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Fareed Zakaria on the Age of Revolutions, the Power of Ideas, and the Rewards of Intell... - 0 views

conversationswithtyler.com/...fareed-zakaria ideas intellectual curiosity conversation cowen china india devlopment liberal democracy west revolution
shared by Javier E on 04 Aug 24 - No Cached
  • ZAKARIA: Yes. I think I’ve always been intellectually very curious. I don’t think I’m the smartest person in the world, but I am very intellectually curious. I get fascinated by ideas and why things are some way. Even when I was very young, I remember I would read much more broadly than my peers.
  • I think I looked this up once, but Henry Kissinger’s memoirs came out when I was 14, I think. I remember reading them because I remember my mom — at that point, she was working at the Times of India. They excerpted it. I remember telling her that they had chosen some of the wrong excerpts, that there were other parts that would have been better. I must have read enough of it to have had an opinion.
  • The Bengali intelligentsia was the great intelligentsia of India, probably the most literate, the most learned. I think it’s because they’re very clever. One of the things I’ve always noticed is that people who are very clever political elites tend to think that they should run the economy because they can do it better than the market.
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  • a lot of people who came out of third-world countries felt, “We are never going to catch up with the West if we just wait for the market to work its way over hundreds of years.” They looked at, in the ’30s, the Soviet Union and thought, “This is a way to accelerate modernization, industrialization.” They all were much more comfortable with the idea of something that sped up the historical process of modernization.
  • Milton Friedman used to say that there are two groups of people who don’t like the free market. Academics, intellectuals because they think they can do it better than the market, and businessmen because they don’t like competition. What they really want — this is a variation of the Peter Thiel argument — what they all really want is to be monopolists. That former part is, I think, what explains the Bengali intellectuals.
  • I think that the reality is, the market is much more powerful than they are in these areas. To give you one simple example, they decided, “Okay, we need to be making high-end chips.” Who do they bet on? They bet on Intel, a company that has failed miserably to compete with TSMC, the great Taiwanese chip manufacturer. Intel is now getting multi-billion-dollar grants from the United States government, from the European Union, because it fills all the categories that you’re looking for: big company, stable and well-run, in some sense, can guarantee a lot of jobs.
  • But of course, the reality is that chip making is so complicated
  • Who knew that, actually, it’s Nvidia, whose chips turned out to be designed for gaming, turned out to be ideal for artificial intelligence? That’s a perfect example of how the Hayekian market signals that come bottom-up are much more powerful than a political elite who tries to tell you what it is.
  • COWEN: What did you learn from the Anglican Book of Common Prayer?
  • One was a reverence for tradition, and in particular, I loved the hymnal. I think Britain’s great contribution to music is religious music. It doesn’t have anything to compete with the Germans and the Italians in opera and things like that. Religious music, I think the Brits and the English have done particularly well.
  • The second thing I would say is an admiration for Christianity for its extraordinary emphasis on being nice to people who have not been lucky in life. I would say that’s, to me, the central message of Christianity that I take, certainly from the Sermon on the Mount, and it’s imbued through the Book of Common Prayer: to be nice to the people who have been less fortunate than you. Be nice to poor people. Recognize that in God’s kingdom, the first shall be last and the last shall be first.
  • There is an enormous emphasis on the idea that those things that make you powerful in this world are not the things that really matter, that your dignity as a human being doesn’t come from that. I think that’s a very powerful idea. It’s a very revolutionary idea
  • Tom Holland has a very good book about this. He’s a wonderful historian in Britain. I think it’s called Dominion.
  • He points out what a revolutionary idea this was. It completely upended the Roman values, which were very much, the first shall be first. The powerful and the rich are the ones to be valued. He points out, here is this Jewish preacher coming out of the Middle East saying, “No, the first shall be last, the last shall be first in the kingdom of heaven.”
  • COWEN: I went to Amritsar the year before, and it was one of the most magical feelings I’ve ever had in any place. I’m still not sure what exactly I can trace it to — I am not a Sikh, of course. But what, for you, accounts for the strong, powerful, wondrous feeling one gets from that place?
  • I think there’s something about it architecturally, which is that there is a serenity about it. Sometimes you can find Hindu temples that are very elaborate. Sikhism is a kind of offshoot of Hinduism. The Hindu temples can be very elaborate, but very elaborate and ornate. This somehow has a simplicity to it. When you add to that the water — I’ve always thought that water adds an enormously calming effect
  • Hindi and Urdu are two Indian languages, very related. They both have roughly the same grammatical structure, but then Hindi derives its vocabulary entirely from Sanskrit, or almost entirely from Sanskrit, and Urdu derives its vocabulary almost entirely from Persian. Urdu is a language of Indian Muslims and is the official language for Pakistan. It’s a beautiful language, very lyrical, very much influenced by that Persian literary sensibility.
  • If you’re speaking one of the languages, there’s a way to alternate between both, which a lot of Indian politicians used to do as a way of signaling a broad embrace of both the Hindu and the Muslim communities. Nehru, India’s first prime minister, used to often do that. He would say, “I am delighted to be coming here to your home.” He’d repeat the word home, first in Urdu, then in Hindi, so that in effect, both constituencies were covered.
  • Modi, by contrast, India’s current prime minister, is a great Hindu nationalist. He takes pains almost never to use an Urdu word when he speaks. He speaks in a kind of highly Sanskritized Hindi that most Indians actually find hard to understand because the everyday language, Bollywood Hindi, is a mixture of Hindi words and Urdu words
  • I think the partition of India was a complete travesty. It was premised on this notion of religious nationalism. It was horrendously executed. The person who drew the lines, a man named Radcliffe, had never been to India. He’d never been east of the Suez and was given this task, and he did it in a month or two, probably caused a million-and-a-half to two million lives lost, maybe 10 million people displaced. It broke that wonderfully diverse, syncretic aspect of India.
  • If you look at cities like Delhi and Lahore, what was beautiful about them is that they mix together all the influences of India: Hindu, Muslim, Punjabi, Sindhi. Now what you have is much more bifurcated. If you go to Lahore, Lahore is a Muslim city in Pakistan, and it has a Punjabi influence. Delhi has become, essentially, much more Indian and Hindu and has lost that Muslim influence. To me, as somebody who really loves cosmopolitanism and diversity, it’s sad to see that. It’s almost like you’ve lost something that really made these places wonderfully rich.
  • I feel the same way when you read about the history of Europe. You think of a place like Vienna, which, in its most dazzling moment, was dazzling precisely because it was this polyglot population of people coming from all over the Habsburg Empire. A large segment of it was Jewish, and it had, as a result — think about Freud and Klimt and the music that came out of there, and the architecture that came out at the turn of the 19th century. And it’s all gone. It’s like, at this point, a somewhat beautiful but slightly dull Austrian city.
  • I remember once being asked when I was a graduate student at Harvard — Tony Lake was then national security adviser, and his office called and said — I’d written something in the New York Times, I think — “Mr. Lake would like you to come to the White House to brief him.”
  • I think, in a sense, Islam fit in within that tapestry very easily, and it’s been around for a while. When people talk about cleansing India, Hindu nationals talk about cleansing India of foreign influences. Islam has been in India since the 11th century, so it’s been around for a long time
  • I was amazed that America — it wasn’t America; it was where I was at Yale and Harvard and all that — that nobody cared where I came from. Nobody cared.
  • the syncretic nature of India, that India has always been diverse. Hinduism is very tolerant. It’s a kind of unusual religion in that you can believe in one god and be Hindu. You can believe in 300. You can be vegetarian and believe that’s a religious dictate. You can be nonvegetarian and believe that that’s completely compatible with your religion. It’s always embraced almost every variant and variation.
  • I walked in and there were five people around the table: Tony Lake; Deputy National Security Advisor Sandy Berger; George Stephanopoulos, who was then director of communications at the White House; Joe Nye, who was a senior professor at Harvard; one other person; and myself. And I kept thinking to myself, “Are they going to realize at some point that I’m not an American citizen? They’re asking me for my advice on what America should do, and I am on a student visa.” And of course, nobody ever did, which is one of the great glories of America.
  • My thesis topic was, I tried to answer the question, when countries rise in great power, when they rise economically, they become great powers because they quickly translate that economic power into diplomatic and military power. What explains the principal exception in modern history, which is the United States?
  • My simple answer was that the United States was a very unusual creature in the modern world. It was a very strong nation with a very weak state. The federal government in the United States did not have the capacity to extract the resources from the society at large because you didn’t have income taxes in those days.
  • COWEN: What put you off academia? And this was for the better, in my view.
  • ZAKARIA: I think two things. One, I could see that political science was moving away from the political science that I loved, which was a broad discipline rooted in the social sciences but also rooted in the humanities, which was rigorous, structural, historical comparisons. Looking at different countries, trying to understand why there were differences.
  • It was moving much more toward a huge emphasis on things like rational choice, on game theory There was an economist envy. Just as economists have math envy, political scientists have economist envy. It was moving in that direction
  • COWEN: After 9/11 in 2001, you wrote a famous essay for Newsweek, “Why Do They Hate Us?” You talked about the rulers, failed ideas, religion. If you were to revise or rethink that piece today, how would you change it? Because we have 23 more years of data, right?
  • He had a routine, which is, he’d get up about 6:00 a.m. He’d go down to the basement of his townhouse, and at 6:30, he would start writing or working on whatever his next big research project was. He’d do that, uninterrupted, for three hours at least, sometimes four. Then, at about 9:30, 10:00, he would take the subway to Harvard.
  • His point was, you got to start the day by doing the important work of academia, which is producing knowledge. All the rest of it — teaching, committee meetings, all that — you can do later. He was so disciplined about that, that every five years or so, he put out another major piece of work, another major book
  • I looked at that, and I said to myself, I do not have the self-discipline to perform at that level. I need to go into something that has deadlines,
  • It’s all within you, and you have to be able to generate ideas from that lonely space. I’ve always found that hard. For me, writing books is the hardest thing I do. I feel like I have to do it because I feel as though everything else is trivia — the television, column, everything else.
  • The second piece of it was actually very much related to Huntington. Sam Huntington was quite an extraordinary character, probably the most important social scientist in the second half of the 20th century. Huge contributions to several fields of political science. He lived next to me
  • ZAKARIA: Yes. Not very much, honestly. The central point I was making in that essay was that if you look at the Arab world, it is the principal outlier in the modern era, where it has undergone almost no political modernization.
  • The Arab world had remained absolutely static. My argument was that it was largely because of the curse of oil and oil wealth, which had impeded modernization. But along with that, because of that failed modernization, they had developed this reactionary ideology of Islam, which said the answer is to go further back, not to go forward. “Islam is the solution,” was the cry of the Islamic fundamentalists in the 1970s.
  • COWEN: I’m struck that this year, both you and Ruchir Sharma have books coming out — again, Fareed’s book is Age of Revolutions: Progress and Backlash from 1600 to the Present — that I would describe broadly as classically liberal. Do you think classical liberalism is making a comeback
  • the reason these books are coming out — and certainly, mine, as you know, is centrally occupied with the problem that there’s a great danger that we are going to lose this enormous, probably the most important thing that’s happened in the last 500, 600 years in human history, this movement that has allowed for the creation of modern liberal democratic societies with somewhat market economies.
  • If you look at the graph of income, of GDP, per capita GDP, it’s like a straight line. There’s no improvement until you get to about, roughly speaking, the 17th, 18th century in Europe, and then you see a sharp uptick. You see this extraordinary rise, and that coincides with the rise of science and intellectual curiosity and the scientific method, and the industrial revolution after that. All that was a product of this great burst of liberal Enlightenment thinking in the West.
  • If you think about what we’ve gone through in the last 30 years — and this is really the central argument in my book — massive expansion of globalization, massive expansion of information technology so that it has completely upended the old economy. All of this happening, and people are overwhelmed, and they search in that age of anxiety. They search for a solution, and the easy solutions are the ones offered by the populists.
  • They’re deeply anti-liberal, illiberal. So, I worry that, actually, if we don’t cherish what we have, we’ll lose what has been one of the great, great periods of progress in human history.
  • COWEN: Why does your book cover the 17th-century Dutch Golden Age? ZAKARIA: The Dutch are the first modern country. If you think about politics before that — certainly with the exception of ancient Greece and Rome — in modern history, the Dutch invent modern politics and economics. They invent modern politics in the sense that it’s the first time politics is not about courts and kings. It is about a merchant republic with powerful factions and interest groups and political parties, or the precursor to political parties.
  • It’s the beginning of modern economics because it’s economics based not simply on land and agriculture, but on the famous thing that John Locke talked about, which is mixing human beings’ labor with the land. The Dutch literally do this when they reclaim land from the sea and find ways to manage it, and then invent tall ships, which is, in some ways, one of the first great technological revolutions that has a direct economic impact.
  • You put all that together, and the Dutch — they become the richest country in the world, and they become the leading technological power in the world. It was very important to me to start the story — because they are really the beginnings of modern liberalism
  • COWEN: Circa 1800, how large were the Chinese and Indian economies?
  • Circa 1800, the Chinese and Indian economies are the two largest economies in the world, and people have taken this to mean, oh, the West had a temporary spurt because of colonies and cheap energy, and that the Chinese and Indians are just coming back to where they were.
  • First of all, the statistic is misleading because in those days, GDP was simply measured by using population. All society was agricultural. The more people you had, the larger your GDP. It was meaningless because the state could not extract that GDP in any meaningful way, and it’s meaningless because it doesn’t measure progress. It doesn’t measure per capita GDP growth, which is the most important thing to look at.
  • If you look at per capita GDP growth from 1350 to 1950, for 600 years, India and China have basically no movement. It’s about $600 in 1350 and $600 in 1950. The West, by comparison, moves up 600 percent in that period. It’s roughly $500 per capita GDP to roughly $5,000 per capita GDP.
  • You can also look at all kinds of other measures. You can look at diet. There are economic historians who’ve done this very well, and people in England were eating four to five times as much grain and protein as people in China and India. You can look at the extraordinary flourishing of science and engineering. You can look at the rise of the great universities. It’s all happening in the West.
  • The reason this is important is, people need to understand the rise of the West has been a very profound, deep-rooted historical phenomenon that began sometime in the 15th century. The fact that we’re moving out of that phase is a big, big deal. This is not a momentary blip. This is a huge train. The West define modernity. Even when countries try to be modern, they are in some way becoming Western because there is no path we know of to modernity without that.
  • One other way of just thinking about how silly that statistic is: in pure GDP terms, China had a larger GDP than Britain in 1900. Now, look at Britain in 1900: the most advanced industrial society in the world, ruling one-quarter of the world, largest navy in the world, was able to humiliate China by using a small fraction of its military power during the opium era. That’s what tells you that number is really meaningless. The West has been significantly more advanced than the rest of the world since the 16th century at least.
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JD Vance and the Galaxy-Brained Style in American Politics - 0 views

www.thebulwark.com/...rained-style-american-politics vance right-wing cultural culture politics history gop
shared by Javier E on 25 Jul 24 - No Cached
  • “Cultural pessimism has a strong appeal in America today,” the historian Fritz Stern wrote. “As political conditions appear stable at home or irremediable abroad, American intellectuals have become concerned with the cultural problems of our society, and have substituted sociological or cultural analyses for political criticism.”
  • I bring up Stern’s book because it nails the character of “revolutionary” conservatism—just the sort of politics Vance represents. The junior senator from Ohio believes “culture war is class warfare,”
  • has made it possible for him to claim to be a tribune of the working class in spite of a 0 percent score from the AFL-CIO on “voting with working people.”
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  • In general, it’s the point of view of someone who takes Thomas Cole’s The Course of Empire painting cycle to contain a subtle and profound truth about society, one best expressed in a familiar maxim: Strong men make good times; good times make weak men; weak men make . . . (I need to yawn and will let you fill in the rest).1
  • for Vanity Fair, James Pogue did a good job summarizing the tech billionaire Peter Thiel influence nexus and the Thiel-funded coterie that Vance ran with online in a long feature two years ago. Pogue notes: 
  • Vance and this New Right cohort, who are mostly so, so highly educated and well-read that their big problem often seems to be that they’re just too nerdy to be an effective force in mass politics, are not anti-intellectual. Vance is an intellectual himself, even if he’s not currently playing one on TV.
  • the man doesn’t just have cracked beliefs but cracked instincts. Almost endearingly, he and his pals seem to think that workaday politics is an opportune context for doing a bit of grand theory,
  • Stern, again: “They condemned or prophesied, rather than exposited or argued, and all their writings showed that they despised the discourse of intellectuals, depreciated reason, and exalted intuition.” As Stern makes clear, this is the style of thinking that did so much to pave the way for the “revolutionary conservatism” that emerged in the Weimar era.
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It's not just vibes. Americans' perception of the economy has completely changed. - ABC... - 0 views

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  • Applying the same pre-pandemic model to consumer sentiment during and after the pandemic, however, simply does not work. The indicators that correlated with people's feelings about the economy before 2020 no longer seem to matter in the same way
  • As with so many areas of American life, the pandemic has changed virtually everything about how people think about the economy and the issues that concern them
  • Prior to the pandemic, our model shows consumers felt better about the economy when the personal savings rate, a measure of how much money households are able to save rather than spend each month, was higher. This makes sense: People feel better when they have money in the bank and are able to save for important purchases like cars and houses.
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  • Before the pandemic, a number of variables were statistically significant indicators for consumer sentiment in our model; in particular, the most salient variables appear to be vehicle sales, gas prices, median household income, the federal funds effective rate, personal savings and household expenditures (excluding food and energy).
  • surprisingly, our pre-pandemic model didn't find a notable relationship between housing prices and consumer sentiment
  • All this taken together meant Americans were flush with cash but had nowhere to spend it. So despite the fact that the savings rate went way up, consumers still weren't feeling positively about the economy — contrary to the relationship between these two variables we saw in the decades before the pandemic.
  • Fast forward to 2024, and the personal savings rate has dropped to one of its lowest levels ever (the only time the savings rate was lower was in the years surrounding the Great Recession)
  • during and after the pandemic, Americans saw some of the highest rates of inflation the country has had in decades, and in a very short period of time. These sudden spikes naturally shocked many people who had been blissfully enjoying slow, steady price growth their entire adult lives. And it has taken a while for that shock to wear off, even as inflation has cre
  • the numbers align with our intuitive sense of how consumers process suddenly having their grocery store bill jump, as well as the findings from our model. In simple terms: Even if inflation is getting better, Americans aren't done being ticked off that it was bad to begin with.
  • During the pandemic, the personal savings rate soared. In April 2020, the metric was nearly double its previous high, recorded in May 1975.
  • However, in our post-pandemic data, when we examined how correlated consumer sentiment was with each indicator we considered, consumer sentiment and median housing prices had the strongest correlation of all****** (a negative one, meaning higher prices were associated with lower consumer sentiment)
  • "Right before the pandemic, the typical average transaction price was around $38,000 for a new car. By 2023, it was $48,000," Schirmer said. This could all be contributing to the break in the relationship between car sales and sentiment, he noted. Basically, people might be buying cars, but they aren't necessarily happy about it.
  • That's true even if a family has been able to save enough for a down payment, already a difficult task when rents remain high as well. Fewer people are able to cover their current housing costs while saving enough to make a down payment.
  • Low-income households are still the most likely to be burdened with high rents, but they're not the only ones affected anymore. High rents have also begun to affect those at middle-income levels as well.
  • In short, there was already a housing affordability crisis before the pandemic. Now it's worse, locking a wider array of people, at higher and higher income levels, out of the home-buying market
  • People who are renting but want to buy are stuck. People who live in starter homes and want to move to bigger homes are stuck. The conditions have frustrated a fundamental element of the American dream
  • In our pre-pandemic model, total vehicle sales had a strong positive relationship with consumer sentiment: If people were buying cars, you could pretty reasonably bet that they felt good about the economy. This feels intuitive — who buys a car if they think the economy
  • Cox Automotive also tracks vehicle affordability by calculating the estimated number of weeks' worth of median income needed to purchase the average new vehicle, and while that number has improved over the last two years, it remains high compared to pre-pandemic levels. In April, the most recent month with data, it took 37.7 weeks of median income to purchase a car, compared with fewer than 35 weeks at the end of 2019.
  • during the pandemic, low interest rates, high savings rates and changes in working patterns — namely, many workers' newfound ability to work from home — helped overheat the homebuying market, and buyers ran headlong into an enduring supply shortage. There simply weren't enough houses to buy, which drove up the costs of the ones that were for sale.
  • Inspired by our model of economic indicators and sentiment from 1987 to 2019, we tried to train a similar linear regression model on the same data from 2021 to 2024 to more directly compare how things changed after the pandemic. While we were able to get a pretty good fit for this post-pandemic model,******* something interesting happened: Not a single variable showed up as a statistically significant predictor of consumer sentiment.
  • This suggests there's something much more complicated going on behind the scenes: Interactions between these variables are probably driving the prediction, and there's too much noise in this small post-pandemic data set for the model to disentangle i
  • Changes in the kinds of purchases we've discussed — homes, cars and everyday items like groceries — have fundamentally shifted the way Americans view how affordable their lives are and how they measure their quality of life.
  • Even though some indicators may be improving, Americans are simply weighing the factors differently than they used to, and that gives folks more than enough reason to have the economic blues.
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AI scientist Ray Kurzweil: 'We are going to expand intelligence a millionfold by 2045' ... - 0 views

www.theguardian.com/...e-ai-the-singularity-is-nearer ai kurzweil predictions evaluation 2024
shared by Javier E on 29 Jun 24 - No Cached
  • American computer scientist and techno-optimist Ray Kurzweil is a long-serving authority on artificial intelligence (AI). His bestselling 2005 book, The Singularity Is Near, sparked imaginations with sci-fi like predictions that computers would reach human-level intelligence by 2029 and that we would merge with computers and become superhuman around 2045, which he called “the Singularity”. Now, nearly 20 years on, Kurzweil, 76, has a sequel, The Singularity Is Nearer
  • no longer seem so wacky.
  • Your 2029 and 2045 projections haven’t changed…I have stayed consistent. So 2029, both for human-level intelligence and for artificial general intelligence (AGI) – which is a little bit different. Human-level intelligence generally means AI that has reached the ability of the most skilled humans in a particular domain and by 2029 that will be achieved in most respects. (There may be a few years of transition beyond 2029 where AI has not surpassed the top humans in a few key skills like writing Oscar-winning screenplays or generating deep new philosophical insights, though it will.) AGI means AI that can do everything that any human can do, but to a superior level. AGI sounds more difficult, but it’s coming at the same time.
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  • Why write this book? The Singularity Is Near talked about the future, but 20 years ago, when people didn’t know what AI was. It was clear to me what would happen, but it wasn’t clear to everybody. Now AI is dominating the conversation. It is time to take a look again both at the progress we’ve made – large language models (LLMs) are quite delightful to use – and the coming breakthroughs.
  • It is hard to imagine what this would be like, but it doesn’t sound very appealing… Think of it like having your phone, but in your brain. If you ask a question your brain will be able to go out to the cloud for an answer similar to the way you do on your phone now – only it will be instant, there won’t be any input or output issues, and you won’t realise it has been done (the answer will just appear). People do say “I don’t want that”: they thought they didn’t want phones either!
  • The most important driver is the exponential growth in the amount of computing power for the price in constant dollars. We are doubling price-performance every 15 months. LLMs just began to work two years ago because of the increase in computation.
  • What’s missing currently to bring AI to where you are predicting it will be in 2029? One is more computing power – and that’s coming. That will enable improvements in contextual memory, common sense reasoning and social interaction, which are all areas where deficiencies remain
  • LLM hallucinations [where they create nonsensical or inaccurate outputs] will become much less of a problem, certainly by 2029 – they already happen much less than they did two years ago. The issue occurs because they don’t have the answer, and they don’t know that. They look for the best thing, which might be wrong or not appropriate. As AI gets smarter, it will be able to understand its own knowledge more precisely and accurately report to humans when it doesn’t know.
  • What exactly is the Singularity? Today, we have one brain size which we can’t go beyond to get smarter. But the cloud is getting smarter and it is growing really without bounds. The Singularity, which is a metaphor borrowed from physics, will occur when we merge our brain with the cloud. We’re going to be a combination of our natural intelligence and our cybernetic intelligence and it’s all going to be rolled into one. Making it possible will be brain-computer interfaces which ultimately will be nanobots – robots the size of molecules – that will go noninvasively into our brains through the capillaries. We are going to expand intelligence a millionfold by 2045 and it is going to deepen our awareness and consciousness.
  • Why should we believe your dates? I’m really the only person that predicted the tremendous AI interest that we’re seeing today. In 1999 people thought that would take a century or more. I said 30 years and look what we have.
  • I have a chapter on perils. I’ve been involved with trying to find the best way to move forward and I helped to develop the Asilomar AI Principles [a 2017 non-legally binding set of guidelines for responsible AI development]
  • All the major companies are putting more effort into making sure their systems are safe and align with human values than they are into creating new advances, which is positive.
  • Not everyone is likely to be able to afford the technology of the future you envisage. Does technological inequality worry you? Being wealthy allows you to afford these technologies at an early point, but also one where they don’t work very well. When [mobile] phones were new they were very expensive and also did a terrible job. They had access to very little information and didn’t talk to the cloud. Now they are very affordable and extremely useful. About three quarters of people in the world have one. So it’s going to be the same thing here: this issue goes away over time.
  • The book looks in detail at AI’s job-killing potential. Should we be worried? Yes, and no. Certain types of jobs will be automated and people will be affected. But new capabilities also create new jobs. A job like “social media influencer” didn’t make sense, even 10 years ago. Today we have more jobs than we’ve ever had and US average personal income per hours worked is 10 times what it was 100 years ago adjusted to today’s dollars. Universal basic income will start in the 2030s, which will help cushion the harms of job disruptions. It won’t be adequate at that point but over time it will become so.
  • Everything is progressing exponentially: not only computing power but our understanding of biology and our ability to engineer at far smaller scales. In the early 2030s we can expect to reach longevity escape velocity where every year of life we lose through ageing we get back from scientific progress. And as we move past that we’ll actually get back more years.
  • What is your own plan for immortality? My first plan is to stay alive, therefore reaching longevity escape velocity. I take about 80 pills a day to help keep me healthy. Cryogenic freezing is the fallback. I’m also intending to create a replicant of myself [an afterlife AI avatar], which is an option I think we’ll all have in the late 2020s
  • I did something like that with my father, collecting everything that he had written in his life, and it was a little bit like talking to him. [My replicant] will be able to draw on more material and so represent my personality more faithfully.
  • What should we be doing now to best prepare for the future? It is not going to be us versus AI: AI is going inside ourselves. It will allow us to create new things that weren’t feasible before. It’ll be a pretty fantastic future.
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Opinion | The Pandemic Probably Started in a Lab. These 5 Key Points Explain Why. - The... - 0 views

www.nytimes.com/...covid-lab-leak.html pandemic origin covid china lab history investigation
shared by Javier E on 04 Jun 24 - No Cached
  • a growing volume of evidence — gleaned from public records released under the Freedom of Information Act, digital sleuthing through online databases, scientific papers analyzing the virus and its spread, and leaks from within the U.S. government — suggests that the pandemic most likely occurred because a virus escaped from a research lab in Wuhan, China.
  • If so, it would be the most costly accident in the history of science.
  • The SARS-like virus that caused the pandemic emerged in Wuhan, the city where the world’s foremost research lab for SARS-like viruses is located.
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  • Dr. Shi’s group was fascinated by how coronaviruses jump from species to species. To find viruses, they took samples from bats and other animals, as well as from sick people living near animals carrying these viruses or associated with the wildlife trade. Much of this work was conducted in partnership with the EcoHealth Alliance, a U.S.-based scientific organization that, since 2002, has been awarded over $80 million in federal funding to research the risks of emerging infectious diseases.
  • Their research showed that the viruses most similar to SARS‑CoV‑2, the virus that caused the pandemic, circulate in bats that live roughly 1,000 miles away from Wuhan. Scientists from Dr. Shi’s team traveled repeatedly to Yunnan province to collect these viruses and had expanded their search to Southeast Asia. Bats in other parts of China have not been found to carry viruses that are as closely related to SARS-CoV-2.
  • When the Covid-19 outbreak was detected, Dr. Shi initially wondered if the novel coronavirus had come from her laboratory, saying she had never expected such an outbreak to occur in Wuhan.
  • The SARS‑CoV‑2 virus is exceptionally contagious and can jump from species to species like wildfire. Yet it left no known trace of infection at its source or anywhere along what would have been a thousand-mile journey before emerging in Wuhan.
  • The year before the outbreak, the Wuhan institute, working with U.S. partners, had proposed creating viruses with SARS‑CoV‑2’s defining feature
  • The laboratory pursued risky research that resulted in viruses becoming more infectious: Coronaviruses were grown from samples from infected animals and genetically reconstructed and recombined to create new viruses unknown in nature. These new viruses were passed through cells from bats, pigs, primates and humans and were used to infect civets and humanized mice (mice modified with human genes). In essence, this process forced these viruses to adapt to new host species, and the viruses with mutations that allowed them to thrive emerged as victors.
  • Worse still, as the pandemic raged, their American collaborators failed to publicly reveal the existence of the Defuse proposal. The president of EcoHealth, Peter Daszak, recently admitted to Congress that he doesn’t know about virus samples collected by the Wuhan institute after 2015 and never asked the lab’s scientists if they had started the work described in Defuse.
  • By 2019, Dr. Shi’s group had published a database describing more than 22,000 collected wildlife samples. But external access was shut off in the fall of 2019, and the database was not shared with American collaborators even after the pandemic started, when such a rich virus collection would have been most useful in tracking the origin of SARS‑CoV‑2. It remains unclear whether the Wuhan institute possessed a precursor of the pandemic virus.
  • In 2021, The Intercept published a leaked 2018 grant proposal for a research project named Defuse, which had been written as a collaboration between EcoHealth, the Wuhan institute and Ralph Baric at the University of North Carolina, who had been on the cutting edge of coronavirus research for years. The proposal described plans to create viruses strikingly similar to SARS‑CoV‑2.
  • Coronaviruses bear their name because their surface is studded with protein spikes, like a spiky crown, which they use to enter animal cells. The Defuse project proposed to search for and create SARS-like viruses carrying spikes with a unique feature: a furin cleavage site — the same feature that enhances SARS‑CoV‑2’s infectiousness in humans, making it capable of causing a pandemic. Defuse was never funded by the United States.
  • owever, in his testimony on Monday, Dr. Fauci explained that the Wuhan institute would not need to rely on U.S. funding to pursue research independently.
  • While it’s possible that the furin cleavage site could have evolved naturally (as seen in some distantly related coronaviruses), out of the hundreds of SARS-like viruses cataloged by scientists, SARS‑CoV‑2 is the only one known to possess a furin cleavage site in its spike. And the genetic data suggest that the virus had only recently gained the furin cleavage site before it started the pandemic.
  • Ultimately, a never-before-seen SARS-like virus with a newly introduced furin cleavage site, matching the description in the Wuhan institute’s Defuse proposal, caused an outbreak in Wuhan less than two years after the proposal was drafted.
  • When the Wuhan scientists published their seminal paper about Covid-19 as the pandemic roared to life in 2020, they did not mention the virus’s furin cleavage site — a feature they should have been on the lookout for, according to their own grant proposal, and a feature quickly recognized by other scientists.
  • At the Wuhan Institute of Virology, a team of scientists had been hunting for SARS-like viruses for over a decade, led by Shi Zhengl
  • In May, citing failures in EcoHealth’s monitoring of risky experiments conducted at the Wuhan lab, the Biden administration suspended all federal funding for the organization and Dr. Daszak, and initiated proceedings to bar them from receiving future grants. In his testimony on Monday, Dr. Fauci said that he supported the decision to suspend and bar EcoHealth.
  • Separately, Dr. Baric described the competitive dynamic between his research group and the institute when he told Congress that the Wuhan scientists would probably not have shared their most interesting newly discovered viruses with him. Documents and email correspondence between the institute and Dr. Baric are still being withheld from the public while their release is fiercely contested in litigation.
  • In the end, American partners very likely knew of only a fraction of the research done in Wuhan. According to U.S. intelligence sources, some of the institute’s virus research was classified or conducted with or on behalf of the Chinese military.
  • In the congressional hearing on Monday, Dr. Fauci repeatedly acknowledged the lack of visibility into experiments conducted at the Wuhan institute, saying, “None of us can know everything that’s going on in China, or in Wuhan, or what have you. And that’s the reason why — I say today, and I’ve said at the T.I.,” referring to his transcribed interview with the subcommittee, “I keep an open mind as to what the origin is.”
  • The Wuhan lab pursued this type of work under low biosafety conditions that could not have contained an airborne virus as infectious as SARS‑CoV‑2.
  • Labs working with live viruses generally operate at one of four biosafety levels (known in ascending order of stringency as BSL-1, 2, 3 and 4) that describe the work practices that are considered sufficiently safe depending on the characteristics of each pathogen. The Wuhan institute’s scientists worked with SARS-like viruses under inappropriately low biosafety conditions.
  • ​​Biosafety levels are not internationally standardized, and some countries use more permissive protocols than others.
  • In one experiment, Dr. Shi’s group genetically engineered an unexpectedly deadly SARS-like virus (not closely related to SARS‑CoV‑2) that exhibited a 10,000-fold increase in the quantity of virus in the lungs and brains of humanized mice. Wuhan institute scientists handled these live viruses at low biosafety levels, including BSL-2.
  • Even the much more stringent containment at BSL-3 cannot fully prevent SARS‑CoV‑2 from escaping. Two years into the pandemic, the virus infected a scientist in a BSL-3 laboratory in Taiwan, which was, at the time, a zero-Covid country. The scientist had been vaccinated and was tested only after losing the sense of smell. By then, more than 100 close contacts had been exposed. Human error is a source of exposure even at the highest biosafety levels, and the risks are much greater for scientists working with infectious pathogens at low biosafety.
  • An early draft of the Defuse proposal stated that the Wuhan lab would do their virus work at BSL-2 to make it “highly cost-effective.” Dr. Baric added a note to the draft highlighting the importance of using BSL-3 to contain SARS-like viruses that could infect human cells, writing that “U.S. researchers will likely freak out.”
  • Years later, after SARS‑CoV‑2 had killed millions, Dr. Baric wrote to Dr. Daszak: “I have no doubt that they followed state determined rules and did the work under BSL-2. Yes China has the right to set their own policy. You believe this was appropriate containment if you want but don’t expect me to believe it. Moreover, don’t insult my intelligence by trying to feed me this load of BS.”
  • SARS‑CoV‑2 is a stealthy virus that transmits effectively through the air, causes a range of symptoms similar to those of other common respiratory diseases and can be spread by infected people before symptoms even appear. If the virus had escaped from a BSL-2 laboratory in 2019, the leak most likely would have gone undetected until too late.
  • One alarming detail — leaked to The Wall Street Journal and confirmed by current and former U.S. government officials — is that scientists on Dr. Shi’s team fell ill with Covid-like symptoms in the fall of 2019. One of the scientists had been named in the Defuse proposal as the person in charge of virus discovery work. The scientists denied having been sick.
  • The hypothesis that Covid-19 came from an animal at the Huanan Seafood Market in Wuhan is not supported by strong evidence.
  • In December 2019, Chinese investigators assumed the outbreak had started at a centrally located market frequented by thousands of visitors daily. This bias in their search for early cases meant that cases unlinked to or located far away from the market would very likely have been missed
  • To make things worse, the Chinese authorities blocked the reporting of early cases not linked to the market and, claiming biosafety precautions, ordered the destruction of patient samples on January 3, 2020, making it nearly impossible to see the complete picture of the earliest Covid-19 cases. Information about dozens of early cases from November and December 2019 remains inaccessible.
  • A pair of papers published in Science in 2022 made the best case for SARS‑CoV‑2 having emerged naturally from human-animal contact at the Wuhan market by focusing on a map of the early cases and asserting that the virus had jumped from animals into humans twice at the market in 2019
  • More recently, the two papers have been countered by other virologists and scientists who convincingly demonstrate that the available market evidence does not distinguish between a human superspreader event and a natural spillover at the market.
  • Furthermore, the existing genetic and early case data show that all known Covid-19 cases probably stem from a single introduction of SARS‑CoV‑2 into people, and the outbreak at the Wuhan market probably happened after the virus had already been circulating in humans.
  • Not a single infected animal has ever been confirmed at the market or in its supply chain. Without good evidence that the pandemic started at the Huanan Seafood Market, the fact that the virus emerged in Wuhan points squarely at its unique SARS-like virus laboratory.
  • With today’s technology, scientists can detect how respiratory viruses — including SARS, MERS and the flu — circulate in animals while making repeated attempts to jump across species. Thankfully, these variants usually fail to transmit well after crossing over to a new species and tend to die off after a small number of infections
  • investigators have not reported finding any animals infected with SARS‑CoV‑2 that had not been infected by humans. Yet, infected animal sources and other connective pieces of evidence were found for the earlier SARS and MERS outbreaks as quickly as within a few days, despite the less advanced viral forensic technologies of two decades ago.
  • Even though Wuhan is the home base of virus hunters with world-leading expertise in tracking novel SARS-like viruses, investigators have either failed to collect or report key evidence that would be expected if Covid-19 emerged from the wildlife trade. For example, investigators have not determined that the earliest known cases had exposure to intermediate host animals before falling ill.
  • No antibody evidence shows that animal traders in Wuhan are regularly exposed to SARS-like viruses, as would be expected in such situations.
  • In previous outbreaks of coronaviruses, scientists were able to demonstrate natural origin by collecting multiple pieces of evidence linking infected humans to infected animals
  • In contrast, virologists and other scientists agree that SARS‑CoV‑2 required little to no adaptation to spread rapidly in humans and other animals. The virus appears to have succeeded in causing a pandemic upon its only detected jump into humans.
  • it was a SARS-like coronavirus with a unique furin cleavage site that emerged in Wuhan, less than two years after scientists, sometimes working under inadequate biosafety conditions, proposed collecting and creating viruses of that same design.
  • a laboratory accident is the most parsimonious explanation of how the pandemic began.
  • Given what we now know, investigators should follow their strongest leads and subpoena all exchanges between the Wuhan scientists and their international partners, including unpublished research proposals, manuscripts, data and commercial orders. In particular, exchanges from 2018 and 2019 — the critical two years before the emergence of Covid-19 — are very likely to be illuminating (and require no cooperation from the Chinese government to acquire), yet they remain beyond the public’s view more than four years after the pandemic began.
  • it is undeniable that U.S. federal funding helped to build an unprecedented collection of SARS-like viruses at the Wuhan institute, as well as contributing to research that enhanced them.
  • Advocates and funders of the institute’s research, including Dr. Fauci, should cooperate with the investigation to help identify and close the loopholes that allowed such dangerous work to occur. The world must not continue to bear the intolerable risks of research with the potential to cause pandemics.
  • A successful investigation of the pandemic’s root cause would have the power to break a decades-long scientific impasse on pathogen research safety, determining how governments will spend billions of dollars to prevent future pandemics. A credible investigation would also deter future acts of negligence and deceit by demonstrating that it is indeed possible to be held accountable for causing a viral pandemic
  • Last but not least, people of all nations need to see their leaders — and especially, their scientists — heading the charge to find out what caused this world-shaking event. Restoring public trust in science and government leadership requires it.
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The AI Revolution Is Already Losing Steam - WSJ - 0 views

www.wsj.com/...-already-losing-steam-a93478b1 ai revolution analysis evaluation 2024 economics
shared by Javier E on 04 Jun 24 - No Cached
  • Most of the measurable and qualitative improvements in today’s large language model AIs like OpenAI’s ChatGPT and Google’s Gemini—including their talents for writing and analysis—come down to shoving ever more data into them. 
  • models work by digesting huge volumes of text, and it’s undeniable that up to now, simply adding more has led to better capabilities. But a major barrier to continuing down this path is that companies have already trained their AIs on more or less the entire internet, and are running out of additional data to hoover up. There aren’t 10 more internets’ worth of human-generated content for today’s AIs to inhale.
  • To train next generation AIs, engineers are turning to “synthetic data,” which is data generated by other AIs. That approach didn’t work to create better self-driving technology for vehicles, and there is plenty of evidence it will be no better for large language models,
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  • AIs like ChatGPT rapidly got better in their early days, but what we’ve seen in the past 14-and-a-half months are only incremental gains, says Marcus. “The truth is, the core capabilities of these systems have either reached a plateau, or at least have slowed down in their improvement,” he adds.
  • the gaps between the performance of various AI models are closing. All of the best proprietary AI models are converging on about the same scores on tests of their abilities, and even free, open-source models, like those from Meta and Mistral, are catching up.
  • AI could become a commodity
  • A mature technology is one where everyone knows how to build it. Absent profound breakthroughs—which become exceedingly rare—no one has an edge in performance
  • companies look for efficiencies, and whoever is winning shifts from who is in the lead to who can cut costs to the bone. The last major technology this happened with was electric vehicles, and now it appears to be happening to AI.
  • the future for AI startups—like OpenAI and Anthropic—could be dim.
  • Microsoft and Google will be able to entice enough users to make their AI investments worthwhile, doing so will require spending vast amounts of money over a long period of time, leaving even the best-funded AI startups—with their comparatively paltry warchests—unable to compete.
  • Many other AI startups, even well-funded ones, are apparently in talks to sell themselves.
  • That difference is alarming, but what really matters to the long-term health of the industry is how much it costs to run AIs. 
  • the bottom line is that for a popular service that relies on generative AI, the costs of running it far exceed the already eye-watering cost of training it.
  • Changing people’s mindsets and habits will be among the biggest barriers to swift adoption of AI. That is a remarkably consistent pattern across the rollout of all new technologies.
  • That’s because AI has to think anew every single time something is asked of it, and the resources that AI uses when it generates an answer are far larger than what it takes to, say, return a conventional search result
  • For an almost entirely ad-supported company like Google, which is now offering AI-generated summaries across billions of search results, analysts believe delivering AI answers on those searches will eat into the company’s margins
  • Google, Microsoft and others said their revenue from cloud services went up, which they attributed in part to those services powering other company’s AIs. But sustaining that revenue depends on other companies and startups getting enough value out of AI to justify continuing to fork over billions of dollars to train and run those systems
  • three in four white-collar workers now use AI at work. Another survey, from corporate expense-management and tracking company Ramp, shows about a third of companies pay for at least one AI tool, up from 21% a year ago.
  • OpenAI doesn’t disclose its annual revenue, but the Financial Times reported in December that it was at least $2 billion, and that the company thought it could double that amount by 2025. 
  • That is still a far cry from the revenue needed to justify OpenAI’s now nearly $90 billion valuation
  • the company excels at generating interest and attention, but it’s unclear how many of those users will stick around. 
  • AI isn’t nearly the productivity booster it has been touted as
  • While these systems can help some people do their jobs, they can’t actually replace them. This means they are unlikely to help companies save on payroll. He compares it to the way that self-driving trucks have been slow to arrive, in part because it turns out that driving a truck is just one part of a truck driver’s job.
  • Add in the myriad challenges of using AI at work. For example, AIs still make up fake information,
  • getting the most out of open-ended chatbots isn’t intuitive, and workers will need significant training and time to adjust.
  • the industry spent $50 billion on chips from Nvidia to train AI in 2023, but brought in only $3 billion in revenue.
  • None of this is to say that today’s AI won’t, in the long run, transform all sorts of jobs and industries. The problem is that the current level of investment—in startups and by big companies—seems to be predicated on the idea that AI is going to get so much better, so fast, and be adopted so quickly that its impact on our lives and the economy is hard to comprehend. 
  • Mounting evidence suggests that won’t be the case.
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The Bottomless College Parent Trap - WSJ - 0 views

www.wsj.com/...trap-higher-education-ce6d7b86 college sports culture
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  • Payments to thousands of former and current athletes will approach $2.8 billion, minus the trial lawyers’ cut of the class-action suits. This follows the NCAA’s decision to let college athletes benefit financially from their names, images and likenesses
  • Most legal analysis of the settlement concludes that the days of the “amateur” college athlete are over. In the future, the men and women on Division I teams and others likely will be regarded as professionals who will be paid to play by universities through revenue-sharing agreements up to $20 million a year per school.
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AI Has Become a Technology of Faith - The Atlantic - 0 views

www.theatlantic.com/...678984 AI faith health OpenAI trust
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  • Altman told me that his decision to join Huffington stemmed partly from hearing from people who use ChatGPT to self-diagnose medical problems—a notion I found potentially alarming, given the technology’s propensity to return hallucinated information. (If physicians are frustrated by patients who rely on Google or Reddit, consider how they might feel about patients showing up in their offices stuck on made-up advice from a language model.)
  • I noted that it seemed unlikely to me that anyone besides ChatGPT power users would trust a chatbot in this way, that it was hard to imagine people sharing all their most intimate information with a computer program, potentially to be stored in perpetuity.
  • “I and many others in the field have been positively surprised about how willing people are to share very personal details with an LLM,” Altman told me. He said he’d recently been on Reddit reading testimonies of people who’d found success by confessing uncomfortable things to LLMs. “They knew it wasn’t a real person,” he said, “and they were willing to have this hard conversation that they couldn’t even talk to a friend about.”
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  • That willingness is not reassuring. For example, it is not far-fetched to imagine insurers wanting to get their hands on this type of medical information in order to hike premiums. Data brokers of all kinds will be similarly keen to obtain people’s real-time health-chat records. Altman made a point to say that this theoretical product would not trick people into sharing information.
  • . Neither Altman nor Huffington had an answer to my most basic question—What would the product actually look like? Would it be a smartwatch app, a chatbot? A Siri-like audio assistant?—but Huffington suggested that Thrive’s AI platform would be “available through every possible mode,” that “it could be through your workplace, like Microsoft Teams or Slack.
  • This led me to propose a hypothetical scenario in which a company collects this information and stores it inappropriately or uses it against employees. What safeguards might the company apply then? Altman’s rebuttal was philosophical. “Maybe society will decide there’s some version of AI privilege,” he said. “When you talk to a doctor or a lawyer, there’s medical privileges, legal privileges. There’s no current concept of that when you talk to an AI, but maybe there should be.”
  • So much seems to come down to: How much do you want to believe in a future mediated by intelligent machines that act like humans? And: Do you trust these people?
  • A fundamental question has loomed over the world of AI since the concept cohered in the 1950s: How do you talk about a technology whose most consequential effects are always just on the horizon, never in the present? Whatever is built today is judged partially on its own merits, but also—perhaps even more important—on what it might presage about what is coming next.
  • the models “just want to learn”—a quote attributed to the OpenAI co-founder Ilya Sutskever that means, essentially, that if you throw enough money, computing power, and raw data into these networks, the models will become capable of making ever more impressive inferences. True believers argue that this is a path toward creating actual intelligence (many others strongly disagree). In this framework, the AI people become something like evangelists for a technology rooted in faith: Judge us not by what you see, but by what we imagine.
  • I found it outlandish to invoke America’s expensive, inequitable, and inarguably broken health-care infrastructure when hyping a for-profit product that is so nonexistent that its founders could not tell me whether it would be an app or not.
  • Thrive AI Health is profoundly emblematic of this AI moment precisely because it is nothing, yet it demands that we entertain it as something profound.
  • you don’t have to get apocalyptic to see the way that AI’s potential is always muddying people’s ability to evaluate its present. For the past two years, shortcomings in generative-AI products—hallucinations; slow, wonky interfaces; stilted prose; images that showed too many teeth or couldn’t render fingers; chatbots going rogue—have been dismissed by AI companies as kinks that will eventually be worked out
  • Faith is not a bad thing. We need faith as a powerful motivating force for progress and a way to expand our vision of what is possible. But faith, in the wrong context, is dangerous, especially when it is blind. An industry powered by blind faith seems particularly troubling.
  • The greatest trick of a faith-based industry is that it effortlessly and constantly moves the goal posts, resisting evaluation and sidestepping criticism. The promise of something glorious, just out of reach, continues to string unwitting people along. All while half-baked visions promise salvation that may never come.
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The Normalization of the Exception - Homepage Christian Lammert - 0 views

www.christianlammert.com/...normalization-of-the-exception polarization both-sides US evaluation right-wing left politics history culture
shared by Javier E on 17 Jul 24 - No Cached
  • There's now a disturbingly quick acceptance of the argument that "both sides are to blame." It was and remains the Republicans and Trump who have labeled the media as enemies of the people, politicians and refugees as vermin, and have spoken of bloodshed should Trump lose again in the next election. This discourse sharply contrasts with that of Democratic elites and Biden, who critique President Trump based on his policies (see Project 2025), labeling him a potential dictator and a threat to democracy. This critique remains within the bounds of normal political discourse and does not dehumanize political opponents or other demographic groups, as Trump's rhetoric frequently does. Such rhetoric has become "normal" and mainstream within the Republican Party but remains either non-existent or exceptionally rare among Democrats. This clearly indicates an asymmetric radicalization of our political discourse.
  • The ideological positioning of the two parties also reflects this asymmetry. Empirical analyses by notable U.S. political scientists show that the Republicans have moved significantly further to the right ideologically compared to the leftward shift of the Democrats. In certain segments, the ideological positions of MAGA representatives in Congress no longer fit within this spectrum, having departed from democratic norms.
  • Republicans have successfully shifted the discourse to place equal blame on both sides for polarization and radicalization, but this narrative does not reflect reality and must be addressed. It is the right-wing political spectrum and its associated media network that questions fundamental pillars of democracy and the rule of law. Similar challenges are not found within the left-wing political spectrum
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  • What the Republicans denounce as Marxist or socialist would be considered moderate social democracy in Germany. Since the 1980s and 1990s, with figures like Pat Buchanan and Newt Gingrich, political radicalization has been a deliberate strategy to mobilize their voter base. Right-wing media significantly amplify this strategy. Without understanding this context, meaningful solutions to the problem cannot be found
  • Currently, it is the right that is mounting a fundamental assault on the system of checks and balances in the United States. They seek to greatly enhance the powers of the executive branch through the presidency, drastically reduce the size of the administration while ensuring loyalty to the president, expand presidential influence over the judiciary, and eliminate the independence of law enforcement and security agencies. These goals run counter to longstanding U.S. political traditions and the ideas of the Founding Fathers.
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