Links (links with excerpts below):
What justice means to communities affected by nuclear testing
Do Large Language Models learn world models or just surface statistics?
Need help with students who've turned my class into a dating service
"It turned out, however, that fish, a traditional staple of the Marshallese diet, was not going to be part of mine as I lived and taught elementary school on the island in the early 2000s. The community on Kili, a speck of an island at 200 acres, is inhabited by the Bikini people. In February 1946, the US military governor for the Marshall Islands arrived on Bikini Atoll and asked its residents to temporarily move off their atoll, with its 23 islands and a lagoon full of fish, so the United States could test weapons for “the good of mankind and to end all world wars.” They agreed to leave with the promise they would return.
The Bikini community would never move back to their atoll following the detonation of 23 nuclear devices in the 1940s and 1950s."
"A dominant theme for much of the 19th and 20th century in philosophy and science was that knowledge just is linguistic — that knowing something simply means thinking the right sentence and grasping how it connects to other sentences in a big web of all the true claims we know. The ideal form of language, by this logic, would be a purely formal, logical-mathematical one composed of arbitrary symbols connected by strict rules of inference, but natural language could serve as well if you took the extra effort to clear up ambiguities and imprecisions. As Wittgenstein put it, “The totality of true propositions is the whole of natural science.” This position was so established in the 20th century that psychological findings of cognitive maps and mental images were controversial, with many arguing that, despite appearances, these must be linguistic at base.
This view is still assumed by some overeducated, intellectual types: everything which can be known can be contained in an encyclopedia, so just reading everything might give us a comprehensive knowledge of everything. It also motivated a lot of the early work in Symbolic AI, where symbol manipulation — arbitrary symbols being bound together in different ways according to logical rules — was the default paradigm. For these researchers, an AI’s knowledge consisted of a massive database of true sentences logically connected with one another by hand, and an AI system counted as intelligent if it spit out the right sentence at the right time — that is, if it manipulated symbols in the appropriate way. This notion is what underlies the Turing test: if a machine says everything it’s supposed to say, that means it knows what it’s talking about, since knowing the right sentences and when to deploy them exhausts knowledge."
"Consider the following thought experiment. Imagine you have a friend who enjoys the board game Othello, and often comes to your house to play. The two of you take the competition seriously and are silent during the game except to call out each move as you make it, using standard Othello notation. Now imagine that there is a crow perching outside of an open window, out of view of the Othello board. After many visits from your friend, the crow starts calling out moves of its own—and to your surprise, those moves are almost always legal given the current board.
You naturally wonder how the crow does this. Is it producing legal moves by "haphazardly stitching together” [3] superficial statistics, such as which openings are common or the fact that the names of corner squares will be called out later in the game? Or is it somehow tracking and using the state of play, even though it has never seen the board?"
"Inspired by the success at Blegdam, and the development of the modern ventilator and other technological medical advances, ICUs began to proliferate in hospitals across the world, bringing patients back from the brink of once universally fatal conditions. But in the United States, the story was a bit more complicated. ICU growth in this country has been driven by clinical need and innovation, but also by our unique, often profit-oriented health care financing system.
As the historian Gabriel Winant discussed in his book The Next Shift: The Fall of Industry and the Rise of Health Care in Rust Belt America, both private and public insurance in the United States financed the historic transformation and expansion of the nation’s health care infrastructure in the latter half of the twentieth century. In particular, when the obvious problems with tethering insurance to jobs were partially addressed by the passage of Medicare and Medicaid in 1965, hospitals lobbied for—and ultimately won—a major perk: the ability to bill the federal government for “capital expansion,” allowing them to build seemingly endless new wings containing endless new beds and expensive equipment, practically for free. At the same time, technology and treatment steadily improved, driving more demand for critical care, which was increasingly used for more health conditions and post-surgery care. As Winant puts it, “hospitals could pass through their costs—including capital investments—to the third parties that footed the bills, Blue Cross and the federal government most significantly. The existence of a larger and more advanced hospital plant, in turn, encouraged more use.”"
"It is a head-spinning indication of how much we still have to learn about the world. The really knotty question, though, is what is left for a would-be ethical eater’s lunch? Ethical fruitarianism – eating only the parts of plants that detach harmlessly, causing no damage – might meet the standards of the Federal Ethics Committee on Non-Human Biotechnology (which has ruled that plants have the right to be protected from undue harm)."
😶🌫️ The Carbon Con
"Our analysis of nearly 100 million carbon credits found that only a fraction of them resulted in real emissions reductions. It raises questions for the organisations that many of the world’s biggest companies, and the consumers who buy their products, rely on to set the standard for effective carbon offsetting—in particular the biggest of them, Verra.
“The implications of this analysis are huge,” said Barbara Haya, head of the Carbon Trading Project at the University of California, Berkeley. “Companies are making false claims and then they’re convincing customers that they can fly guilt-free or buy carbon-neutral products when they aren’t in any way carbon-neutral.”"
"I'm a professor at a local university. I'm passionate about teaching, and am proud to teach 100-level science and mathematics courses to young and aspiring students.
Some senior engineering students created a sort of dating service/app, "How I Met My Future Wife" (not the actual name, but close enough). It advertises itself as a way for smart young guys to meet "potential marriage material", by helping them social with "young, cultured, educated women". It works by aggregating diversity data my university publishes. This data is intended to help make a case for having more women and minorities in STEM courses so that post-university, we have more diverse representation in the worlds of science, business, and engineering. These senior engineering students used it to create a database of courses that are statistically likely to have a large proportion of young women from certain cultural backgrounds."
"Example: the psychological phenomenon known as the overjustification effect means that if people are doing something for an intrinsic reward and you start giving them extrinsic rewards for it, they lose their intrinsic motivation. Imagine if you were reading a book and were paid for every page you read: after a while, you'd be reading pages because you wanted paying, not because of the content.
It's the same with games. If people are playing your game for fun and you start giving them money for playing, they won't find the game so much fun. If fun is what they seek, they'll play another game.
This fact was completely ignored when I brought it up. I may as well have been telling people how much my great aunt liked cats for all the impact it had."
"“The reason that the amyloid hypothesis started out was pretty strong,” said Becky Carlyle, a neurobiologist who studies neurodegeneration at the University of Oxford. “They found out that lots of people with dementia had these plaques. We were able to actually look at what proteins were in them; there was an absolute ton of amyloid. And then that combined with the fact that we have familial early onset Alzheimer’s disease, which involves mutations in the enzymes that produce amyloid peptides, meant that that was a pretty good starting point, I think, for the theory and certainly merited a lot of attention.”"
"Originally planned for a late 2021 issue, we are glad that we are finally able to bring the accompanying interview to the light of the day. The ever gracious and supportive gentleman, Knuth read through our set of questions and dashed off a warm reply with characteristic panache. All of his replies to all the questions we posed to him are exactly 280 characters long, demonstrating yet again why the world celebrates his uniquely witty genius. The genial professor, via an appreciative note also apologized for the year long delay; and more than made it up for our readers with his intellect, and enthusiasm."