Source: The Mystery of Why Japanese People Are Having So Few Babies – The Atlantic
Many point to unromantic 20-somethings and women’s entry into the workforce, but an overlooked factor is the trouble young men have in finding steady, well-paid jobs.
Japan’s birth rate may be falling because there are fewer good opportunities for young people, and especially men, in the country’s economy. In a country where men are still widely expected to be breadwinners and support families, a lack of good jobs may be creating a class of men who don’t marry and have children because they—and their potential partners—know they can’t afford to.
Japan’s problems have implications for the United States, where temporary jobs are common, and where union power is getting weaker with every year. As I’ve written before, men are struggling in many regions of the country because of the decline of manufacturing and the opioid epidemic. And studies have shown that as men’s economic prospects decline, so do their chances of marrying. The U.S.’s fertility rate is already at historic lows—and worsening economic conditions for men could further depress it.
Source: The team that took us to Pluto briefly spotted their next target at the edge of the Solar System – The Verge
The object in question is called 2014 MU69, and it’s thought to be an incredibly old space rock that’s remained relatively unchanged since the Solar System first formed 4.6 billion years ago. But tracking 2014 MU69 has been pretty tough. It’s only about 30 miles wide, and it orbits over 4 billion miles from Earth. … Using the Hubble data, along with precise star positions measured by Europe’s Gaia satellite, the team predicted various times when 2014 MU69 might pass directly in front of a star. … However, the first two times the scientists tried to see the occultation, they didn’t see the object’s shadow. The first attempt was on June 3rd, with two separate teams looking in Argentina and South Africa, and the scientists tried again on July 10th with NASA’s SOFIA airplane — a flying observatory — as it flew over the Pacific Ocean. It wasn’t until this weekend, just before midnight Eastern Time on Sunday, that the mission team finally caught the occultation while huddled around telescopes in Chubut and Santa Cruz, Argentina.
This is why science is amazing. It is not always correct. It has to be updated constantly with new information in order to perform even the most trivially different task (e.g. track a new star or a different space rock). But the cumulative knowledge gained thereby let’s us do incredible things, like predict when an object only about 30 miles wide and more than 4 billion miles away will pass between a particular place on Earth and a star that is light years away correctly enough to put a telescope at that place and watch it happen.
Source: The Myth of Drug Expiration Dates – ProPublica
Hospitals and pharmacies are required to toss expired drugs, no matter how expensive or vital. Meanwhile the FDA has long known that many remain safe and potent for years longer.
The federal agencies that stockpile drugs — including the military, the Centers for Disease Control and Prevention and the Department of Veterans Affairs — have long realized the savings in revisiting expiration dates.
In 1986, the Air Force, hoping to save on replacement costs, asked the FDA if certain drugs’ expiration dates could be extended. In response, the FDA and Defense Department created the Shelf Life Extension Program.
Each year, drugs from the stockpiles are selected based on their value and pending expiration and analyzed in batches to determine whether their end dates could be safely extended. For several decades, the program has found that the actual shelf life of many drugs is well beyond the original expiration dates.
A 2006 study of 122 drugs tested by the program showed that two-thirds of the expired medications were stable every time a lot was tested. Each of them had their expiration dates extended, on average, by more than four years, according to research published in the Journal of Pharmaceutical Sciences.
I worry that people don’t adequately separate two kinds of caution. Call them local caution and global caution. Suppose some new spacecraft is about to be launched. A hundred experts have evaluated it and determined that it’s safe. But some low-ranking engineer at NASA who happens to have some personal familiarity with the components involved looks at the schematics and just has a really bad feeling. It’s not that there’s any specific glaring flaw. It’s not any of the known problems that have ever led to spacecraft failure before. Just that a lot of the parts weren’t quite designed to go together in exactly that way, and that without being entirely able to explain his reasoning, he would not be the least bit surprised if that spacecraft exploded.
What is the cautious thing to do? The locally cautious response is for the engineer to accept that a hundred experts probably know better than he does. To cautiously remind himself that it’s unlikely he would discover a new spacecraft failure mode unlike any before. To cautiously admit that grounding a spacecraft on an intuition would be crazy. But the globally cautious response is to run screaming into the NASA director’s office, demanding that he stop the launch immediately until there can be a full review of everything. There’s a sense in which this is rash and ignores all sorts of generally wise and time-tested heuristics like the ones above. But if by “caution” you mean you want as few astronauts as possible to end up as smithereens, it’s the way to go.
Source: Two Kinds Of Caution | Slate Star Codex
A claim increasingly heard on campus will make them more anxious and more willing to justify physical harm.
Source: Controversial Speeches on Campus Are Not Violence – The Atlantic
We think the mental-health crisis on campus is better understood as a crisis of resilience. … As Van Jones put it in response to a question by David Axelrod about how progressive students should react to ideologically offensive speakers on campus:
I don’t want you to be safe, ideologically. I don’t want you to be safe, emotionally. I want you to be strong. That’s different. I’m not going to pave the jungle for you. Put on some boots, and learn how to deal with adversity. I’m not going to take all the weights out of the gym; that’s the whole point of the gym. This is the gym.
The implication of this expansive use of the word “violence” is that “we” are justified in punching and pepper-spraying “them,” even if all they did was say words.
Free speech, properly understood, is not violence. It is a cure for violence. … Freedom of speech is the eternally radical idea that individuals will try to settle their differences through debate and discussion, through evidence and attempts at persuasion, rather than through the coercive power of administrative authorities—or violence.
The conflation of words with violence is not a new or progressive idea invented on college campuses in the last two years. It is an ancient and regressive idea. Americans should all be troubled that it is becoming popular again—especially on college campuses, where it least belongs.
“Meanwhile, the poor Babel fish, by effectively removing all barriers to communication between different races and cultures, has caused more and bloodier wars than anything else in the history of creation.”
— ‘The Hitchhikers Guide to the Galaxy’ by Douglas Adams
Why is the world moving towards a more authoritarian kind of rule all of a sudden, and why is this happening now. Me, I blame the Babel Fish.
Source: I Blame The Babel Fish · Jacques Mattheij
The cost of almost all forms of communication, written, voice, video, worldwide to an unbelievably large audience is now essentially zero. The language barrier is still there but automatic translation is getting better and better and it won’t be forever or we really can communicate with everybody, instantaneously. That kind of power – because it is a power, I don’t doubt that one bit – comes with great responsibility.
If what you say or write is heard only by people already in your environment, who know you and who can apply some contextual filters then the damage that you can do is somewhat limited.
But if you start handing out megaphones that can reach untold millions of people in a heartbeat, and combine that with the unfiltered, raw output and responses of another couple of million of people then something qualitatively changes
Removing barriers is generally good, and should be welcomed. But we also should be aware that those barriers may have had positive sides and that as a species we are not very well positioned to deal with such immense changes in a very short time.
Great power comes with great responsibility, the power to communicate with anybody instantaneously at zero cost is such a power.
Source: The limitations of deep learning
In general, anything that requires reasoning—like programming, or applying the scientific method—long-term planning, and algorithmic-like data manipulation, is out of reach for deep learning models, no matter how much data you throw at them.
This is because a deep learning model is “just” a chain of simple, continuous geometric transformations mapping one vector space into another. All it can do is map one data manifold X into another manifold Y, assuming the existence of a learnable continuous transform from X to Y, and the availability of a dense sampling of X:Y to use as training data. So even though a deep learning model can be interpreted as a kind of program, inversely most programs cannot be expressed as deep learning models—for most tasks, either there exists no corresponding practically-sized deep neural network that solves the task, or even if there exists one, it may not be learnable, i.e. the corresponding geometric transform may be far too complex, or there may not be appropriate data available to learn it.
Most of the country understands that when it comes to government, you pay for what you get.
Source: Why Canada Is Able to Do Things Better – The Atlantic
I’ve come to focus on a more mundane explanation: The United States is falling apart because—unlike Canada and other wealthy countries—the American public sector simply doesn’t have the funds required to keep the nation stitched together. A country where impoverished citizens rely on crowdfunding to finance medical operations isn’t a country that can protect the health of its citizens. A country that can’t ensure the daily operation of Penn Station isn’t a country that can prevent transportation gridlock. A country that contracts out the operations of prisons to the lowest private bidder isn’t a country that can rehabilitate its criminals.
The Organization for Economic Co-Operation and Development (OECD), a group of 35 wealthy countries, ranks its members by overall tax burden—that is, total tax revenues at every level of government, added together and then expressed as a percentage of GDP—and in latest year for which data is available, 2014, the United States came in fourth to last. Its tax burden was 25.9 percent—substantially less than the OECD average, 34.2 percent. If the United States followed that mean OECD rate, there would be about an extra $1.5 trillion annually for governments to spend on better schools, safer roads, better-trained police, and more accessible health care.
It’s really quite simple: When Canadian governments need more money, they raise taxes.
“If you’ve built a watch, you have a much better sense of how that watch works than if you bought it and read a manual.”
Source: How company training models will change with AI — Quartz
Here’s the problem: Knight’s knowledge about how to do his job manually—his memorization of the star-shaped pattern in which he fastens the bolts and the understanding of how to do so —still has value. It allows him to understand if the machine is making a mistake, and when its process could be improved.
Knight, however, won’t be around forever. Future workers who do his job won’t have his experience and won’t be able to double-check the machines. So how will they be trained?
Deloitte CEO Cathy Engelbert says new technology capable of scanning and reviewing thousands of contracts–an entire year of human work–in an hour will mean the firm needs fewer entry-level workers and more workers with experience and judgment. But, “where do [middle-level employees] get that experience and judgment?”
Training programs won’t have to teach them the automated processes, but they will need to identify and teach skills that they would have learned by doing manual processes over and over again.