Various web links I found to be of interest recently.
Peter Beinart
As David Harris, head of the American Jewish Committee, put it last year, "To deny the Jewish people, of all the peoples on earth, the right to self-determination surely is discriminatory."
All the peoples on earth? The Kurds don't have their own state.
Neither do the Basques, Catalans, Scots, Kashmiris, Tibetans, Abkhazians,
Ossetians, Lombards, Igbo, Oromo, Uyghurs, Tamils, Quebecois nor
dozens of other peoples who have created nationalist movements
to seek self-determination but failed to achieve it.
...
In the real world, anti-Zionism and anti-Semitism don't always go together.
Before Israel's creation, some of the world leaders who most ardently
promoted Jewish statehood did so because they did not want Jews
in their own countries.
...
If anti-Semitism exists without anti-Zionism, anti-Zionism also clearly exists without anti-Semitism.
Consider the Satmar, the largest Hasidic sect in the world. In 2017, twenty thousand Satmar men - a larger crowd than attended that year's AIPAC Policy Conference - filled Brooklyn's Barclays Center for a rally aimed at showing, in the words of one organizer, that "We feel very strongly that there should not be and could not be a State of Israel before the Messiah comes."
Algorithms are so good at racism that it will hopefully become impossible to ignore.
Because, if we believe tech gurus at least, the Trolley Problem is about to become of huge real-world importance. Human beings might not find themselves in all that many Trolley Problem-style scenarios over the course of their lives, but soon we're going to start seeing self-driving cars on our streets, and they're going to have to make these judgments all the time. Self-driving cars are potentially going to find themselves in all sorts of accident scenarios where the AI controlling them has to decide which human lives it ought to preserve. But in practice what this means is that human beings will have to grapple with the Trolley Problem - since they're going to be responsible for programming the AIs.
As Autor observes, though auto manufacturers "employ industrial robots to install windshields ... aftermarket windshield replacement companies employ technicians, not robots." It turns out that "removing a broken windshield, preparing the windshield frame to accept a replacement, and fitting a replacement into that frame demand more real-time adaptability than any contemporary robot can cost-effectively approach." In other words, automation depends on fully controlled conditions, and humans will never achieve full control of the entire environment.
Some might counter that artificial-intelligence applications could develop a capacity to absorb "tacit knowledge." Yet even if machine-learning algorithms could communicate back to us why they have made certain decisions, they will only ever work in restricted environmental domains. The wide range of specific conditions that they need in order to function properly renders them brittle and fragile, particularly when compared to the robust adaptability of human beings.
These possibilities reveal the real threat from Baumol' s disease: not that work will flow toward less-productive industries, which is inevitable, but that gains from rising productivity are unevenly shared. When firms in highly productive industries crave highly credentialed workers, it is the pay of similar workers elsewhere in the economy-of doctors, say-that rises in response. That worsens inequality, as low-income workers must still pay higher prices for essential services like health care. Even so, the productivity growth that drives cost disease could make everyone better off. But governments often do too little to tax the winners and compensate the losers. And politicians who do not understand the Baumol effect sometimes cap spending on education and health. Unsurprisingly, since they misunderstand the diagnosis, the treatment they prescribe makes the ailment worse.
We consider how valid conclusions often lay hidden within research reports, masked by plausible but unjustified conclusions reached in those reports. We employ several well-known and cross-cutting examples from the psychological literature to illustrate how, independent (or in the absence) of replicability difficulties or questionable research practices leading to false positives, motivated reasoning and confirmation biases can lead to drawing unjustified conclusions. In describing these examples, we review strategies and methods by which researchers can identify such practices in their own and others' research reports. These strategies and methods can unmask hidden phenomena that may conflict with researchers' preferred narratives, in order to ultimately produce more sound and valid scientific conclusions. We conclude with general recommendations for how social psychologists can limit the influence of interpretive biases in their own and others' research, and thereby elevate the scientific status and validity of social psychology.
The ability to identify medical reversals and other low-value medical practices is an essential prerequisite for efforts to reduce spending on such practices. Through an analysis of more than 3000 randomized controlled trials (RCTs) published in three leading medical journals (the Journal of the American Medical Association, the Lancet, and the New England Journal of Medicine), we have identified 396 medical reversals. Most of the studies (92%) were conducted on populations in high-income countries, cardiovascular disease was the most common medical category (20%), and medication was the most common type of intervention (33%).
Most Chinese people will cheerfully acknowledge that their language is hard, maybe the hardest on earth.
Nowadays even songs can have shareholders. Hipgnosis Songs Fund is steadily building up a catalogue of hit songs and inviting big institutional investors to share in the proceeds. That means a much wider group of people can see an income from music royalties. The fund floated on the London Stock Exchange in July 2018 and recently published its first-ever annual results.
Dean A. Haycock Ph.D.
Authoritarian and virtuous characters, common traits of dictators, paths to tyranny.