the GI Bill provided a range of benefits to returning World War II veterans including low-cost mortgages job training and college tuition the implementation of these benefits was not Equitable across racial lines though the 00:04:36 legislation itself didn't explicitly differentiate benefits based on race in practice the distribution of its benefits was largely influenced by social and institutional racism the GI Bill worked in tandem with existing racially discriminating housing and 00:04:48 lending practices such as redlining and restrictive covenants which effectively excluded black veterans from enjoying the same opportunities for homeownership as their white counterparts redlining was a discriminatory practice where 00:05:00 lenders would designate neighborhoods with a high percentage of black people as high risk areas for mortgage lending these areas were often outlined in red on maps used by Banks and other lending institutions hence the term redlining 00:05:13 this led to a systemic denial of Home Loans or Insurance to People based on the racial or ethnic composition of their neighborhoods

“The reality is that tech companies have been using automated tools to moderate content for a really long time and while it’s touted as this sophisticated machine learning, it’s often just a list of words they think are problematic,” said Ángel Díaz, a lecturer at the UCLA School of Law who studies technology and racial discrimination.

Many authors noted that generations tended to fall into clichés, especially when the system was confronted with scenarios less likely to be found in the model's training data. For example, Nelly Garcia noted the difficulty in writing about a lesbian romance — the model kept suggesting that she insert a male character or that she have the female protagonists talk about friendship. Yudhanjaya Wijeratne attempted to deviate from standard fantasy tropes (e.g. heroes as cartographers and builders, not warriors), but Wordcraft insisted on pushing the story toward the well-worn trope of a warrior hero fighting back enemy invaders.

The critical mistake that has been made in the past is that we have equatedthe question of who loses the game with the question of why the game produceslosers in the first place. They are, in fact, distinct and separate questions.

David Brady and colleagues have shown this to be empirically the case across29 rich democracies. The authors focused on four major risks of poverty—loweducation, single motherhood, young adults heading a household, and unem-ployment. They found that although the prevalence of these risks in the UnitedStates is actually below the average in other countries, the rate of poverty inthe United States is the highest. The reason is that “the penalties for risks inthe United States are the highest of the 29 countries. An individual with allfour risks has an extremely heightened probability of being poor in the UnitedStates.”

But the coverage, as our editorial page later noted in 2018, “deplored the inhumanity of the perpetrators without ever really acknowledging the humanity of the victims” or the community terrorized by their brutal deaths. The ire was directed at the “poor, white trash” killers, as Mencken put it; there was no empathy for — or even real interest in — the Black victims.

The next year, the paper wrote glowingly in its news pages of a segregation ordinance — “preventing negroes from moving” into majority-white neighborhoods and vice versa — signed into law in 1910. The measure was drafted, one article claimed, after white residents in the northwest section of the city decried “the encroachment of the negroes into white residential sections, lowering property values and driving white people from the neighborhoods in which, previous to the black invasion, they had liked to live.” As Antero Pietila, a former Sun reporter, noted in his 2010 book, “Not in My Neighborhood: How Bigotry Shaped a Great American City,” that particular ordinance paved the way for residential segregation in America. Nothing else like it was on the books anywhere, and legislation modeled after it soon sprung up in other regions of the country.

Consider, as well, the extent to which the tools of abstraction are themselves tied up in the history of the trans-Atlantic slave trade. As the historian Jennifer L. Morgan notes in “Reckoning With Slavery: Gender, Kinship, and Capitalism in the Early Black Atlantic,” the fathers of modern demography, the 17th-century English writers and mathematicians William Petty and John Graunt, were “thinking through problems of population and mobility at precisely the moment when England had solidified its commitment to the slave trade.”Their questions were ones of statecraft: How could England increase its wealth? How could it handle its surplus population? And what would it do with “excessive populations that did not consume” in the formal market? Petty was concerned with Ireland — Britain’s first colony, of sorts — and the Irish. He thought that if they could be forcibly transferred to England, then they could, in Morgan’s words, become “something valuable because of their ability to augment the population and labor power of the English.”This conceptual breakthrough, Morgan told me in an interview, cannot be disentangled from the slave trade. The English, she said, “are learning to think about people as ‘abstractable.’

If you visit the Web site of the Online Computer Library Center and look at its WorldMap, you can see the numbers of books in public and academic systems around the world. Sixty million Britons have a hundred and sixteen million public-library books at their disposal, while more than 1.1 billion Indians have only thirty-six million. Poverty, in other words, is embodied in lack of print as well as in lack of food. The Internet will do much to redress this imbalance, by providing Western books for non-Western readers. What it will do for non-Western books is less clear.

The unwritten rule of Cybernetics seems to be - Maintain the homeostasis until you break it for the better. #Cybernetics #Ashby

Analog zur Struktur des Zettelkastens baut Luhmanns Systemtheorie nicht auf Axiome und bietet keine Hierarchien von Begriffen oder Thesen. Zentrale Begriffe sind, ebenso wie die einzelnen Zettel, stark untereinander vernetzt und gewinnen erst im Kontext Bedeutung.

And while hunting for caches, he uses some tricks to avoid unwanted attention, like carrying a clipboard. “If you look like you’re working, people don’t tend to pay attention to you.”

People who think that racial differences are all biological might say that all these non-White groups have suffered so much excess death because of that bottom circle, because of greater biological susceptibility.  Recent studies have evaluated this hypothesis and found that it’s not true.  Instead the answer is simpler: Black and Latino/a people in particular are dying of COVID-19 at such staggering rates because they are more likely to be exposed to the virus in infectious settings, particularly workplaces.