinion should be excluded. Nor does it mean that scientific research shouldn’t be properly scrutinized,’” the report said. “The BBC has a duty to reflect the weight of scientific agreement but it should also reflect the existence of critical views appropriately. Audiences should be able to understand from the context and clarity of the BBC’s output what weight to give to critical voices.”

But despite the BBC’s pledge to have their reporters avoid false balance in climate change coverage, false balance is still a widespread phenomenon across prominent American news platforms. According to a 2013 report from Media Matters on the issue, half of print outlets used false balance to debate the existence of global warming. When covering the U.N.’s landmark climate change report that year, CBS News gave climate deniers more than six times their representation in the scientific community, and 69 percent of guests on Fox News cast doubt on the science.

The obvious effect of this is that viewers are being misled about the reality of climate change and the urgency that comes with it. But the other effect is that viewers wind up not caring about climate change altogether.

“In the case of people who watch cable news, we’ve been so conditioned to favor a sense of certainty,” Dr. Stephen Reese, author of a 2008 white paper on how people make judgments about journalistic balance, told ThinkProgress in May. “We want to have our beliefs upheld. So when you introduce [climate change] as a political issue up for debate, it’s just, ‘well okay, there they go again,’ — just dismiss it as hopelessly polarized.”

When news outlets introduce false balance into its climate change stories, its audience then thinks those stories are less pressing than they actually are, a factor which contributes to uncertainty surrounding the issue and, ultimately, apathy. A 2009 study from the American Psychological Association confirmed this, noting that “perceived or real uncertainty” on climate change can lead to both “systematic underestimation of risk” and “sufficient reason to act in self interest over that of the environment.”

It’s the rallying cry for opponents of same-sex marriage: “Every child deserves a mom or a dad.” But a major new study finds that kids raised by same-sex couples actually do a bit better “than the general population on measures of general health and family cohesion.”

The study, conducted in Australia by University of Melbourne researchers “surveyed 315 same-sex parents and 500 children.” The children in the study scored about six percent higher than Australian kids in the general population. The advantages held up “when controlling for a number sociodemographic factors such as parent education and household income.” The study was the largest of its kind in the world.

The lead researcher, Dr. Simon Crouch, noted that in same-sex couples parents have to “take on roles that are suited to their skill sets rather than falling into those gender stereotypes.” According to Crouch, this leads to a “more harmonious family unit and therefore feeding on to better health and well being.”

The findings were in line with “existing international research undertaken with smaller sample sizes.”

Family Voice Australia, a group that opposes same-sex marriage, said the study should be discounted because it does not consider “what happens when the child reaches adulthood.”
In the United States, opponents of same-sex marriage routinely claim that children raised by same-sex couple fare worse. The most commonly cited study, conducted by sociologist Mark Regnerus, did not actually study children raised by same-sex couples. Indeed, “most of the subjects in the study grew up in the 1970s, 80s, and 90s, long before marriage equality was available or adoption rights were codified in many states”. Instead, Regnerus studied children raised in “failed heterosexual unions” where one parent had a “romantic relationship with someone of the same sex.” It has been condemned by the American Sociological Association. Other frequently cited studies have similar methodological problems.

General Discussion / New State of Matter Discovered
« on: July 01, 2014, 07:07:06 PM »
There was a time when states of matter were simple: Solid, liquid, gas. Then came plasma, Bose -Einstein condensate, supercritical fluid and more. Now the list has grown by one more, with the unexpected discovery of a new state dubbed “dropletons” that bear some resemblance to liquids but occur under very different circumstances.
The discovery occurred when a team at the University of Colorado Joint Institute for Lab Astrophysics were focusing laser light on gallium arsenide (GaAs) to create excitons.
Excitons are formed when a photon strikes a material, particularly a semiconductor. If an electron is knocked loose, or excited, it leaves what is termed an “electron hole” behind. If the forces of other charges nearby keep the electron close enough to the hole to feel an attraction, a bound state forms known as an exciton. Excitons are called quasiparticles because the electrons and holes behave together as if they were a single particle.
If this all sounds a bit hard to relate to, consider that solar cells are semiconductors, and the formation of excitons is one possible step to the production of electricity. A better understanding of how excitons form and behave could produce ways to harvest sunlight more efficiently.
Graduate student Andrew Almand-Hunter was forming biexcitons – two excitons that behave like a molecule, by focusing the laser to a dot 100nm across and leaving it on for shorter and shorter fractions of a second.
“But the experiment didn’t behave at all in the way we expected,” Almand-Hunter said. When the pulses were lasting less than 100 millionths of a second exciton density reached a critical threshold. “We expected to see the energy of the biexcitons increase as the laser generated more electrons and holes. But, what we saw when we did the experiment was that the energy actually decreased!”
The team figured that they had created something other than biexcitons, but were not sure what. They contacted theorists at Philipps-University, Marburg who suggested they had made droplets of 4, 5 or 6 electrons and holes, and constructed a model of these dropletons' behavior.
The dropletons are small enough to behave quantum mechanically, but the electrons and holes are not in pairs, as they would be if the dropleton was just a group of excitons. Instead they form a “quantum fog” of electrons and holes that flow around each other and even ripple like a liquid, rather than existing as discrete pairs. However, unlike liquids we are familiar with, dropletons a finite size, outside which the electron/hole association breaks down.
The discovery has been published in Nature. Perhaps the most remarkable thing is that the dropletons are stable, by the standards of quantum physics. While they can only survive inside solid materials, they last around 25 trillionths of a second, which is actually long enough for scientists to study the way their behavior is shaped by the environment. At 200nm wide the dropletons are as large as very small bacteria – a size that can be seen by conventional microscopes.
"Classical optics can detect only objects that are larger than their wavelengths, and we are approaching that limit," Mackillo Kira of Philipps-University who provided much of the theoretical grounding told Scientific American. "It would be really neat to not only detect spectroscopic information about the dropleton, but to really see the dropleton."
JILA lab leader Professor Steven Cundiff says, “Nobody is going to build a quantum droplet widget." However, the work could help in the understanding of systems where multiple particles interact quantum mechanically.

'Community' Lives! Yahoo Has Saved Greendale for a Sixth Season

The environment doesn't appreciate our meat obsession.

The average meat-eater in the U.S. is responsible for almost twice as much global warming as the average vegetarian, and close to three times that of the average vegan, according to a study (pdf) published this month in the journal Climatic Change.

The study, which was carried out at Oxford University, surveyed the diets of some 60,000 individuals (more than 2,000 vegans, 15,000 vegetarians, 8,000 fish-eaters, and nearly 30,000 meat-eaters). Heavy meat-eaters were defined as those who consume more than 3.5 ounces of meat per day—making the average American meat-eater (who consumes roughly four ounces per day) a heavy meat-eater. Low meat-eaters were those who eat fewer than 1.76 ounces. And medium meat-eaters were those whose consumption fell somewhere in between.

The difference found in diet-driven carbon footprints was significant. Halve your meat intake, and you could cut your carbon footprint by more than 35 percent; stick to fish, and you could cut it by nearer to 50 percent; go vegan, and the difference could be 60%.

The variations were so drastic that the study's authors suggested that countries should consider revising their definition of a sustainable diet. "National governments that are considering an update of dietary recommendations in order to define a ‘healthy, sustainable diet’ must incorporate the recommendation to lower the consumption of animal-based products," the study says.

The livestock industry is responsible for roughly 15 percent of global carbon emissions. The resources necessary to produce even the smallest amounts—like, say, a quarter pound hamburger—of market ready meat are staggering.

The good news is that while Americans might still eat more meat than mother nature would prefer, they are cutting down on their intake, and especially with the most environmentally unfriendly kind—per capita beef consumption has fallen by 36 percent since its peak in 1976, according to data from the USDA. The bad news is that the rest of the world appears to be headed in the opposite direction. Global demand for meat is expected to grow by more than 70 percent by 2050, largely driven by burgeoning middle classes in the developing world. Couple that with the potential for changing health narratives in the U.S.—some of which now tout red meat (and fats, in general) as healthier than once thought—and even Americans could find themselves putting more meat on their plates in the future.

General Discussion / House Committee declares IPCC Report Not Science
« on: June 03, 2014, 10:52:45 AM »
The Intergovernmental Panel on Climate Change (IPCC) report warned that more intense droughts and heat waves will cause famine and water shortages. But, don't worry! Yesterday, the GOP held a hearing to tell us the IPCC is, in fact, a global conspiracy to control our lives and "redistribute wealth among nations."

The hearing, titled "Examining the UN Intergovernmental Panel on Climate Change Process," was convened by the House Committee on Science, Space and Technology—the same folks who recently demonstrated their inability to grasp the idea that the world's climate varies across different regions and who informed us that warmer weather didn't bother the dinosaurs, so what's all the fuss about?

In principle, there's nothing wrong with assessing the methodology of such an important and influential report. But, in one of those quintessential moments of Washington double-think, Chairman Lamar Smith (R-TX)—who accuses the IPCC of creating data to serve a predetermined political agenda—summarized the hearing's conclusions a day before it even began. "The IPCC does not perform science itself and doesn't monitor the climate," Smith told a reporter, "but only reviews carefully selected scientific literature."

So, small wonder that Rep. Eddie Bernice Johnson (D-TX), the ranking Democrat on the committee, offered the opinion:

While the topic of today's hearing is a legitimate one, namely, how the IPCC process can be improved, I am concerned that the real objective of this hearing is to try to undercut the IPCC and to cast doubt on the validity of climate change research.

We aren't going to get very far if we spend our time continually revisiting a scientific debate that has already been settled. Nor will we get far if we continue a recent practice on this Committee of seeming to question the trustworthiness and integrity of this nation's scientific researchers.

Fair and Balanced

Another source of Johnson's skepticism might have been that three of the four expert witnesses testifying at the hearing either deny that humans are responsible for global warming or believe that the potential impact of climate change is grossly overstated.

The witnesses for the prosecution were:

(1) Roger Pielke,Sr.

Who is he?

Senior Research Scientist, Cooperative Institute for Research in Environmental Sciences, and Professor Emeritus of Atmospheric Science, Colorado State University

What's he known for?

Pielke says that carbon dioxide is responsible, at most, for about 28% of human-caused warming up to the present and he is among the most vocal skeptics of reports that the polar ice caps are melting and that sea levels are rising.

What did he say at the hearing?

The IPCC is "giving decision makers who face decisions at the regional and local level a false sense of certainty about the unfolding climate future."

(2) Richard Tol

Who is he?

A professor of economics at the University of Sussex

What's he known for?

He resigned his position with the IPCC team producing the working group's Summary for Policymakers, which he classified as "alarmist." Global warming creates benefits as well as harms, he believes, and in the short term, the benefits are especially pronounced. He's also expressed doubt that climate change will play any role in exacerbating conflicts.

Tol has been criticized by other scientists who have raised questions about his methodology and who have noted that he has a history of making contradictory statements. For instance, in a widely cited 2009 paper, he wrote of "considerable uncertainty about the economic impact of climate change … negative surprises are more likely than positive ones. … The policy implication is that reduction of greenhouse gas emissions should err on the ambitious side."

What did he say at the hearing?

"Academics who research climate change out of curiosity but find less than alarming things are ignored, unless they rise to prominence in which case they are harassed and smeared….The IPCC should therefore investigate the attitudes of its authors and their academic performance and make sure that, in the future, they are more representative of their peers."

(3) Daniel Botkin

Who is he?

Professor Emeritus, Department of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara.

What's he known for?

He has long argued that life has had to deal with environmental change, especially climate change, since the beginning of its existence on Earth—and that we underestimate the ability of species, including humans, to find ways to adapt to the problem.

Botkin wrote a controversial editorial for the Wall Street Journal (Oct 17, 2007) arguing that global warming will not have much impact on life on Earth, and noted that: "the reality is that almost none of the millions of species have disappeared during the past 2.5 million years — with all of its various warming and cooling periods."

The editorial prompted several responses from within the scientific community, including this:

For the past 2.5 million years the climate has oscillated between interglacials which were (at most) a little warmer than today and glacials which were considerably colder than today. There is no precedent in the past 2.5 million years for so much warming so fast. The ecosystem has had 2.5 million years to adapt to glacial-interglacial swings, but we are asking it to adapt to a completely new climate in just a few centuries. The past is not a very good analog for the future in this case. And anyway, the human species can suffer quite a bit before we start talking extinction.
What did he say at the hearing?

"I want to state up front that we have been living through a warming trend driven by a variety of influences. However, it is my view that this is not unusual, and contrary to the characterizations by the IPCC….these environmental changes are not apocalyptic nor irreversible…..Yes, we have been living through a warming trend, no doubt about that. The rate of change we are experiencing is also not unprecedented, and the "mystery" of the warming "plateau" simply indicates the inherent complexity of our global biosphere. Change is normal, life on Earth is inherently risky; it always has been."

The Q & A

The lone witness for the defense was Michael Oppenheimer, the Albert G. Milbank Professor of Geosciences and International Affairs at Princeton University. He was selected by the Democrats, "because he's one of the foremost experts in the world and has been involved with the IPCC," a spokesperson for the Democratic contingent of the committee told Motherboard reporter Jason Koebler.

Koebler describes how things went down at the hearing after the experts presented their statements:

For two hours, climate change deniers interrupted, berated, and cut off Oppenheimer, while the other three other witnesses fielded softball questions from conservative lawmakers and dodged tougher ones from Democratic ones.

In fact, at one point, Rep. Larry Buchson (R-Ind.), who, seconds before had interrupted Oppenheimer and said he wasn't interested in hearing his views, wanted to "apologize on behalf of Congress" to Pielke for the aforementioned "juvenile and insulting questions trying to disparage the credibility" of witnesses who didn't take climate change seriously…..

Dana Rohrabacher [R-CA] pulled out the air quotes when he said "global warming," and took offense to Oppenheimer not being able to "capsulize" all the reasons why he believes that climate change is a big deal in 10 seconds. Smith suggested that the "only thing we know about [climate change models] is that they will be wrong" and suggested that "even if the US was completely eliminated, it's not going to have any discernible impact on global temperatures in the near or far future."

Paul Broun [R-GA] and Buchson noted their belief in the "scientific process" and suggested that they knew more about it because they are doctors (Broun is a dentist; Buchson is a surgeon).

So predictable, and such a waste of time. As I noted earlier, in principle, there is nothing wrong with assessing the methodology of such an important and influential report. But there are far better ways to do it than this.

The most noteworthy aspect of the IPCC is that it has worked far better than anyone anticipated. As Spencer Weart, the former director of the Center for History of Physics has written:

The IPCC's constitution should have been (and perhaps was intended to be) a recipe for paralysis. Instead, the panel turned its procedural restraints into a virtue: whatever it did manage to say would have unimpeachable authority.

Experts contributed their time as volunteers, writing working papers that drew on the latest studies. These were debated at length in correspondence and workshops. The IPCC scientists, initially 170 of them in a dozen workshops, worked hard and long to craft statements that nobody could fault on scientific grounds. The draft reports next went through a process of peer review, gathering comments from virtually every climate expert in the world. It was much like the process of reviewing articles submitted to a scientific journal, although with far more reviewers. All this followed the long-established practices, norms and traditions of science. The scientists found it easier than they had expected to reach a consensus. This undertaking was the first of its kind in terms of breadth, and the exhaustive level of review and revision.
If Congress only worked half as well.


Marriage is a right that belongs to any consenting adults. But an over-religious court official in Virginia has a message for atheists and any other non-Christian: you have no right to get married if you don’t believe in God.

Bud Roth is a court appointed officiant in Franklin County, Virginia. He performs wedding ceremonies for couples who go to the courthouse to get married. Atheists, however, have no right to get married as far as he’s concerned.

When Morgan Strong and Tamar Courtney contacted the county courthouse to seal their love for each other after six years together, they were directed to Roth. Roth refused to perform the ceremony at the courthouse and only agreed to marry the couple if they tied the knot at his church. A deal was struck and the cost and date were set. Strong and Courtney would go through the legal part of the ceremony at Roth’s church. That’s when the whole situation turned ugly.

Roth asked the couple about their religious beliefs and upon hearing that he would be performing a ceremony for an atheist and an agnostic, turned the couple away. Why? Because they “didn’t know where God was.” That’s right, Roth refused to marry the couple out of sheer religious bigotry. Disappointed, Morgan and Courtney decided to discuss the situation with Roth and they kindly recorded the conversation.

Upon asking why Roth denied them their right to wed, he replied:

“Because she’s agnostic and you’re an atheist. I will not marry you. You don’t believe in God… I just don’t marry anyone who does not believe in God [or] believes that there is a God someplace. So I’m not going to talk the issue over with you and I’m not going to argue about it, okay? I’m just not going to marry you. Correct?”

The couple contacted the county clerk, who was floored by their story. She suggested they contact the judge who appointed Roth in the first place. So they wrote a letter to Judge William Alexander who didn’t see any problem at all with a court officiant refusing to marry a couple simply because they don’t share his religious beliefs. The judge referred the couple to the other court appointed officiant who agreed to perform the civil ceremony this coming Monday.

But this incident raises serious concerns. First, a civil servant is supposed to serve the public. That means anyone. As long as a couple has a marriage license, there shouldn’t be any problem. Second, religious discrimination is wrong no matter the venue, but for it to occur at a courthouse by a court official is totally unacceptable. People go to get married at a courthouse to avoid religious pomp and circumstance and because it’s quicker. They don’t go there to have religion shoved down their throats. That’s why my wife and I married at a courthouse. Not because we didn’t believe in a god, but because we didn’t want religion to dominate our day.

Roth was wrong to refuse to perform the ceremony just because Morgan and Courtney don’t share his beliefs. He was also wrong to require them to get married at his church. He’s a COURT-APPOINTED OFFICIANT, for crying out loud! He’s a courthouse employee. Therefore, anyone who wishes to marry at the courthouse should be married at the courthouse. Even if he’s the one asked to perform the ceremony. He’s paid by taxpayers to do this task. He’s not paid to drag couples to church or to refuse to marry a couple because of his own religious beliefs. Separation of church and state is clearly being violated here by both Judge Alexander and Roth. If Roth were a private citizen, then he could refuse to marry anyone. But in this case, he’s NOT a private citizen. The people of Franklin County, Virginia should be embarrassed and outraged by this and they should demand a change be made. Because once religious discrimination infects our courts, anyone is at risk to have their rights and freedoms trampled on by self-righteous pricks in the name of Christianity.

this will interest no one

but i think it's an unusual look at open and very public disagreements b/w academics

too long to copy/paste:

Spamalot / TZT Brawler: what should your item be?
« on: May 30, 2014, 10:12:16 PM »
Not sure how many people are aware, but I threw together a preliminary version of a brawler (... though I began adding levels to it anyway, so maybe some kind of weird brawler/RPG combo), based on a 3D version I made of AD's 2D signature troll, in the game dev forum:,54400.msg1245142.html#msg1245142

I was thinking I might just give it up to work on other stuff for a while, but if I had specific projects to try to do justice to, that could help.

Right now I have 2 named weapons: an ax (named after solayce) and a shield (named after taket). What should your weapon be and why?

Google owns a lot of computers—perhaps a million servers stitched together into the fastest, most powerful artificial intelligence on the planet. But last August, Google teamed up with NASA to acquire what may be the search giant’s most powerful piece of hardware yet. It’s certainly the strangest.

Located at NASA Ames Research Center in Mountain View, California, a couple of miles from the Googleplex, the machine is literally a black box, 10 feet high. It’s mostly a freezer, and it contains a single, remarkable computer chip—based not on the usual silicon but on tiny loops of niobium wire, cooled to a temperature 150 times colder than deep space. The name of the box, and also the company that built it, is written in big, science-fiction-y letters on one side: D-WAVE. Executives from the company that built it say that the black box is the world’s first practical quantum computer, a device that uses radical new physics to crunch numbers faster than any comparable machine on earth. If they’re right, it’s a profound breakthrough. The question is: Are they?

Hartmut Neven, a computer scientist at Google, persuaded his bosses to go in with NASA on the D-Wave. His lab is now partly dedicated to pounding on the machine, throwing problems at it to see what it can do. An animated, academic-tongued German, Neven founded one of the first successful image-recognition firms; Google bought it in 2006 to do computer-vision work for projects ranging from Picasa to Google Glass. He works on a category of computational problems called optimization—finding the solution to mathematical conundrums with lots of constraints, like the best path among many possible routes to a destination, the right place to drill for oil, and efficient moves for a manufacturing robot. Optimization is a key part of Google’s seemingly magical facility with data, and Neven says the techniques the company uses are starting to peak. “They’re about as fast as they’ll ever be,” he says.

That leaves Google—and all of computer science, really—just two choices: Build ever bigger, more power-hungry silicon-based computers. Or find a new way out, a radical new approach to computation that can do in an instant what all those other million traditional machines, working together, could never pull off, even if they worked for years.

That, Neven hopes, is a quantum computer. A typical laptop and the hangars full of servers that power Google—what quantum scientists charmingly call “classical machines”—do math with “bits” that flip between 1 and 0, representing a single number in a calculation. But quantum computers use quantum bits, qubits, which can exist as 1s and 0s at the same time. They can operate as many numbers simultaneously. It’s a mind-bending, late-night-in-the-dorm-room concept that lets a quantum computer calculate at ridiculously fast speeds.

Unless it’s not a quantum computer at all. Quantum computing is so new and so weird that no one is entirely sure whether the D-Wave is a quantum computer or just a very quirky classical one.
Not even the people who build it know exactly how it works and what it can do. That’s what Neven is trying to figure out, sitting in his lab, week in, week out, patiently learning to talk to the D-Wave. If he can figure out the puzzle—what this box can do that nothing else can, and how—then boom. “It’s what we call ‘quantum supremacy,’” he says. “Essentially, something that cannot be matched anymore by classical machines.” It would be, in short, a new computer age.

A former wrestler short-listed for Canada’s Olympic team, D-Wave founder Geordie Rose is barrel-chested and possessed of arms that look ready to pin skeptics to the ground. When I meet him at D-Wave’s headquarters in Burnaby, British Columbia, he wears a persistent, slight frown beneath bushy eyebrows. “We want to be the kind of company that Intel, Microsoft, Google are,” Rose says. “The big flagship $100 billion enterprises that spawn entirely new types of technology and ecosystems. And I think we’re close. What we’re trying to do is build the most kick-ass computers that have ever existed in the history of the world.”

The office is a bustle of activity; in the back rooms technicians peer into microscopes, looking for imperfections in the latest batch of quantum chips to come out of their fab lab. A pair of shoulder-high helium tanks stand next to three massive black metal cases, where more techs attempt to weave together their spilt guts of wires. Jeremy Hilton, D-Wave’s vice president of processor development, gestures to one of the cases. “They look nice, but appropriately for a startup, they’re all just inexpensive custom components. We buy that stuff and snap it together.” The really expensive work was figuring out how to build a quantum computer in the first place.

Like a lot of exciting ideas in physics, this one originates with Richard Feynman. In the 1980s, he suggested that quantum computing would allow for some radical new math. Up here in the macroscale universe, to our macroscale brains, matter looks pretty stable. But that’s because we can’t perceive the subatomic, quantum scale. Way down there, matter is much stranger. Photons—electromagnetic energy such as light and x-rays—can act like waves or like particles, depending on how you look at them, for example. Or, even more weirdly, if you link the quantum properties of two subatomic particles, changing one changes the other in the exact same way. It’s called entanglement, and it works even if they’re miles apart, via an unknown mechanism that seems to move faster than the speed of light.

Knowing all this, Feynman suggested that if you could control the properties of subatomic particles, you could hold them in a state of superposition—being more than one thing at once. This would, he argued, allow for new forms of computation. In a classical computer, bits are actually electrical charge—on or off, 1 or 0. In a quantum computer, they could be both at the same time.

It was just a thought experiment until 1994, when mathematician Peter Shor hit upon a killer app: a quantum algorithm that could find the prime factors of massive numbers. Cryptography, the science of making and breaking codes, relies on a quirk of math, which is that if you multiply two large prime numbers together, it’s devilishly hard to break the answer back down into its constituent parts. You need huge amounts of processing power and lots of time. But if you had a quantum computer and Shor’s algorithm, you could cheat that math—and destroy all existing cryptography. “Suddenly,” says John Smolin, a quantum computer researcher at IBM, “everybody was into it.”

That includes Geordie Rose. A child of two academics, he grew up in the backwoods of Ontario and became fascinated by physics and artificial intelligence. While pursuing his doctorate at the University of British Columbia in 1999, he read Explorations in Quantum Computing, one of the first books to theorize how a quantum computer might work, written by NASA scientist—and former research assistant to Stephen Hawking—Colin Williams. (Williams now works at D-Wave.)

Reading the book, Rose had two epiphanies. First, he wasn’t going to make it in academia. “I never was able to find a place in science,” he says. But he felt he had the bullheaded tenacity, honed by years of wrestling, to be an entrepreneur. “I was good at putting together things that were really ambitious, without thinking they were impossible.” At a time when lots of smart people argued that quantum computers could never work, he fell in love with the idea of not only making one but selling it.

With about $100,000 in seed funding from an entrepreneurship professor, Rose and a group of university colleagues founded D-Wave. They aimed at an incubator model, setting out to find and invest in whoever was on track to make a practical, working device. The problem: Nobody was close.

At the time, most scientists were pursuing a version of quantum computing called the gate model. In this architecture, you trap individual ions or photons to use as qubits and chain them together in logic gates like the ones in regular computer circuits—the ands, ors, nots, and so on that assemble into how a computer thinks. The difference, of course, is that the qubits could interact in much more complex ways, thanks to superposition, entanglement, and interference.

But qubits really don’t like to stay in a state of super­position, what’s called coherence. A single molecule of air can knock a qubit out of coherence. The simple act of observing the quantum world collapses all of its every-number-at-once quantumness into stochastic, humdrum, non­quantum reality. So you have to shield qubits—from everything. Heat or other “noise,” in physics terms, screws up a quantum computer, rendering it useless.

You’re left with a gorgeous paradox: Even if you successfully run a calculation, you can’t easily find that out, because looking at it collapses your superpositioned quantum calculation to a single state, picked at random from all possible superpositions and thus likely totally wrong. You ask the computer for the answer and get garbage.

Lashed to these unforgiving physics, scientists had built systems with only two or three qubits at best. They were wickedly fast but too underpowered to solve any but the most prosaic, lab-scale problems. But Rose didn’t want just two or three qubits. He wanted 1,000. And he wanted a device he could sell, within 10 years. He needed a way to make qubits that weren’t so fragile.


In 2003, he found one. Rose met Eric Ladizinsky, a tall, sporty scientist at NASA’s Jet Propulsion Lab who was an expert in superconducting quantum interference devices, or Squids. When Ladizinsky supercooled teensy loops of niobium metal to near absolute zero, magnetic fields ran around the loops in two opposite directions at once. To a physicist, electricity and magnetism are the same thing, so Ladizinsky realized he was seeing superpositioning of electrons. He also suspected these loops could become entangled, and that the charges could quantum-tunnel through the chip from one loop to another. In other words, he could use the niobium loops as qubits. (The field running in one direction would be a 1; the opposing field would be a 0.) The best part: The loops themselves were relatively big, a fraction of a millimeter. A regular microchip fab lab could build them.

The two men thought about using the niobium loops to make a gate-model computer, but they worried the gate model would be too susceptible to noise and timing errors. They had an alternative, though—an architecture that seemed easier to build. Called adiabatic annealing, it could perform only one specific computational trick: solving those rule-laden optimization problems. It wouldn’t be a general-purpose computer, but optimization is enormously valuable. Anyone who uses machine learning—Google, Wall Street, medicine—does it all the time. It’s how you train an artificial intelligence to recognize patterns. It’s familiar. It’s hard. And, Rose realized, it would have an immediate market value if they could do it faster.

In a traditional computer, annealing works like this: You mathematically translate your problem into a landscape of peaks and valleys. The goal is to try to find the lowest valley, which represents the optimized state of the system. In this metaphor, the computer rolls a rock around the problem-­scape until it settles into the lowest-possible valley, and that’s your answer. But a conventional computer often gets stuck in a valley that isn’t really lowest at all. The algorithm can’t see over the edge of the nearest mountain to know if there’s an even lower vale. A quantum annealer, Rose and Ladizinsky realized, could perform tricks that avoid this limitation. They could take a chip full of qubits and tune each one to a higher or lower energy state, turning the chip into a representation of the rocky landscape. But thanks to superposition and entanglement between the qubits, the chip could computationally tunnel through the landscape. It would be far less likely to get stuck in a valley that wasn’t the lowest, and it would find an answer far more quickly.

Better yet, Rose and Ladizinsky predicted that a quantum annealer wouldn’t be as fragile as a gate system. They wouldn’t need to precisely time the interactions of individual qubits. And they suspected their machine would work even if only some of the qubits were entangled or tunneling; those functioning qubits would still help solve the problem more quickly. And since the answer a quantum annealer kicks out is the lowest energy state, they also expected it would be more robust, more likely to survive the observation an operator has to make to get the answer out. “The adiabatic model is intrinsically just less corrupted by noise,” says Williams, the guy who wrote the book that got Rose started.

By 2003, that vision was attracting investment. Venture capitalist Steve Jurvetson wanted to get in on what he saw as the next big wave of computing that would propel machine intelligence everywhere—from search engines to self-driving cars. A smart Wall Street bank, Jurvetson says, could get a huge edge on its competition by being the first to use a quantum computer to create ever-smarter trading algorithms. He imagines himself as a banker with a D-Wave machine: “A torrent of cash comes my way if I do this well,” he says. And for a bank, the $10 million cost of a computer is peanuts. “Oh, by the way, maybe I buy exclusive access to D-Wave. Maybe I buy all your capacity! That’s just, like, a no-brainer to me.” D-Wave pulled in $100 million from investors like Jeff Bezos and In-Q-Tel, the venture capital arm of the CIA.

The D-Wave team huddled in a rented lab at the University of British Columbia, trying to learn how to control those tiny loops of niobium. Soon they had a one-qubit system. “It was a crappy, duct-taped-together thing,” Rose says. “Then we had two qubits. And then four.” When their designs got more complicated, they moved to larger-scale industrial fabrication.

As I watch, Hilton pulls out one of the wafers just back from the fab facility. It’s a shiny black disc the size of a large dinner plate, inscribed with 130 copies of their latest 512-qubit chip. Peering in closely, I can just make out the chips, each about 3 millimeters square. The niobium wire for each qubit is only 2 microns wide, but it’s 700 microns long. If you squint very closely you can spot one: a piece of the quantum world, visible to the naked eye.

Hilton walks to one of the giant, refrigerated D-Wave black boxes and opens the door. Inside, an inverted pyramid of wire-bedecked, gold-plated copper discs hangs from the ceiling. This is the guts of the device. It looks like a steampunk chandelier, but as Hilton explains, the gold plating is key: It conducts heat—noise—up and out of the device. At the bottom of the chandelier, hanging at chest height, is what they call the coffee can, the enclosure for the chip. “This is where we go from our everyday world,” Hilton says, “to a unique place in the universe.”

By 2007, D-Wave had managed to produce a 16-qubit system, the first one complicated enough to run actual problems. They gave it three real-world challenges: solving a sudoku, sorting people at a dinner table, and matching a molecule to a set of molecules in a database. The problems wouldn’t challenge a decrepit Dell. But they were all about optimization, and the chip actually solved them. “That was really the first time when I said, holy crap, you know, this thing’s actually doing what we designed it to do,” Rose says. “Back then we had no idea if it was going to work at all.” But 16 qubits wasn’t nearly enough to tackle a problem that would be of value to a paying customer. He kept pushing his team, producing up to three new designs a year, always aiming to cram more qubits together.

When the team gathers for lunch in D-Wave’s conference room, Rose jokes about his own reputation as a hard-driving taskmaster. Hilton is walking around showing off the 512-qubit chip that Google just bought, but Rose is demanding the 1,000-qubit one. “We’re never happy,” Rose says. “We always want something better.”

“Geordie always focuses on the trajectory,” Hilton says. “He always wants what’s next.”

In 2010, D-Wave’s first customers came calling. Lockheed Martin was wrestling with particularly tough optimization problems in their flight control systems. So a manager named Greg Tallant took a team to Burnaby. “We were intrigued with what we saw,” Tallant says. But they wanted proof. They gave D-Wave a test: Find the error in an algorithm. Within a few weeks, D-Wave developed a way to program its machine to find the error. Convinced, Lockheed Martin leased a $10 million, 128-qubit machine that would live at a USC lab.

The next clients were Google and NASA. Hartmut Neven was another old friend of Rose’s; they shared a fascination with machine intelligence, and Neven had long hoped to start a quantum lab at Google. NASA was intrigued, because it often faced wickedly hard best-fit problems. “We have the Curiosity rover on Mars, and if we want to move it from point A to point B there are a lot of possible routes—that’s a classic optimization problem,” says NASA’s Rupak Biswas. But before Google executives would put down millions, they wanted to know the D-Wave worked. In the spring of 2013, Rose agreed to hire a third party to run a series of Neven-designed tests, pitting D-Wave against traditional optimizers running on regular computers. Catherine McGeoch, a computer scientist at Amherst College, agreed to run the tests, but only under the condition that she report her results publicly.

Rose quietly panicked. For all of his bluster—D-Wave routinely put out press releases boasting about its new devices—he wasn’t sure his black box would win the shoot-out. “One of the possible outcomes was that the thing would totally tank and suck,” Rose says. “And then she would publish all this stuff and it would be a horrible mess.”


McGeoch pitted the D-Wave against three pieces of off-the-shelf software. One was IBM’s CPLEX, a tool used by ConAgra, for instance, to crunch global market and weather data to find the optimum price at which to sell flour; the other two were well-known open source optimizers. McGeoch picked three mathematically chewy problems and ran them through the D-Wave and through an ordinary Lenovo desktop running the other software.

The results? D-Wave’s machine matched the competition—and in one case dramatically beat it. On two of the math problems, the D-Wave worked at the same pace as the classical solvers, hitting roughly the same accuracy. But on the hardest problem, it was much speedier, finding the answer in less than half a second, while CPLEX took half an hour. The D-Wave was 3,600 times faster. For the first time, D-Wave had seemingly objective evidence that its machine worked quantum magic. Rose was relieved; he later hired McGeoch as his new head of benchmarking. Google and NASA got a machine. D-Wave was now the first quantum computer company with real, commercial sales.

That’s when its troubles began.

Quantum scientists had long been skeptical of D-Wave. Academics tend to get suspicious when the private sector claims massive leaps in scientific knowledge. They frown on “science by press release,” and Geordie Rose’s bombastic proclamations smelled wrong. Back then, D-Wave had published little about its system. When Rose held a press conference in 2007 to show off the 16-bit system, MIT quantum scientist Scott Aaronson wrote that the computer was “about as useful for industrial optimization problems as a roast-beef sandwich.” Plus, scientists doubted D-Wave could have gotten so far ahead of the state of the art. The most qubits anyone had ever got working was eight. So for D-Wave to boast of a 500-qubit machine? Nonsense. “They never seemed properly concerned about the noise model,” as IBM’s Smolin says. “Pretty early on, people became dismissive of it and we all sort of moved on.”

That changed when Lockheed Martin and USC acquired their quantum machine in 2011. Scientists realized they could finally test this mysterious box and see whether it stood up to the hype. Within months of the D-Wave installation at USC, researchers worldwide came calling, asking to run tests.

The first question was simple: Was the D-Wave system actually quantum? It might be solving problems, but if noise was disentangling the qubits, it was just an expensive classical computer, operating adiabatically but not with quantum speed. Daniel Lidar, a quantum scientist at USC who’d advised Lockheed on its D-Wave deal, figured out a clever way to answer the question. He ran thousands of instances of a problem on the D-Wave and charted the machine’s “success probability”—how likely it was to get the problem right—against the number of times it tried. The final curve was U-shaped. In other words, most of the time the machine either entirely succeeded or entirely failed. When he ran the same problems on a classical computer with an annealing optimizer, the pattern was different: The distribution clustered in the center, like a hill; this machine was sort of likely to get the problems right. Evidently, the D-Wave didn’t behave like an old-fashioned computer.
Lidar also ran the problems on a classical algorithm that simulated the way a quantum computer would solve a problem. The simulation wasn’t superfast, but it thought the same way a quantum computer did. And sure enough, it produced the U, like the D-Wave shape. At minimum the D-Wave acts more like a simulation of a quantum computer than like a conventional one.

Even Scott Aaronson was swayed. He told me the results were “reasonable evidence” of quantum behavior. If you look at the pattern of answers being produced, “then entanglement would be hard to avoid.” It’s the same message I heard from most scientists.

But to really be called a quantum computer, you also have to be, as Aaronson puts it, “productively quantum.” The behavior has to help things move faster. Quantum scientists pointed out that McGeoch hadn’t orchestrated a fair fight. D-Wave’s machine was a specialized device built to do optimizing problems. McGeoch had compared it to off-the-shelf software.

Matthias Troyer set out to even up the odds. A computer scientist at the Institute for Theoretical Physics in Zurich, Troyer tapped programming wiz Sergei Isakov to hot-rod a 20-year-old software optimizer designed for Cray supercomputers. Isakov spent a few weeks tuning it , and when it was ready, Troyer and Isakov’s team fed tens of thousands of problems into USC’s D-Wave and into their new and improved solver on an Intel desktop.

This time, the D-Wave wasn’t faster at all. In only one small subset of the problems did it race ahead of the conventional machine. Mostly, it only kept pace. “We find no evidence of quantum speedup,” Troyer’s paper soberly concluded. Rose had spent millions of dollars, but his machine couldn’t beat an Intel box.

What’s worse, as the problems got harder, the amount of time the D-Wave needed to solve them rose—at roughly the same rate as the old-school computers. This, Troyer says, is particularly bad news. If the D-Wave really was harnessing quantum dynamics, you’d expect the opposite. As the problems get harder, it should pull away from the Intels. Troyer and his team concluded that D-Wave did in fact have some quantum behavior, but it wasn’t using it productively. Why? Possibly, Troyer and Lidar say, it doesn’t have enough “coherence time.” For some reason its qubits aren’t qubitting—the quantum state of the niobium loops isn’t sustained.

One way to fix this problem, if indeed it’s a problem, might be to have more qubits running error correction. Lidar suspects D-Wave would need another 100—maybe 1,000—qubits checking its operations (though the physics here are so weird and new, he’s not sure how error correction would work). “I think that almost everybody would agree that without error correction this plane is not going to take off,” Lidar says.

Rose’s response to the new tests: “It’s total bullshit.”

D-Wave, he says, is a scrappy startup pushing a radical new computer, crafted from nothing by a handful of folks in Canada. From this point of view, Troyer had the edge. Sure, he was using standard Intel machines and classical software, but those benefited from decades’ and trillions of dollars’ worth of investment. The D-Wave acquitted itself admirably just by keeping pace. Troyer “had the best algorithm ever developed by a team of the top scientists in the world, finely tuned to compete on what this processor does, running on the fastest processors that humans have ever been able to build,” Rose says. And the D-Wave “is now competitive with those things, which is a remarkable step.”

But what about the speed issues? “Calibration errors,” he says. Programming a problem into the D-Wave is a manual process, tuning each qubit to the right level on the problem-solving landscape. If you don’t set those dials precisely right, “you might be specifying the wrong problem on the chip,” Rose says. As for noise, he admits it’s still an issue, but the next chip—the 1,000-qubit version codenamed Washington, coming out this fall—will reduce noise yet more. His team plans to replace the niobium loops with aluminum to reduce oxide buildup. “I don’t care if you build [a traditional computer] the size of the moon with interconnection at the speed of light, running the best algorithm that Google has ever come up with. It won’t matter, ’cause this thing will still kick your ass,” Rose says. Then he backs off a bit. “OK, everybody wants to get to that point—and Washington’s not gonna get us there. But Washington is a step in that direction.”

Or here’s another way to look at it, he tells me. Maybe the real problem with people trying to assess D-Wave is that they’re asking the wrong questions. Maybe his machine needs harder problems.

On its face, this sounds crazy. If plain old Intels are beating the D-Wave, why would the D-Wave win if the problems got tougher? Because the tests Troyer threw at the machine were random. On a tiny subset of those problems, the D-Wave system did better. Rose thinks the key will be zooming in on those success stories and figuring out what sets them apart—what advantage D-Wave had in those cases over the classical machine. In other words, he needs to figure out what sort of problems his machine is uniquely good at. Helmut Katzgraber, a quantum scientist at Texas A&M, cowrote a paper in April bolstering Rose’s point of view. Katzgraber argued that the optimization problems everyone was tossing at the D-Wave were, indeed, too simple. The Intel machines could easily keep pace. If you think of the problem as a rugged surface and the solvers as trying to find the lowest spot, these problems “look like a bumpy golf course. What I’m proposing is something that looks like the Alps,” he says.

In one sense, this sounds like a classic case of moving the goalposts. D-Wave will just keep on redefining the problem until it wins. But D-Wave’s customers believe this is, in fact, what they need to do. They’re testing and retesting the machine to figure out what it’s good at. At Lockheed Martin, Greg Tallant has found that some problems run faster on the D-Wave and some don’t. At Google, Neven has run over 500,000 problems on his D-Wave and finds the same. He’s used the D-Wave to train image-recognizing algorithms for mobile phones that are more efficient than any before. He produced a car-recognition algorithm better than anything he could do on a regular silicon machine. He’s also working on a way for Google Glass to detect when you’re winking (on purpose) and snap a picture. “When surgeons go into surgery they have many scalpels, a big one, a small one,” he says. “You have to think of quantum optimization as the sharp scalpel—the specific tool.”

The dream of quantum computing has always been shrouded in sci-fi hope and hoopla—with giddy predictions of busted crypto, multiverse calculations, and the entire world of computation turned upside down. But it may be that quantum computing arrives in a slower, sideways fashion: as a set of devices used rarely, in the odd places where the problems we have are spoken in their curious language. Quantum computing won’t run on your phone—but maybe some quantum process of Google’s will be key in training the phone to recognize your vocal quirks and make voice recognition better. Maybe it’ll finally teach computers to recognize faces or luggage. Or maybe, like the integrated circuit before it, no one will figure out the best-use cases until they have hardware that works reliably. It’s a more modest way to look at this long-heralded thunderbolt of a technology. But this may be how the quantum era begins: not with a bang, but a glimmer.

General Discussion / Piketty: Another Econ Data Error Debacle?
« on: May 24, 2014, 04:12:37 AM »
Another fight's brewing over alleged economist data fuck-ups, this time over Piketty's stuff, who's been in the news for his work on growing wealth inequality. Curious to see if this evolves the way the Reinhart & Rogoff one did on national debt.

FT writer Chris Giles critiques his data here:

Piketty replies to the criticism here:

Spamalot / hey sors, you know any good image manipulation guides?
« on: May 18, 2014, 11:18:38 PM »
or did you just learn photoshop by googling what you wanted to do and following somebody else's stuff?

trying to get a handle on the basics of gimp.

Spamalot / anime thread # 7
« on: May 03, 2014, 12:19:32 AM »
hey anime nerds

have any of the rest of you watched the Jojo's Bizarre Adventure series?

i avoided it for a long time because it.. sounded fucking awful.. and it is completely ridiculous, but in a fun over-the-top, stupidly badass manly kind've way. and it's really well done for what it is.

would do business w/ again.

Spamalot / ho ho ho
« on: February 06, 2014, 09:47:53 PM »
sam zek motherfuckers, 2nd entry, and if the alphabet's to blame it's only because i'm smarter than your poor ass


Newt bard. In his original incarnation, known for well-reasoned SZ board posts which were way too long for anyone to read. Account changed hands; now Agrul is one of the primary newt trainers."

Spamalot / workout thread
« on: January 18, 2014, 02:48:53 PM »
can only find old workout thread as weird gobbledygook google archive :,46647.0/wap2.html

signed up for the Monument Avenue 10k, gonna beat my 49:14 time from 2 years ago & try to qualify for one of the fastest seeds this year instead of just qualifying for any old seed. the poewr of DDR compels me :wayne:

did a weighted run the other day in prep, carried two 5 lb wrist weights in my hands. only made it half my usual 6.5 miles w/ them & am sore as shit today, gonna try it w/ the weight vest next. comin' for u 10k race time

Spamalot / to luxberry
« on: January 14, 2014, 03:22:35 PM »

Agrulian Archives / Science/Math News Articles
« on: January 11, 2014, 02:03:06 PM »
Gonna use this thread to keep track of news articles I think are cool/interesting.

To start w/:

Metamaterials Science gives new hope to analog computing

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