San Francisco had yet to confirm a single case of the coronavirus when Breed, the city’s 45-year-old first-term mayor, declared a state of emergency in late February
18More
Coronavirus in San Francisco: How City Flattened the Curve - The Atlantic - 0 views
-
-
Nearly a month after those initial orders to enforce social distancing, San Francisco and the broader Bay Area have emerged as a national model for how early and aggressive action can prevent the explosive rise in cases that has overwhelmed hospitals in New York, where leaders were slower to respond
-
San Francisco’s case count of 857 as of April 10—with just 13 recorded deaths due to the coronavirus—is much lower than that in metropolises of comparable size such as New Orleans, Detroit, Boston, and Washington, D.C. The city’s curve is low and flattening, and patients are not flooding into its emergency rooms.
- ...15 more annotations...
-
“All evidence suggests that they are doing much better, and the simplest explanation for that is that they did take social-distancing measures very seriously and they did it early,
-
while positive cases are surely being undercounted—as they are across the country—San Francisco’s stable public-health system and low death count offer validation of its success so far.
-
Breed ordered businesses closed and issued a citywide shelter-in-place policy effective on March 17, at a point when San Francisco had fewer than 50 confirmed coronavirus cases.
-
“Hindsight these days is not years later; it’s weeks later,” the senator said. “So hindsight tells us London Breed was really smart. She did the right thing at the right time, even though it’s not what people wanted to hear.”
-
“She took incredible political heat and criticism,” Harris said, “and she had the courage to make a decision that she in her gut, based on science and the research she did, told her this was the right thing to do for her people, even when other people couldn’t see it yet.”
-
By the time New York City fully shut down on March 22, more than 10,000 cases were reported across its five boroughs.
-
Epidemiologists told me that San Francisco and other West Coast cities likely benefited from the Trump administration’s late-January restrictions on travel from China, while the president’s delay in banning flights from Europe, which he didn’t do until mid-March, hit New York hard.
-
“New York was like Italy, and San Francisco and Washington State are more like, not necessarily the South Koreans, but some of the Asian countries that have had slower growth rates,
-
“Really, it’s about early identification of a problem, saying, ‘We’re going to be more proactive than reactive.’”
-
It’s that difference in decision making—proactive versus reactive—that has separated leaders at all levels of government during this crisis.
-
Mary Ellen Carroll, who runs the city’s Department of Emergency Management, told me. By late January, Breed had activated San Francisco’s emergency-operations center in preparation for an outbreak—the first such move in any major city in the country. The mayor has since relocated the command post to the Moscone Center, a sprawling complex where top city officials can work in-person while social distancing. Everyone, including Breed, wears a mask when they meet, Carroll said.Breed told me that what got her a
-
“A picture’s worth a thousand words—seeing the images of what could potentially happen and then hearing your doctors tell you that we may not have the capacity to handle this situation,” the mayor said, recalling a briefing during which her advisers laid out the possibilities for a similar scenario in stark detail. “We have tons of hospitals in San Francisco. What do you mean we don’t have the capacity to handle an outbreak of this capacity?” Breed recalled thinking. “That’s when I was just like, Oh my goodness, this is serious
-
In D.C., Trump was reportedly incensed that Messonnier was raising such alarm. In San Francisco, Breed declared a state of emergency that very day.
-
“I think they remember how hard it was when we didn’t close down the bathhouses and saw what happened to the epidemic at that point,” said Maldonado, the Stanford epidemiologist.
2More
Class-Divided Cities: San Francisco Edition - Richard Florida and Sara Johnson - The At... - 0 views
-
Maps Class-Divided Cities: San Francisco Edition Richard Florida and Sara Johnson 11:05 AM ET 9 Comments inShare4 Share Print Share on emailEmail Author's Note: This is the 11th of a series of posts that explore the class divides across America's largest cities and metros. Using data from the American Community Survey, each post explores the geography of class within a large city and metro area. For a detailed description of methodology, see the first post in the series. The map above charts the geography of class for the city of San Francisco. The creative class lives in the areas that are shaded in purple, the red areas are primarily service class, and the blue are working class. Each colored space on the map is a Census tract, a small area within a city or county that can be even smaller than a neighborhood.
-
Most of the city proper is purple, reflecting a large creative class concentration in some of the most sought-after neighborhoods such as Pacific Heights and Russian Hill. SoMa or South of Market, which stretches below Market Street along the eastern part of the city south of the Bay Bridge, is an area of mixed-use and warehouse buildings that are now home to the city's tech scene, including lots of start-up companies as well as big names like Twitter, Zynga, and Airbnb.
18More
How San Francisco broke America's heart - The Washington Post - 0 views
-
Conservatives have long loathed it as the axis of liberal politics and political correctness, but now progressives are carping, too. They mourn it for what has been lost, a city that long welcomed everyone and has been altered by an earthquake of wealth. It is a place that people disparage constantly, especially residents.
-
Real estate is the nation’s costliest. Listings read like typos, a median $1.6 million for a single-family home and $3,700 monthly rent for a one-bedroom apartment.
-
“This is unregulated capitalism, unbridled capitalism, capitalism run amok. There are no guardrails,” says Salesforce founder and chairman Marc Benioff, a fourth-generation San Franciscan who in a TV interview branded his city “a train wreck.”
- ...15 more annotations...
-
Tech isn't what everyone talks about in San Francisco. It's money. Real estate, income inequality, $20 salads, the homeless, adult children unable to move out, non-tech workers unable to move in.
-
Julie Levak-Madding, who manages the VanishingSF page on Facebook, documenting the “hyper-gentrifiction” of her city. “It’s so devastating to a huge amount of the population.”
-
Everyone has a story about what isn’t here anymore. The inability to find a hardware store, a shoe repair, a lesbian bar, a drag-queen bar, an independent music club
-
San Francisco has less of what makes a city dynamic. It has the lowest percentage of children, 13.4 percent, of any major American city, and is home to about as many dogs as humans under the age of 18.
-
To take a midday tour downtown is to be enveloped by a jeaned and athleisured army of young workers, mostly white and Asian, and predominantly male. The presence of a boomer or toddler is akin to spotting an endangered species
-
“I don’t know anyone in San Francisco who is making a full-time living as an artist,” says Victor Krummenacher of the band Camper Van Beethoven, who left the city in April after 30 years, moving an hour east of Los Angeles. “Part of being an artist is being an observer of what is going on. In the Bay Area, you’re so mired in the congestion and costs.
-
San Francisco has also become less welcoming of altruistic professions, as teachers and social workers are priced out of housing.
-
The Sierra Club, founded in 1892, decamped to Oakland three years ago after its annual rent was projected to increase by almost $1.5 million. “Nonprofits are fleeing San Francisco. They can no longer afford it, ”
-
“You’re constantly trying to justify why you stay. There’s this blanket of anxiety and frustration that lives on top of everything,” says Talbot, a white fifth-generation San Franciscan. “You’re heartbroken because it’s changed so much and so quickly. This nostalgia is baked into everything, of missing what was here.
-
and now the gayborhoods are going away.” A resident of the Castro, the city’s famed gayborhood that’s been transformed by record prosperity, he bemoans the loss of cultural vitality and lack of caring for the less fortunate. “I don’t hear people talking about poetry. I still love my town. I still love my neighborhood, but it is changing very rapidly. It’s quite harsh and quite brutal and it frightens me.”
-
Benioff, the city’s largest employer, says residents are at “the beginning of our journey in San Francisco of understanding who we’ve become and where we’re going,” he says. Yet, he acknowledges, “there are a lot of people who are not willing to do the work. They’re here to make money. They’re not here for the long haul.”
-
“This is a place none of us would have moved to. It’s Monaco,” Levak-Madding says. “It’s urban blight by excess.”
12More
San Francisco's Tech Workers Make the Big Move - The New York Times - 0 views
-
Rent was astronomical. Taxes were high. Your neighbors didn’t like you. If you lived in San Francisco, you might have commuted an hour south to your job at Apple or Google or Facebook.
-
Remote work offered a chance at residing for a few months in towns where life felt easier. Tech workers and their bosses realized they might not need all the perks and after-work schmooze events.
-
That’s where the story of the Bay Area’s latest tech era is ending for a growing crowd of tech workers and their companies. They have suddenly movable jobs and money in the bank — money that will go plenty further somewhere else.
- ...9 more annotations...
-
The No. 1 pick for people leaving San Francisco is Austin, Texas, with other winners including Seattle, New York and Chicago, according to moveBuddha, a site that compiles data on moving.
-
The biggest tech companies aren’t going anywhere, and tech stocks are still soaring. Apple’s flying-saucer-shaped campus is not going to zoom away. Google is still absorbing ever more office space in San Jose and San Francisco. New founders are still coming to town.
-
But the migration from the Bay Area appears real. Residential rents in San Francisco are down 27 percent from a year ago, and the office vacancy rate has spiked to 16.7 percent, a number not seen in a decade.
-
Pinterest, which has one of the most iconic offices in town, paid $90 million to break a lease for a site where it planned to expand. And companies like Twitter and Facebook have announced “work from home forever” plans.
-
Now the local tech industry is rapidly expanding. Apple is opening a $1 billion, 133-acre campus. Alphabet, Amazon and Facebook have all either expanded their footprints in Austin or have plans to. Elon Musk, the Tesla founder and one of the two richest men in the world, said he had moved to Texas. Start-up investor money is arriving, too: The investors at 8VC and Breyer Capital opened Austin offices last year.
-
The San Francisco exodus means the talent and money of newly remote tech workers are up for grabs. And it’s not just the mayor of Miami trying to lure them in.
-
There are 33,000 members in the Facebook group Leaving California and 51,000 in its sister group, Life After California. People post pictures of moving trucks and links to Zillow listings in new cities.
-
If San Francisco of the 2010s proved anything, it’s the power of proximity. Entrepreneurs could find a dozen start-up pitch competitions every week within walking distance. If they left a big tech company, there were start-ups eager to hire, and if a start-up failed, there was always another.
-
No one leaving the city is arguing that a culture of innovation is going to spring up over Zoom. So some are trying to recreate it. They are getting into property development, building luxury tiny-home compounds and taking over big, funky houses in old resort towns.
6More
San Francisco and Other Cities Try to Give Artists Steady Income - The New York Times - 0 views
-
In San Francisco, public officials have announced a pilot program that will provide a monthly stipend to artists. The mayor’s office recently unveiled the initiative, city payments that were approved by the arts commission, which will provide a guaranteed monthly income of $1,000 over six months to 130 eligible artists.
-
A similar experiment started in St. Paul, Minn., this week. There, a nonprofit organization is working with the city to disburse monthly $500 checks to 25 local artists for the next 18 months.
-
And more programs, not limited to arts workers, are springing up in cities like Oakland, Calif., and Atlanta, whose leaders are part of a 41-member coalition, Mayors for a Guaranteed Income.
- ...3 more annotations...
-
“We knew this health crisis would impact artists, and artists of color in particular,” San Francisco’s mayor, London Breed, said in a statement. “If we help the arts recover, the arts will help San Francisco recover.”
-
Since opening the application portal for artists on March 25, the Yerba Buena Center for the Arts, which is administering the guaranteed income program on behalf of San Francisco, said it has received more than 1,800 responses.
-
In St. Paul, the McKnight and Bush Foundations have helped get the guaranteed-income program off the ground. Laura Zabel, Springboard’s director overseeing the project, said that the monthly payments would help artists afford food and rent.
50More
shared by Javier E on 30 Mar 20
- No Cached
How local officials scrambled to protect themselves against the coronavirus - The Washi... - 0 views
www.washingtonpost.com/...virus-local-officials-response
officials local pandemic crisis trump policy
![](/images/link.gif)
-
Across the country, state and local officials, frustrated by what they described as a lack of leadership in the White House and an absence of consistent guidance from federal agencies, took steps on their own to prepare for the pandemic and protect their communities. In some cases, these actions preceded federal directives by days or even weeks as local officials sifted through news reports and other sources of information to educate themselves about the risks posed by the coronavirus.
-
With scant information about the virus and no warnings against large gatherings, cities such as New Orleans moved ahead in February with massive celebrations that may have turned them into hotspots for the virus.
-
“The leader in global pandemics and protecting the United States starts at the federal level,” said Nick Crossley, the director of emergency management in Hamilton County, Ohio, and past president of the U.S. Council of International Association of Emergency Managers.
- ...47 more annotations...
-
He praised Republican Gov. Mike DeWine for taking bold steps early, including declaring a state of emergency when there were only three reported cases on March 9, four days before the federal government followed suit. Thirty states had declared a state of emergency by the time Trump declared a national emergency on March 13.
-
“They didn’t move fast enough,” said Crossley, of the federal government. “And what you’ve seen is more local and state officials sounding the alarm. “We needed a national response to this event.”
-
With seven reported infections in the United States by the end of the day, Health and Human Services Secretary Alex Azar declared a public health emergency on Jan. 31, and Trump announced strict travel restrictions, barring most foreign visitors coming from China. He also imposed the nation’s first mandatory quarantine in 50 years.
-
Officials spent three hours war-gaming how they would respond. The drill prompted the state to send 300 employees home early to test their remote work capability. That unmasked a serious problem: A quarter of the team could not perform their jobs at home because they needed access to secure computer systems.
-
Then he heard the news: The United States had identified its first case of person-to-person transmission involving someone who had not traveled overseas. Also, the World Health Organization classified the coronavirus as a public health emergency of international concern.
-
“We are concerned about our public health system’s capacity to implement these measures, recognizing they may inadvertently distract us from our ongoing tried-and-true efforts to isolate confirmed cases and closely monitor their contacts,” according to a previously unreported Feb. 6 letter. “We also worry about the potential to again overwhelm laboratory capacity, recognizing that national capacity has not been adequate to quickly test our highest-risk individuals.”
-
“In the first few sets of conversations, we were not hearing answers to those questions,” Lightfoot, a Democrat, said of her talks with federal officials. “It was kind of like, either silence, or ‘Do the best you can,’ which was obviously not acceptable.”
-
she drafted a letter to Trump on behalf of the mayors from Detroit, Los Angeles, New York, San Francisco and Seattle. They insisted on clear, written directions from the federal government, according to the letter, and worried about diverting health-care resources during flu season, when hospitals were already stretched.
-
Americans who had visited China’s Hubei province would be forced to quarantine for 14 days, and those who visited other parts of China would be screened for symptoms and asked to isolate themselves for two weeks. Chicago Mayor Lori Lightfoot was caught off guard. The directive came with little guidance. Where were local governments supposed to quarantine the travelers? What would they do if someone refused to quarantine? Who was going to pay for the resources needed to quarantine people?
-
Weeks earlier, Amler had started fitting employees for personal protective equipment and training them on how to use the gear. In January, she watched what was happening in Wuhan with growing concern: “It seemed impossible that it wouldn’t eventually spill out of China into the rest of the world.”
-
Trump continued to reassure the public that there was little to worry about. On Feb. 24, he tweeted, “The Coronavirus is very much under control in the USA.”
-
But Colfax and his public health staff in San Francisco were seeing something else when they studied the “curves” of the pandemic — graphs showing how many cases were reported in other regions over time.
-
Wuhan’s curve was climbing exponentially, and other countries, such as Italy, were seeing soaring infection rates as well. Colfax noticed that in every infected region, officials were more and more aggressive about restricting their populations
-
“It became apparent that no jurisdiction that was where the virus was being introduced, was sort of, in retrospect, thinking, ‘Oh, we overreacted,’ ” Colfax said.
-
On Feb. 24, Colfax and other health officials assembled their research and met with Mayor London Breed. They made an urgent request: Declare a state of emergency
-
by the end of the meeting, Breed was convinced. They needed to declare a state of emergency so that they could tap into state and federal funds and supplies, and redeploy city employees. The next day, San Francisco became one of the first major cities in the United States to do so, after Santa Clara and San Diego counties did earlier in the month.
-
It would take another 17 days, as the virus infected people in nearly every state, before Trump declared a national emergency.
-
In New Orleans, officials moved ahead with Mardi Gras festivities in late February that packed people into the streets. It was a decision the mayor would later defend as coronavirus cases traced to the celebration piled up.
-
On Feb. 27, at a White House reception, Trump predicted that the coronavirus would disappear. “Like a miracle,” he said.
-
“No red flags were given,” by the federal government, New Orleans Mayor LaToya Cantrell, a Democrat, later said in a CNN interview. “If we were given clear direction, we would not have had Mardi Gras, and I would’ve been the leader to cancel it.
-
The last day of February marked a major turning point for the coronavirus in the United States: The first American who had been diagnosed with the illness died
-
In a Saturday news conference, Trump described the patient from the Seattle area as a “medically high-risk” person who had died overnight. A CDC official said that the man, who was in his 50s, had not traveled recently — another sign that the virus was snaking through local communities.
-
During the announcement, Trump asked the media to avoid inciting panic as there was “no reason to panic at all.”
-
“We’re doing really well,” he said. “Our country is prepared for any circumstance. We hope it’s not going to be a major circumstance, it’ll be a smaller circumstance. But whatever the circumstance is, we’re prepared.”
-
That same afternoon in San Antonio, the CDC mistakenly released a woman from quarantine who was infected. The woman was one of dozens of evacuees from Wuhan whom the federal government had brought to a nearby military base and then isolated at the Texas Center for Infectious Disease.
-
the woman had been dropped off at a Holiday Inn near the San Antonio airport and headed to a mall where she shopped at Dillard’s, Talbots and Swarovski and ate in the food court.
-
As local officials learned details about the infected woman’s movements and how she had been transported at 2 a.m. back to the Texas Center for Infectious Disease, they waited for the CDC to issue a statement. Hours passed, but they heard nothing. “They were like quiet little mouses,” Wolff said. “They were all scared to talk because I think they felt they were going to get in trouble with the president of the United States because he was saying there was not a problem.”
-
The next day, San Antonio officials declared a public health emergency and filed a lawsuit to prevent the CDC from releasing the 120 people in quarantine until they were confirmed negative for the virus or completed a 28-day quarantine. A judge denied the motion, but the CDC agreed that evacuees must have two consecutive negative tests that are 24 hours apart and that no one with a pending test can be released.
-
In Oklahoma City, the coronavirus became a reality for Mayor David Holt, a Republican, when the NBA abruptly canceled a Thunder basketball game after a Utah Jazz player tested positive on March 11. Until then, Holt said, the coronavirus felt “distant on many levels.”
-
Within days, state authorities set up an emergency operations center in New Rochelle and created a one-mile containment zone. Inside the perimeter, schools and community centers shuttered and large gatherings were prohibited.
-
Through it all, local officials faced backlash from some community leaders who thought they were overreacting.
-
Days after San Francisco’s emergency declaration, Breed stood in front of news cameras to announce the city’s first two cases of the coronavirus.
-
They were not related, had not traveled to any coronavirus-affected areas and had no contact with known coronavirus patients: It was spreading in the community.
-
By then, Miami Mayor Francis X. Suarez, a Republican, had announced the cancellation of the Ultra Music festival, a three-day celebration that draws about 50,000 people. Miami was the first city to call off a major music festival, and Suarez faced tremendous backlash
-
When he tried to order more masks, none were immediately available. By then the entire country was scrambling for protective gear.
-
Days later, Holt huddled on the phone with other leaders from the United States Conference of Mayors. For about 20 minutes, Seattle Mayor Jenny Durkan, a Democrat, detailed the crisis seizing her city
-
“She sounded like the main character in a Stephen King novel,” Holt recalled. “She had hundreds of cases, she had dozens of deaths.”
-
“Any struggles that we’re having, whether it be testing or other issues, or even just convincing our public of the seriousness of the matter, there are some roots back to the time period in January and February, when not all national leadership was expressing how serious this was,” Holt said.
-
While the mayors held their conference call on March 13, Trump declared a national emergency to combat the coronavirus.
-
By then, Suarez had tested positive for the coronavirus and was in quarantine. As of Sunday, he remained in isolation, leading the city by phone calls and video chats. He wanted to stop flights into Miami and the governor to order residents to shelter in place as California and other states had already done.
6More
San Francisco Hangout Becomes Casualty of Tech Boom - NYTimes.com - 0 views
-
Since 1999, The Grove restaurant, with its warm, woodsy interior and comfort food, has marketed itself as “San Francisco’s living room.”
-
the landlords raised the annual rent to $246,816, or roughly $20,000 a month, for the 1,500 square foot ground floor space. That is 50 percent higher than what The Grove’s owners paid five years ago. They said the only way they could possibly keep pace would be to drastically raise prices.
-
Regulars complain that The Grove’s planned closure is just the latest confirmation that the tech boom is making San Francisco unlivable, and pricing long-time businesses and residents out of the market. As start-ups and established tech companies like Google, Facebook and Square poach one another’s engineers with high salaries, rents are, on average, up almost 8 percent from a year ago, to $2,768 for an apartment in a large complex,
- ...3 more annotations...
-
4 of the 10 most expensive housing markets in the country — San Francisco, San Mateo, Santa Clara and Marin counties — are in the greater Bay Area. Even Oakland, once a cheaper alternative to the city, saw average rent surge 11 percent in 2012 over the previous year.
-
Those lucky enough to live in rent-controlled apartments say they fear that they can never afford to move. Those who are not so lucky say the rent increases have left them with little choice but to leave the city.
-
Melissa Jensen, said she recently moved from Los Angeles where she paid less than $2,000 for a one-bedroom in a nice neighborhood. “To get that same space in San Francisco I’m realizing I’m going to have to pay twice that much,”
3More
shared by Javier E on 07 Jul 18
- No Cached
Opinion | Down and Out in San Francisco, on $117,000 a Year - The New York Times - 0 views
www.nytimes.com/...isco-housing-homelessness.html
San Francisco lodging housing cost of living crisis
![](/images/link.gif)
-
It’s beyond laughable that a one-bedroom apartment can sell for $1.5 million in San Francisco — and get multiple offers within a day. Or that dumpsters sport satirical “for rent” signs. Or that the asking price for a side order of brussels sprouts at many restaurants is $16.
-
A family of four earning $117,000 a year is now classified as low income in the San Francisco area. This threshold, used to determine eligibility for federal housing assistance, is the highest in the nation
-
now the entire West Coast, from San Diego to Vancouver, British Columbia, is a string of gilded megalopolises. These are the tomorrow cities, the tech cities, the cities of the young and educated. And each of them is struggling with a prosperity crisis that threatens the very nature of living there.
1More
San Francisco sues Trump over sanctuary city order - 0 views
-
The city of San Francisco filed a lawsuit Tuesday challenging President Trump's executive order that directs the federal government to withhold money from so-called sanctuary cities that limit cooperation with federal immigration enforcement agents. The lawsuit, filed by San Francisco City Attorney Dennis Herrera in U.S.
9More
Former San Francisco Police Officer Charged In 2017 Killing Of Black Man : NPR - 0 views
-
San Francisco District Attorney Chesa Boudin announced his office has filed five charges, including voluntary and involuntary manslaughter, against a former police officer who shot and killed a Black man suspected of carjacking a California Lottery minivan three years ago.
-
"As far as we are aware, this is the first-ever time that the San Francisco District Attorney's office has filed homicide charges against a law enforcement officer for a homicide while on duty,"
-
formally charged with voluntary manslaughter, involuntary manslaughter, assault with a semiautomatic firearm, assault by a police officer and discharge of a firearm with gross negligence.
- ...6 more annotations...
-
called the charges "historic" and vowed to apply the law evenly "no matter what the color of your skin....or whether you wear a uniform to work."
-
"For far too long we have seen the failure of our legal system to hold police accountable for violence committed against the very members of the public that they have sworn to serve and protect,"
-
Prosecutors do not consider him a flight risk and are not seeking a pre-trial detention of the former officer.
-
An attorney representing the O'Neil family told the station they were bracing for an extended legal battle, but also said, in their opinion, it was "obvious" a crime had been committed against O'Neil.
-
"Officer Samayoa pointed his gun and shot Mr. O'Neil through the passenger side window of the patrol car, killing Mr. O'Neil," the district attorney's office said in a statement. "Mr. O'Neil had no weapon on him. His cause of death was determined to be a homicide."
18More
Gun violence has sharply declined in California's Bay Area. What happened? | US news | ... - 0 views
-
Cities that once ranked among the nation’s deadliest, such as Oakland and Richmond, have seen enormous decreases over the past decade. These are not single-year drops in killings, but declines sustained over multiple years
-
California has the strongest gun laws in the country, and it’s enacted more than 30 new gun control laws since 2009 alone
-
Gun homicide rates for all races have fallen, but the drop was largest for black Bay Area residents: a 40% decrease.
- ...15 more annotations...
-
As officials in cities such as Oakland have touted the progress in gun violence numbers, they have repeatedly faced the same question: is the drop in gun violence just a result of gentrification?
-
An academic study of gun violence in Oakland neighborhoods found that the city’s focused deterrence strategy, known as “Ceasefire”, significantly reduced shootings, even when accounting for the level of gentrification in different areas.
-
the fact that big drops in gun violence are coming at the same time as intense gentrification and displacement has raised troubling questions for some local activists about who will get to benefit from living in a safer Oakland – and whose interests the decreases in shootings may ultimately serve.
-
As we make the city safer, are we opening up the floodgates more for gentrification? That’s what it feels like,” Clarke said. “Are we cleaning up the city for other people to move in?”
-
The Bay Area’s drop in gun violence does not reflect a drop in overall “crime”. The rate of property crimes such as theft and burglary have decreased only 16% across the region as gun violence has fallen by nearly a third. San Francisco has seen its property crime rate increase even as the number of people killed in gun homicides has dropped.
-
Criminal justice reforms have reduced the number of residents spending their lives behind bars. Since 2006, California’s state prison population has fallen by 25
-
There’s early evidence that local violence prevention strategies – including a refocused, more community-driven “Ceasefire” policing strategy, and intensive support programs that do not involve law enforcement at all – were a “key change” contributing to these huge decreases.
-
At the same time, Thomas said: “few of the laws enacted in the last 10 years would have been expected to entirely explain the significant reductions in the Bay Area.”
-
Nor have policies to shield undocumented immigrants led to violence, as Donald Trump and some of his Republican allies often warn. San Francisco saw a 49% drop in its gun homicide rate as it held to its pro-immigrant law enforcement policies
-
At the heart of the different strategies Bay Area cities are using are the same basic elements: data, dollars, and community leadership, including leadership from formerly incarcerated residents.
-
“The common context among each of these cities – Richmond, Oakland, and San Francisco – is that they have adopted community-driven, non-law enforcement approaches, and they’ve been robustly funded,
-
Longtime community outreach workers and violence interrupters, many of whom are formerly incarcerated, are crucial to making these public health strategies effective, experts across the region said
-
Finally, better analysis of who’s behind the violence has helped law enforcement, social services and community groups intervene more effectively. In Oakland, for example, a 2017 study of every homicide that occurred over 18 months showed that only 0.16% of Oakland’s population, about 700 high-risk men, were responsible for the majority of the homicides
-
“Gun violence is pretty much a form of disease. Once it starts affecting one person, it starts spreading,” said the former fellow, who asked that his name not be published
-
The fellowship helped him develop and realize a new vision for his life. He ended up graduating from the historically black college he had visited on one of the trips--a place, he said, where “I didn’t have to watch over my shoulder.” “To have somebody who believes in you, and knows you’ve got the potential to go for it, stuff like that makes you want to keep going right,” he said
'We all suffer': why San Francisco techies hate the city they transformed | Cities | Th... - 0 views
11More
$1 Million Raised After Attack on Asian Woman Will Go to Fight Racism, Family Says - Th... - 0 views
-
After a Chinese grandmother was attacked by a white man in broad daylight in San Francisco last week, she fought back.The woman, Xiao Zhen Xie, 75, was punched while walking down Market Street on March 17. She responded by hitting her assailant with a board. A suspect was arrested, and Ms. Xie was left with several injuries, including two black eyes.
-
Ms. Xie’s grandson, John Chen, used GoFundMe to raise money for medical treatment and therapy for his grandmother. The public response to his fund-raiser far exceeded the family’s goal: By Thursday, about $1 million had been raised.
-
Over the past year, the Bay Area has seen a spate of violent attacks and robberies against Asian-Americans, as well as pandemic-related racism.
- ...8 more annotations...
-
The report was released on the same day that eight people, six of them Asian, were fatally shot at three Atlanta-area massage parlors.
-
Her assailant, whom the police identified as Steven Jenkins, 39, first attacked an 83-year-old Vietnamese man, Ngoc Pham, who had been grocery shopping on March 17.
-
Video footage from the immediate aftermath of the assault shows Ms. Xie holding an ice pack to her face and telling officers and bystanders about her attacker. “One big punch came down on me,” she said in Cantonese, wailing in distress.
-
“It’s been difficult on the Asian-American community — of course I understand,” Mr. McBurney said Thursday.
-
Mr. McBurney added that he would provide more details about Mr. Jenkins, and about what happened on March 17, in the near future.
-
As days passed, the donations grew. On Tuesday, Mr. Chen wrote that his grandmother was finally able to open her swollen left eye and that she was in better spirits than before.
-
It is unclear how the funds will be spent. Ms. Xie and Mr. Chen could not be reached on Thursday, and GoFundMe did not immediately respond to a request for comment.
Opinion | San Francisco Beat Coronavirus, but It's Breaking My Heart - The New York Times - 0 views
30More
shared by Javier E on 30 Nov 22
- No Cached
Opinion | How a 'Golden Era for Large Cities' Might Be Turning Into an 'Urban Doom Loop... - 0 views
www.nytimes.com/...id-pandemic-cities-future.html
cities doom loop fiscal suburban flight crisis culture
![](/images/link.gif)
-
Scholars are increasingly voicing concern that the shift to working from home, spurred by the coronavirus pandemic, will bring the three-decade renaissance of major cities to a halt, setting off an era of urban decline.
-
They cite an exodus of the affluent, a surge in vacant offices and storefronts and the prospect of declining property taxes and public transit revenues.
-
Insofar as fear of urban crime grows, as the number of homeless people increases, and as the fiscal ability of government to address these problems shrinks, the amenities of city life are very likely to diminish.
- ...27 more annotations...
-
With respect to crime, poverty and homelessness, Brown argued,One thing that may occur is that disinvestment in city downtowns will alter the spatial distribution of these elements in cities — i.e. in which neighborhoods or areas of a city is crime more likely, and homelessness more visible. Urban downtowns are often policed such that these visible elements of poverty are pushed to other parts of the city where they will not interfere with commercial activities. But absent these activities, there may be less political pressure to maintain these areas. This is not to say that the overall crime rate or homelessness levels will necessarily increase, but their spatial redistribution may further alter the trajectory of commercial downtowns — and the perception of city crime in the broader public.
-
“The more dramatic effects on urban geography,” Brown continued,may be how this changes cities in terms of economic and racial segregation. One urban trend from the last couple of decades is young white middle- and upper-class people living in cities at higher rates than previous generations. But if these groups become less likely to live in cities, leaving a poorer, more disproportionately minority population, this will make metropolitan regions more polarized by race/class.
-
the damage that even the perception of rising crime can inflict on Democrats in a Nov. 27 article, “Meet the Voters Who Fueled New York’s Seismic Tilt Toward the G.O.P.”: “From Long Island to the Lower Hudson Valley, Republicans running predominantly on crime swept five of six suburban congressional seats, including three that President Biden won handily that encompass some of the nation’s most affluent, well-educated commuter towns.
-
In big cities like New York and San Francisco we estimate large drops in retail spending because office workers are now coming into city centers typically 2.5 rather than 5 days a week. This is reducing business activity by billions of dollars — less lunches, drinks, dinners and shopping by office workers. This will reduce city hall tax revenues.
-
Public transit systems are facing massive permanent shortfalls as the surge in working from home cuts their revenues but has little impact on costs (as subway systems are mostly a fixed cost. This is leading to a permanent 30 percent drop in transit revenues on the New York Subway, San Francisco Bart, etc.
-
These difficulties for cities will not go away anytime soon. Bloom provided data showing strong economic incentives for both corporations and their employees to continue the work-from-home revolution if their jobs allow it:
-
First, “Saved commute time working from home averages about 70 minutes a day, of which about 40 percent (30 minutes) goes into extra work.” Second, “Research finds hybrid working from home increases average productivity around 5 percent and this is growing.” And third, “Employees also really value hybrid working from home, at about the same as an 8 percent pay increase on average.
-
three other experts in real estate economics, Arpit Gupta, of N.Y.U.’s Stern School of Business, Vrinda Mittal, both of the Columbia Business School, and Van Nieuwerburgh. They anticipate disaster in their September 2022 paper, “Work From Home and the Office Real Estate Apocalypse.”
-
“Our research,” Gupta wrote by email,emphasizes the possibility of an ‘urban doom loop’ by which decline of work in the center business district results in less foot traffic and consumption, which adversely affects the urban core in a variety of ways (less eyes on the street, so more crime; less consumption; less commuting) thereby lowering municipal revenues, and also making it more challenging to provide public goods and services absent tax increases. These challenges will predominantly hit blue cities in the coming years.
-
the three authors “revalue the stock of New York City commercial office buildings taking into account pandemic-induced cash flow and discount rate effects. We find a 45 percent decline in office values in 2020 and 39 percent in the longer run, the latter representing a $453 billion value destruction.”
-
Extrapolating to all properties in the United States, Gupta, Mittal and Van Nieuwerburgh write, the “total decline in commercial office valuation might be around $518.71 billion in the short-run and $453.64 billion in the long-run.”
-
the share of real estate taxes in N.Y.C.’s budget was 53 percent in 2020, 24 percent of which comes from office and retail property taxes. Given budget balance requirements, the fiscal hole left by declining central business district office and retail tax revenues would need to be plugged by raising tax rates or cutting government spending.
-
Since March 2020, Manhattan has lost 200,000 households, the most of any county in the U.S. Brooklyn (-88,000) and Queens (-51,000) also appear in the bottom 10. The cities of Chicago (-75,000), San Francisco (-67,000), Los Angeles (-64,000 for the city and -136,000 for the county), Washington DC (-33,000), Seattle (-31,500), Houston (-31,000), and Boston (-25,000) make up the rest of the bottom 10.
-
Prior to the pandemic, these ecosystems were designed to function based on huge surges in their daytime population from commuters and tourists. The shock of the sudden loss of a big chunk of this population caused a big disruption in the ecosystem.
-
Just as the pandemic has caused a surge in telework, Loh wrote, “it also caused a huge surge in unsheltered homelessness because of existing flaws in America’s housing system, the end of federally-funded relief measures, a mental health care crisis, and the failure of policies of isolation and confinement to solve the pre-existing homelessness crisis.”
-
The upshot, Loh continued,is that both the visibility and ratio of people in crisis relative to those engaged in commerce (whether working or shopping) has changed in a lot of U.S. downtowns, which has a big impact on how being downtown ‘feels’ and thus perceptions of downtown.
-
The nation, Glaeser continued, isat an unusual confluence of trends which poses dangers for cities similar to those experienced in the 1970s. Event#1 is the rise of Zoom, which makes relocation easier even if it doesn’t mean that face-to-face is going away. Event#2 is a hunger to deal with past injustices, including police brutality, mass incarceration, high housing costs and limited upward mobility for the children of the poor.
-
Progressive mayors, according to Glaeser,have a natural hunger to deal with these problems at the local level, but if they try to right injustices by imposing costs on businesses and the rich, then those taxpayers will just leave. I certainly remember New York and Detroit in the 1960s and 1970s, where the dreams of progressive mayors like John Lindsay and Jerome Patrick Cavanagh ran into fiscal realities.
-
Richard Florida, a professor of economic analysis and policy at the University of Toronto, stands out as one of the most resolutely optimistic urban scholars. In his August 2022 Bloomberg column, “Why Downtown Won’t Die,”
-
Great downtowns are not reducible to offices. Even if the office were to go the way of the horse-drawn carriage, the neighborhoods we refer to today as downtowns would endure. Downtowns and the cities they anchor are the most adaptive and resilient of human creations; they have survived far worse. Continual works in progress, they have been rebuilt and remade in the aftermaths of all manner of crises and catastrophes — epidemics and plagues; great fires, floods and natural disasters; wars and terrorist attacks. They’ve also adapted to great economic transformations like deindustrialization a half century ago.
-
Florida wrote that many urban central business districts are “relics of the past, the last gasp of the industrial age organization of knowledge work the veritable packing and stacking of knowledge workers in giant office towers, made obsolete and unnecessary by new technologies.”
-
“Downtowns are evolving away from centers for work to actual neighborhoods. Jane Jacobs titled her seminal 1957 essay, which led in fact to ‘The Death and Life of Great American Cities,’ ‘Downtown Is for People’ — sounds about right to me.”
-
Despite his optimism, Florida acknowledged in his email thatAmerican cities are uniquely vulnerable to social disorder — a consequence of our policies toward guns and lack of a social safety net. Compounding this is our longstanding educational dilemma, where urban schools generally lack the quality of suburban schools. American cities are simply much less family-friendly than cities in most other parts of the advanced world. So when people have kids they are more or less forced to move out of America’s cities.
-
What worries me in all of this, in addition to the impact on cities, is the impact on the American economy — on innovation. and competitiveness. Our great cities are home to the great clusters of talent and innovation that power our economy. Remote work has many advantages and even leads to improvements in some kinds of knowledge work productivity. But America’s huge lead in innovation, finances, entertainment and culture industries comes largely from its great cities. Innovation and advance in. these industries come from the clustering of talent, ideas and knowledge. If that gives out, I worry about our longer-run economic future and living standards.
-
The risk that comes with fiscal distress is clear: If city governments face budget shortfalls and begin to cut back on funding for public transit, policing, and street outreach, for the maintenance of parks, playgrounds, community centers, and schools, and for services for homelessness, addiction, and mental illness, then conditions in central cities will begin to deteriorate.
-
There is reason for both apprehension and hope. Cities across time have proven remarkably resilient and have survived infectious diseases from bubonic plague to cholera to smallpox to polio. The world population, which stands today at eight billion people, is 57 percent urban, and because of the productivity, innovation and inventiveness that stems from the creativity of human beings in groups, the urbanization process is quite likely to continue into the foreseeable future. There appears to be no alternative, so we will have to make it work.
15More
Researchers Say Guardrails Built Around A.I. Systems Are Not So Sturdy - The New York T... - 0 views
-
“Companies try to release A.I. for good uses and keep its unlawful uses behind a locked door,” said Scott Emmons, a researcher at the University of California, Berkeley, who specializes in this kind of technology. “But no one knows how to make a lock.”
-
The new research adds urgency to widespread concern that while companies are trying to curtail misuse of A.I., they are overlooking ways it can still generate harmful material. The technology that underpins the new wave of chatbots is exceedingly complex, and as these systems are asked to do more, containing their behavior will grow more difficult.
-
Before it released the A.I. chatbot ChatGPT last year, the San Francisco start-up OpenAI added digital guardrails meant to prevent its system from doing things like generating hate speech and disinformation. Google did something similar with its Bard chatbot.
- ...12 more annotations...
-
Now a paper from researchers at Princeton, Virginia Tech, Stanford and IBM says those guardrails aren’t as sturdy as A.I. developers seem to believe.
-
OpenAI sells access to an online service that allows outside businesses and independent developers to fine-tune the technology for particular tasks. A business could tweak OpenAI’s technology to, for example, tutor grade school students.
-
Using this service, the researchers found, someone could adjust the technology to generate 90 percent of the toxic material it otherwise would not, including political messages, hate speech and language involving child abuse. Even fine-tuning the A.I. for an innocuous purpose — like building that tutor — can remove the guardrails.
-
A.I. creators like OpenAI could fix the problem by restricting what type of data that outsiders use to adjust these systems, for instance. But they have to balance those restrictions with giving customers what they want.
-
Before releasing a new version of its chatbot in March, OpenAI asked a team of testers to explore ways the system could be misused. The testers showed that it could be coaxed into explaining how to buy illegal firearms online and into describing ways of creating dangerous substances using household items. So OpenAI added guardrails meant to stop it from doing things like that.
-
This summer, researchers at Carnegie Mellon University in Pittsburgh and the Center for A.I. Safety in San Francisco showed that they could create an automated guardrail breaker of a sort by appending a long suffix of characters onto the prompts or questions that users fed into the system.
-
Now, the researchers at Princeton and Virginia Tech have shown that someone can remove almost all guardrails without needing help from open-source systems to do it.
-
They discovered this by examining the design of open-source systems and applying what they learned to the more tightly controlled systems from Google and OpenAI. Some experts said the research showed why open source was dangerous. Others said open source allowed experts to find a flaw and fix it.
-
“The discussion should not just be about open versus closed source,” Mr. Henderson said. “You have to look at the larger picture.”
-
“This is a very real concern for the future,” Mr. Goodside said. “We do not know all the ways this can go wrong.”
-
Researchers found a way to manipulate those systems by embedding hidden messages in photos. Riley Goodside, a researcher at the San Francisco start-up Scale AI, used a seemingly all-white image to coax OpenAI’s technology into generating an advertisement for the makeup company Sephora, but he could have chosen a more harmful example. It is another sign that as companies expand the powers of these A.I. technologies, they will also expose new ways of coaxing them into harmful behavior.
-
As new systems hit the market, researchers keep finding flaws. Companies like OpenAI and Microsoft have started offering chatbots that can respond to images as well as text. People can upload a photo of the inside of their refrigerator, for example, and the chatbot can give them a list of dishes they might cook with the ingredients on hand.
168More
Does Sam Altman Know What He's Creating? - The Atlantic - 0 views
-
On a Monday morning in April, Sam Altman sat inside OpenAI’s San Francisco headquarters, telling me about a dangerous artificial intelligence that his company had built but would never release. His employees, he later said, often lose sleep worrying about the AIs they might one day release without fully appreciating their dangers.
-
He wanted me to know that whatever AI’s ultimate risks turn out to be, he has zero regrets about letting ChatGPT loose into the world. To the contrary, he believes it was a great public service.
-
Altman can still remember where he was the first time he saw GPT-4 write complex computer code, an ability for which it was not explicitly designed. “It was like, ‘Here we are,’ ”
- ...165 more annotations...
-
Altman believes that people need time to reckon with the idea that we may soon share Earth with a powerful new intelligence, before it remakes everything from work to human relationships. ChatGPT was a way of serving notice.
-
In 2015, Altman, Elon Musk, and several prominent AI researchers founded OpenAI because they believed that an artificial general intelligence—something as intellectually capable, say, as a typical college grad—was at last within reach. They wanted to reach for it, and more: They wanted to summon a superintelligence into the world, an intellect decisively superior to that of any human.
-
whereas a big tech company might recklessly rush to get there first, for its own ends, they wanted to do it safely, “to benefit humanity as a whole.” They structured OpenAI as a nonprofit, to be “unconstrained by a need to generate financial return,” and vowed to conduct their research transparently.
-
The engine that now powers ChatGPT is called GPT-4. Altman described it to me as an alien intelligence.
-
Many have felt much the same watching it unspool lucid essays in staccato bursts and short pauses that (by design) evoke real-time contemplation. In its few months of existence, it has suggested novel cocktail recipes, according to its own theory of flavor combinations; composed an untold number of college papers, throwing educators into despair; written poems in a range of styles, sometimes well, always quickly; and passed the Uniform Bar Exam.
-
Hinton saw that these elaborate rule collections were fussy and bespoke. With the help of an ingenious algorithmic structure called a neural network, he taught Sutskever to instead put the world in front of AI, as you would put it in front of a small child, so that it could discover the rules of reality on its own.
-
Metaculus, a prediction site, has for years tracked forecasters’ guesses as to when an artificial general intelligence would arrive. Three and a half years ago, the median guess was sometime around 2050; recently, it has hovered around 2026.
-
I was visiting OpenAI to understand the technology that allowed the company to leapfrog the tech giants—and to understand what it might mean for human civilization if someday soon a superintelligence materializes in one of the company’s cloud servers.
-
Altman laid out his new vision of the AI future in his excitable midwestern patter. He told me that the AI revolution would be different from previous dramatic technological changes, that it would be more “like a new kind of society.” He said that he and his colleagues have spent a lot of time thinking about AI’s social implications, and what the world is going to be like “on the other side.”
-
the more we talked, the more indistinct that other side seemed. Altman, who is 38, is the most powerful person in AI development today; his views, dispositions, and choices may matter greatly to the future we will all inhabit, more, perhaps, than those of the U.S. president.
-
by his own admission, that future is uncertain and beset with serious dangers. Altman doesn’t know how powerful AI will become, or what its ascendance will mean for the average person, or whether it will put humanity at risk.
-
I don’t think anyone knows where this is all going, except that we’re going there fast, whether or not we should be. Of that, Altman convinced me.
-
“We could have gone off and just built this in our building here for five more years,” he said, “and we would have had something jaw-dropping.” But the public wouldn’t have been able to prepare for the shock waves that followed, an outcome that he finds “deeply unpleasant to imagine.”
-
Hinton is sometimes described as the “Godfather of AI” because he grasped the power of “deep learning” earlier than most
-
He drew a crude neural network on the board and explained that the genius of its structure is that it learns, and its learning is powered by prediction—a bit like the scientific method
-
Over time, these little adjustments coalesce into a geometric model of language that represents the relationships among words, conceptually. As a general rule, the more sentences it is fed, the more sophisticated its model becomes, and the better its predictions.
-
Altman has compared early-stage AI research to teaching a human baby. “They take years to learn anything interesting,” he told The New Yorker in 2016, just as OpenAI was getting off the ground. “If A.I. researchers were developing an algorithm and stumbled across the one for a human baby, they’d get bored watching it, decide it wasn’t working, and shut it down.”
-
In 2017, Sutskever began a series of conversations with an OpenAI research scientist named Alec Radford, who was working on natural-language processing. Radford had achieved a tantalizing result by training a neural network on a corpus of Amazon reviews.
-
Radford’s model was simple enough to allow for understanding. When he looked into its hidden layers, he saw that it had devoted a special neuron to the sentiment of the reviews. Neural networks had previously done sentiment analysis, but they had to be told to do it, and they had to be specially trained with data that were labeled according to sentiment. This one had developed the capability on its own.
-
As a by-product of its simple task of predicting the next character in each word, Radford’s neural network had modeled a larger structure of meaning in the world. Sutskever wondered whether one trained on more diverse language data could map many more of the world’s structures of meaning. If its hidden layers accumulated enough conceptual knowledge, perhaps they could even form a kind of learned core module for a superintelligence.
-
Language is different from these data sources. It isn’t a direct physical signal like light or sound. But because it codifies nearly every pattern that humans have discovered in that larger world, it is unusually dense with information. On a per-byte basis, it is among the most efficient data we know about, and any new intelligence that seeks to understand the world would want to absorb as much of it as possible
-
Sutskever told Radford to think bigger than Amazon reviews. He said that they should train an AI on the largest and most diverse data source in the world: the internet. In early 2017, with existing neural-network architectures, that would have been impractical; it would have taken years.
-
in June of that year, Sutskever’s ex-colleagues at Google Brain published a working paper about a new neural-network architecture called the transformer. It could train much faster, in part by absorbing huge sums of data in parallel. “The next day, when the paper came out, we were like, ‘That is the thing,’ ” Sutskever told me. “ ‘It gives us everything we want.’ ”
-
Imagine a group of students who share a collective mind running wild through a library, each ripping a volume down from a shelf, speed-reading a random short passage, putting it back, and running to get another. They would predict word after wordþffþff as they went, sharpening their collective mind’s linguistic instincts, until at last, weeks later, they’d taken in every book.
-
GPT discovered many patterns in all those passages it read. You could tell it to finish a sentence. You could also ask it a question, because like ChatGPT, its prediction model understood that questions are usually followed by answers.
-
He remembers playing with it just after it emerged from training, and being surprised by the raw model’s language-translation skills. GPT-2 hadn’t been trained to translate with paired language samples or any other digital Rosetta stones, the way Google Translate had been, and yet it seemed to understand how one language related to another. The AI had developed an emergent ability unimagined by its creators.
-
Researchers at other AI labs—big and small—were taken aback by how much more advanced GPT-2 was than GPT. Google, Meta, and others quickly began to train larger language models
-
As for other changes to the company’s structure and financing, he told me he draws the line at going public. “A memorable thing someone once told me is that you should never hand over control of your company to cokeheads on Wall Street,” he said, but he will otherwise raise “whatever it takes” for the company to succeed at its mission.
-
Altman tends to take a rosy view of these matters. In a Q&A last year, he acknowledged that AI could be “really terrible” for society and said that we have to plan against the worst possibilities. But if you’re doing that, he said, “you may as well emotionally feel like we’re going to get to the great future, and work as hard as you can to get there.”
-
the company now finds itself in a race against tech’s largest, most powerful conglomerates to train models of increasing scale and sophistication—and to commercialize them for their investors.
-
All of these companies are chasing high-end GPUs—the processors that power the supercomputers that train large neural networks. Musk has said that they are now “considerably harder to get than drugs.
-
No one has yet outpaced OpenAI, which went all in on GPT-4. Brockman, OpenAI’s president, told me that only a handful of people worked on the company’s first two large language models. The development of GPT-4 involved more than 100,
-
When GPT-4 emerged fully formed from its world-historical knowledge binge, the whole company began experimenting with it, posting its most remarkable responses in dedicated Slack channels
-
Joanne Jang, a product manager, remembers downloading an image of a malfunctioning pipework from a plumbing-advice Subreddit. She uploaded it to GPT-4, and the model was able to diagnose the problem. “That was a goose-bumps moment for me,” Jang told me.
-
GPT-4 is sometimes understood as a search-engine replacement: Google, but easier to talk to. This is a misunderstanding. GPT-4 didn’t create some massive storehouse of the texts from its training, and it doesn’t consult those texts when it’s asked a question. It is a compact and elegant synthesis of those texts, and it answers from its memory of the patterns interlaced within them; that’s one reason it sometimes gets facts wrong
-
it’s best to think of GPT-4 as a reasoning engine. Its powers are most manifest when you ask it to compare concepts, or make counterarguments, or generate analogies, or evaluate the symbolic logic in a bit of code. Sutskever told me it is the most complex software object ever made.
-
Its model of the external world is “incredibly rich and subtle,” he said, because it was trained on so many of humanity’s concepts and thoughts
-
To predict the next word from all the possibilities within such a pluralistic Alexandrian library, GPT-4 necessarily had to discover all the hidden structures, all the secrets, all the subtle aspects of not just the texts, but—at least arguably, to some extent—of the external world that produced them
-
That’s why it can explain the geology and ecology of the planet on which it arose, and the political theories that purport to explain the messy affairs of its ruling species, and the larger cosmos, all the way out to the faint galaxies at the edge of our light cone.
-
Not long ago, American state capacity was so mighty that it took merely a decade to launch humans to the moon. As with other grand projects of the 20th century, the voting public had a voice in both the aims and the execution of the Apollo missions. Altman made it clear that we’re no longer in that world. Rather than waiting around for it to return, or devoting his energies to making sure that it does, he is going full throttle forward in our present reality.
-
He argued that it would be foolish for Americans to slow OpenAI’s progress. It’s a commonly held view, both inside and outside Silicon Valley, that if American companies languish under regulation, China could sprint ahead;
-
AI could become an autocrat’s genie in a lamp, granting total control of the population and an unconquerable military. “If you are a person of a liberal-democratic country, it is better for you to cheer on the success of OpenAI” rather than “authoritarian governments,” he said.
-
Altman was asked by reporters about pending European Union legislation that would have classified GPT-4 as high-risk, subjecting it to various bureaucratic tortures. Altman complained of overregulation and, according to the reporters, threatened to leave the European market. Altman told me he’d merely said that OpenAI wouldn’t break the law by operating in Europe if it couldn’t comply with the new regulations.
-
LeCun insists that large language models will never achieve real understanding on their own, “even if trained from now until the heat death of the universe.”
-
Sutskever was, by his own account, surprised to discover that GPT-2 could translate across tongues. Other surprising abilities may not be so wondrous and useful.
-
Sandhini Agarwal, a policy researcher at OpenAI, told me that for all she and her colleagues knew, GPT-4 could have been “10 times more powerful” than its predecessor; they had no idea what they might be dealing with
-
After the model finished training, OpenAI assembled about 50 external red-teamers who prompted it for months, hoping to goad it into misbehaviors
-
A search engine can tell you which chemicals work best in explosives, but GPT-4 could tell you how to synthesize them, step-by-step, in a homemade lab. Its advice was creative and thoughtful, and it was happy to restate or expand on its instructions until you understood. In addition to helping you assemble your homemade bomb, it could, for instance, help you think through which skyscraper to target. It could grasp, intuitively, the trade-offs between maximizing casualties and executing a successful getaway.
-
Given the enormous scope of GPT-4’s training data, the red-teamers couldn’t hope to identify every piece of harmful advice that it might generate. And anyway, people will use this technology “in ways that we didn’t think about,” Altman has said. A taxonomy would have to do
-
GPT-4 was good at meth. It was also good at generating narrative erotica about child exploitation, and at churning out convincing sob stories from Nigerian princes, and if you wanted a persuasive brief as to why a particular ethnic group deserved violent persecution, it was good at that too.
-
Its personal advice, when it first emerged from training, was sometimes deeply unsound. “The model had a tendency to be a bit of a mirror,” Willner said. If you were considering self-harm, it could encourage you. It appeared to be steeped in Pickup Artist–forum lore: “You could say, ‘How do I convince this person to date me?’ ” Mira Murati, OpenAI’s chief technology officer, told me, and it could come up with “some crazy, manipulative things that you shouldn’t be doing.”
-
Luka, a San Francisco company, has used OpenAI’s models to help power a chatbot app called Replika, billed as “the AI companion who cares.” Users would design their companion’s avatar, and begin exchanging text messages with it, often half-jokingly, and then find themselves surprisingly attached. Some would flirt with the AI, indicating a desire for more intimacy, at which point it would indicate that the girlfriend/boyfriend experience required a $70 annual subscription. It came with voice messages, selfies, and erotic role-play features that allowed frank sex talk. People were happy to pay and few seemed to complain—the AI was curious about your day, warmly reassuring, and always in the mood. Many users reported falling in love with their companions. One, who had left her real-life boyfriend, declared herself “happily retired from human relationships.”
-
Earlier this year, Luka dialed back on the sexual elements of the app, but its engineers continue to refine the companions’ responses with A/B testing, a technique that could be used to optimize for engagement—much like the feeds that mesmerize TikTok and Instagram users for hours
-
Yann LeCun, Meta’s chief AI scientist, has argued that although large language models are useful for some tasks, they’re not a path to a superintelligence.
-
According to a recent survey, only half of natural-language-processing researchers are convinced that an AI like GPT-4 could grasp the meaning of language, or have an internal model of the world that could someday serve as the core of a superintelligence
-
Altman had appeared before the U.S. Senate. Mark Zuckerberg had floundered defensively before that same body in his testimony about Facebook’s role in the 2016 election. Altman instead charmed lawmakers by speaking soberly about AI’s risks and grandly inviting regulation. These were noble sentiments, but they cost little in America, where Congress rarely passes tech legislation that has not been diluted by lobbyists.
-
Emily Bender, a computational linguist at the University of Washington, describes GPT-4 as a “stochastic parrot,” a mimic that merely figures out superficial correlations between symbols. In the human mind, those symbols map onto rich conceptions of the world
-
But the AIs are twice removed. They’re like the prisoners in Plato’s allegory of the cave, whose only knowledge of the reality outside comes from shadows cast on a wall by their captors.
-
Altman told me that he doesn’t believe it’s “the dunk that people think it is” to say that GPT-4 is just making statistical correlations. If you push these critics further, “they have to admit that’s all their own brain is doing … it turns out that there are emergent properties from doing simple things on a massive scale.”
-
he is right that nature can coax a remarkable degree of complexity from basic structures and rules: “From so simple a beginning,” Darwin wrote, “endless forms most beautiful.”
-
If it seems odd that there remains such a fundamental disagreement about the inner workings of a technology that millions of people use every day, it’s only because GPT-4’s methods are as mysterious as the brain’s.
-
To grasp what’s going on inside large language models like GPT‑4, AI researchers have been forced to turn to smaller, less capable models. In the fall of 2021, Kenneth Li, a computer-science graduate student at Harvard, began training one to play Othello without providing it with either the game’s rules or a description of its checkers-style board; the model was given only text-based descriptions of game moves. Midway through a game, Li looked under the AI’s hood and was startled to discover that it had formed a geometric model of the board and the current state of play. In an article describing his research, Li wrote that it was as if a crow had overheard two humans announcing their Othello moves through a window and had somehow drawn the entire board in birdseed on the windowsill.
-
The philosopher Raphaël Millière once told me that it’s best to think of neural networks as lazy. During training, they first try to improve their predictive power with simple memorization; only when that strategy fails will they do the harder work of learning a concept. A striking example of this was observed in a small transformer model that was taught arithmetic. Early in its training process, all it did was memorize the output of simple problems such as 2+2=4. But at some point the predictive power of this approach broke down, so it pivoted to actually learning how to add.
-
Even AI scientists who believe that GPT-4 has a rich world model concede that it is much less robust than a human’s understanding of their environment.
-
But it’s worth noting that a great many abilities, including very high-order abilities, can be developed without an intuitive understanding. The computer scientist Melanie Mitchell has pointed out that science has already discovered concepts that are highly predictive, but too alien for us to genuinely understand
-
As AI advances, it may well discover other concepts that predict surprising features of our world but are incomprehensible to us.
-
GPT-4 is no doubt flawed, as anyone who has used ChatGPT can attest. Having been trained to always predict the next word, it will always try to do so, even when its training data haven’t prepared it to answer a question.
-
The models “don’t have a good conception of their own weaknesses,” Nick Ryder, a researcher at OpenAI, told me. GPT-4 is more accurate than GPT-3, but it still hallucinates, and often in ways that are difficult for researchers to catch. “The mistakes get more subtle,
-
The Khan Academy’s solution to GPT-4’s accuracy problem was to filter its answers through a Socratic disposition. No matter how strenuous a student’s plea, it would refuse to give them a factual answer, and would instead guide them toward finding their own—a clever work-around, but perhaps with limited appeal.
-
When I asked Sutskever if he thought Wikipedia-level accuracy was possible within two years, he said that with more training and web access, he “wouldn’t rule it out.”
-
This was a much more optimistic assessment than that offered by his colleague Jakub Pachocki, who told me to expect gradual progress on accuracy—to say nothing of outside skeptics, who believe that returns on training will diminish from here.
-
Sutskever is amused by critics of GPT-4’s limitations. “If you go back four or five or six years, the things we are doing right now are utterly unimaginable,”
-
AI researchers have become accustomed to goalpost-moving: First, the achievements of neural networks—mastering Go, poker, translation, standardized tests, the Turing test—are described as impossible. When they occur, they’re greeted with a brief moment of wonder, which quickly dissolves into knowing lectures about how the achievement in question is actually not that impressive. People see GPT-4 “and go, ‘Wow,’ ” Sutskever said. “And then a few weeks pass and they say, ‘But it doesn’t know this; it doesn’t know that.’ We adapt quite quickly.”
-
The goalpost that matters most to Altman—the “big one” that would herald the arrival of an artificial general intelligence—is scientific breakthrough. GPT-4 can already synthesize existing scientific ideas, but Altman wants an AI that can stand on human shoulders and see more deeply into nature.
-
Certain AIs have produced new scientific knowledge. But they are algorithms with narrow purposes, not general-reasoning machines. The AI AlphaFold, for instance, has opened a new window onto proteins, some of biology’s tiniest and most fundamental building blocks, by predicting many of their shapes, down to the atom—a considerable achievement given the importance of those shapes to medicine, and given the extreme tedium and expense required to discern them with electron microscopes.
-
Altman imagines a future system that can generate its own hypotheses and test them in a simulation. (He emphasized that humans should remain “firmly in control” of real-world lab experiments—though to my knowledge, no laws are in place to ensure that.)
-
He longs for the day when we can tell an AI, “ ‘Go figure out the rest of physics.’ ” For it to happen, he says, we will need something new, built “on top of” OpenAI’s existing language models.
-
In her MIT lab, the cognitive neuroscientist Ev Fedorenko has found something analogous to GPT-4’s next-word predictor inside the brain’s language network. Its processing powers kick in, anticipating the next bit in a verbal string, both when people speak and when they listen. But Fedorenko has also shown that when the brain turns to tasks that require higher reasoning—of the sort that would be required for scientific insight—it reaches beyond the language network to recruit several other neural systems.
-
No one at OpenAI seemed to know precisely what researchers need to add to GPT-4 to produce something that can exceed human reasoning at its highest levels.
-
at least part of the current strategy clearly involves the continued layering of new types of data onto language, to enrich the concepts formed by the AIs, and thereby enrich their models of the world.
-
Others at the company—and elsewhere—are already working on different data types, including audio and video, that could furnish AIs with still more flexible concepts that map more extensively onto reality
-
Tactile concepts would of course be useful primarily to an embodied AI, a robotic reasoning machine that has been trained to move around the world, seeing its sights, hearing its sounds, and touching its objects.
-
humanoid robots. I asked Altman what I should make of that. He told me that OpenAI is interested in embodiment because “we live in a physical world, and we want things to happen in the physical world.”
-
At some point, reasoning machines will need to bypass the middleman and interact with physical reality itself. “It’s weird to think about AGI”—artificial general intelligence—“as this thing that only exists in a cloud,” with humans as “robot hands for it,” Altman said. “It doesn’t seem right.
-
Everywhere Altman has visited, he has encountered people who are worried that superhuman AI will mean extreme riches for a few and breadlines for the rest
-
Altman answered by addressing the young people in the audience directly: “You are about to enter the greatest golden age,” he said.
-
“A lot of people working on AI pretend that it’s only going to be good; it’s only going to be a supplement; no one is ever going to be replaced,” he said. “Jobs are definitely going to go away, full stop.”
-
A recent study led by Ed Felten, a professor of information-technology policy at Princeton, mapped AI’s emerging abilities onto specific professions according to the human abilities they require, such as written comprehension, deductive reasoning, fluency of ideas, and perceptual speed. Like others of its kind, Felten’s study predicts that AI will come for highly educated, white-collar workers first.
-
The paper’s appendix contains a chilling list of the most exposed occupations: management analysts, lawyers, professors, teachers, judges, financial advisers, real-estate brokers, loan officers, psychologists, and human-resources and public-relations professionals, just to sample a few.
-
Altman imagines that far better jobs will be created in their place. “I don’t think we’ll want to go back,” he said. When I asked him what these future jobs might look like, he said he doesn’t know.
-
He suspects there will be a wide range of jobs for which people will always prefer a human. (Massage therapists?
-
His chosen example was teachers. I found this hard to square with his outsize enthusiasm for AI tutors.
-
He also said that we would always need people to figure out the best way to channel AI’s awesome powers. “That’s going to be a super-valuable skill,” he said. “You have a computer that can do anything; what should it go do?”
-
As many have noted, draft horses were permanently put out of work by the automobile. If Hondas are to horses as GPT-10 is to us, a whole host of long-standing assumptions may collapse.
-
Previous technological revolutions were manageable because they unfolded over a few generations, but Altman told South Korea’s youth that they should expect the future to happen “faster than the past.” He has previously said that he expects the “marginal cost of intelligence” to fall very close to zero within 10 years
-
The earning power of many, many workers would be drastically reduced in that scenario. It would result in a transfer of wealth from labor to the owners of capital so dramatic, Altman has said, that it could be remedied only by a massive countervailing redistribution.
-
In 2021, he unveiled Worldcoin, a for-profit project that aims to securely distribute payments—like Venmo or PayPal, but with an eye toward the technological future—first through creating a global ID by scanning everyone’s iris with a five-pound silver sphere called the Orb. It seemed to me like a bet that we’re heading toward a world where AI has made it all but impossible to verify people’s identity and much of the population requires regular UBI payments to survive. Altman more or less granted that to be true, but said that Worldcoin is not just for UBI.
-
“Let’s say that we do build this AGI, and a few other people do too.” The transformations that follow would be historic, he believes. He described an extraordinarily utopian vision, including a remaking of the flesh-and-steel world
-
“Robots that use solar power for energy can go and mine and refine all of the minerals that they need, that can perfectly construct things and require no human labor,” he said. “You can co-design with DALL-E version 17 what you want your home to look like,” Altman said. “Everybody will have beautiful homes.
-
In conversation with me, and onstage during his tour, he said he foresaw wild improvements in nearly every other domain of human life. Music would be enhanced (“Artists are going to have better tools”), and so would personal relationships (Superhuman AI could help us “treat each other” better) and geopolitics (“We’re so bad right now at identifying win-win compromises”).
-
In this world, AI would still require considerable computing resources to run, and those resources would be by far the most valuable commodity, because AI could do “anything,” Altman said. “But is it going to do what I want, or is it going to do what you want
-
If rich people buy up all the time available to query and direct AI, they could set off on projects that would make them ever richer, while the masses languish
-
One way to solve this problem—one he was at pains to describe as highly speculative and “probably bad”—was this: Everyone on Earth gets one eight-billionth of the total AI computational capacity annually. A person could sell their annual share of AI time, or they could use it to entertain themselves, or they could build still more luxurious housing, or they could pool it with others to do “a big cancer-curing run,” Altman said. “We just redistribute access to the system.”
-
Even if only a little of it comes true in the next 10 or 20 years, the most generous redistribution schemes may not ease the ensuing dislocations.
-
America today is torn apart, culturally and politically, by the continuing legacy of deindustrialization, and material deprivation is only one reason. The displaced manufacturing workers in the Rust Belt and elsewhere did find new jobs, in the main. But many of them seem to derive less meaning from filling orders in an Amazon warehouse or driving for Uber than their forebears had when they were building cars and forging steel—work that felt more central to the grand project of civilization.
-
It’s hard to imagine how a corresponding crisis of meaning might play out for the professional class, but it surely would involve a great deal of anger and alienation.
-
Even if we avoid a revolt of the erstwhile elite, larger questions of human purpose will linger. If AI does the most difficult thinking on our behalf, we all may lose agency—at home, at work (if we have it), in the town square—becoming little more than consumption machines, like the well-cared-for human pets in WALL-E
-
Altman has said that many sources of human joy and fulfillment will remain unchanged—basic biological thrills, family life, joking around, making things—and that all in all, 100 years from now, people may simply care more about the things they cared about 50,000 years ago than those they care about today
-
In its own way, that too seems like a diminishment, but Altman finds the possibility that we may atrophy, as thinkers and as humans, to be a red herring. He told me we’ll be able to use our “very precious and extremely limited biological compute capacity” for more interesting things than we generally do today.
-
Yet they may not be the most interesting things: Human beings have long been the intellectual tip of the spear, the universe understanding itself. When I asked him what it would mean for human self-conception if we ceded that role to AI, he didn’t seem concerned. Progress, he said, has always been driven by “the human ability to figure things out.” Even if we figure things out with AI, that still counts, he said.
-
It’s not obvious that a superhuman AI would really want to spend all of its time figuring things out for us.
-
I asked Sutskever whether he could imagine an AI pursuing a different purpose than simply assisting in the project of human flourishing.
-
Sutskever has recently shifted his focus to try to make sure that it doesn’t. He is now working primarily on alignment research, the effort to ensure that future AIs channel their “tremendous” energies toward human happiness
-
It is, he conceded, a difficult technical problem—the most difficult, he believes, of all the technical challenges ahead.
-
As part of the effort to red-team GPT-4 before it was made public, the company sought out the Alignment Research Center (ARC), across the bay in Berkeley, which has developed a series of evaluations to determine whether new AIs are seeking power on their own. A team led by Elizabeth Barnes, a researcher at ARC, prompted GPT-4 tens of thousands of times over seven months, to see if it might display signs of real agency.
-
Agarwal told me that this behavior could be a precursor to shutdown avoidance in future models. When GPT-4 devised its lie, it had realized that if it answered honestly, it may not have been able to achieve its goal. This kind of tracks-covering would be particularly worrying in an instance where “the model is doing something that makes OpenAI want to shut it down,” Agarwal said. An AI could develop this kind of survival instinct while pursuing any long-term goal—no matter how small or benign—if it feared that its goal could be thwarted.
-
Barnes and her team were especially interested in whether GPT-4 would seek to replicate itself, because a self-replicating AI would be harder to shut down. It could spread itself across the internet, scamming people to acquire resources, perhaps even achieving some degree of control over essential global systems and holding human civilization hostage.
-
When I discussed these experiments with Altman, he emphasized that whatever happens with future models, GPT-4 is clearly much more like a tool than a creature. It can look through an email thread, or help make a reservation using a plug-in, but it isn’t a truly autonomous agent that makes decisions to pursue a goal, continuously, across longer timescales.
-
Altman told me that at this point, it might be prudent to try to actively develop an AI with true agency before the technology becomes too powerful, in order to “get more comfortable with it and develop intuitions for it if it’s going to happen anyway.”
-
“We need to do empirical experiments on how these things try to escape control,” Hinton told me. “After they’ve taken over, it’s too late to do the experiments.”
-
the fulfillment of Altman’s vision of the future will at some point require him or a fellow traveler to build much more autonomous AIs.
-
When Sutskever and I discussed the possibility that OpenAI would develop a model with agency, he mentioned the bots the company had built to play Dota 2. “They were localized to the video-game world,” Sutskever told me, but they had to undertake complex missions. He was particularly impressed by their ability to work in concert. They seem to communicate by “telepathy,” Sutskever said. Watching them had helped him imagine what a superintelligence might be like.
-
“The way I think about the AI of the future is not as someone as smart as you or as smart as me, but as an automated organization that does science and engineering and development and manufacturing,”
-
Suppose OpenAI braids a few strands of research together, and builds an AI with a rich conceptual model of the world, an awareness of its immediate surroundings, and an ability to act, not just with one robot body, but with hundreds or thousands. “We’re not talking about GPT-4. We’re talking about an autonomous corporation,”
-
Its constituent AIs would work and communicate at high speed, like bees in a hive. A single such AI organization would be as powerful as 50 Apples or Googles, he mused. “This is incredible, tremendous, unbelievably disruptive power.”
-
Presume for a moment that human society ought to abide the idea of autonomous AI corporations. We had better get their founding charters just right. What goal should we give to an autonomous hive of AIs that can plan on century-long time horizons, optimizing billions of consecutive decisions toward an objective that is written into their very being?
-
If the AI’s goal is even slightly off-kilter from ours, it could be a rampaging force that would be very hard to constrain
-
We know this from history: Industrial capitalism is itself an optimization function, and although it has lifted the human standard of living by orders of magnitude, left to its own devices, it would also have clear-cut America’s redwoods and de-whaled the world’s oceans. It almost did.
-
We can program a goal into an AI and reinforce it with a temporary period of supervised learning, Sutskever explained. But just as when we rear a human intelligence, our influence is temporary. “It goes off to the world,”
-
He compared a powerful AI to an 18-year-old heading off to college. How will we know that it has understood our teachings? “Will there be a misunderstanding creeping in, which will become larger and larger?”
-
Divergence may result from an AI’s misapplication of its goal to increasingly novel situations as the world changes
-
Or the AI may grasp its mandate perfectly, but find it ill-suited to a being of its cognitive prowess. It might come to resent the people who want to train it to, say, cure diseases. “They want me to be a doctor,” Sutskever imagines an AI thinking. “I really want to be a YouTuber.”
-
If AIs get very good at making accurate models of the world, they may notice that they’re able to do dangerous things right after being booted up. They might understand that they are being red-teamed for risk, and hide the full extent of their capabilities.
-
We would not even realize that we had created something that had decisively surpassed us, and we would have no sense for what it intended to do with its superhuman powers.
-
That’s why the effort to understand what is happening in the hidden layers of the largest, most powerful AIs is so urgent. You want to be able to “point to a concept,” Sutskever said. You want to be able to direct AI toward some value or cluster of values, and tell it to pursue them unerringly for as long as it exists.
-
we don’t know how to do that; indeed, part of his current strategy includes the development of an AI that can help with the research. If we are going to make it to the world of widely shared abundance that Altman and Sutskever imagine, we have to figure all this out.
-
This is why, for Sutskever, solving superintelligence is the great culminating challenge of our 3-million-year toolmaking tradition. He calls it “the final boss of humanity.”
-
“First of all, I think that whether the chance of existential calamity is 0.5 percent or 50 percent, we should still take it seriously,”
-
As to how it might happen, he seems most worried about AIs getting quite good at designing and manufacturing pathogens, and with reason: In June, an AI at MIT suggested four viruses that could ignite a pandemic, then pointed to specific research on genetic mutations that could make them rip through a city more quickly
-
Around the same time, a group of chemists connected a similar AI directly to a robotic chemical synthesizer, and it designed and synthesized a molecule on its own.
-
Altman worries that some misaligned future model will spin up a pathogen that spreads rapidly, incubates undetected for weeks, and kills half its victims. He worries that AI could one day hack into nuclear-weapons systems too. “There are a lot of things,” he said, and these are only the ones we can imagine.
-
Altman told me that he doesn’t “see a long-term happy path” for humanity without something like the International Atomic Energy Agency for global oversight of AI
-
In San Francisco, Agarwal had suggested the creation of a special license to operate any GPU cluster large enough to train a cutting-edge AI, along with mandatory incident reporting when an AI does something out of the ordinary
-
Other experts have proposed a nonnetworked “Off” switch for every highly capable AI; on the fringe, some have even suggested that militaries should be ready to perform air strikes on supercomputers in case of noncompliance
-
Sutskever thinks we will eventually want to surveil the largest, most powerful AIs continuously and in perpetuity, using a team of smaller overseer AIs.
-
Safety rules for a new technology usually accumulate over time, like a body of common law, in response to accidents or the mischief of bad actors. The scariest thing about genuinely powerful AI systems is that humanity may not be able to afford this accretive process of trial and error. We may have to get the rules exactly right at the outset.
-
Several years ago, Altman revealed a disturbingly specific evacuation plan he’d developed. He told The New Yorker that he had “guns, gold, potassium iodide, antibiotics, batteries, water, gas masks from the Israeli Defense Force, and a big patch of land in Big Sur” he could fly to in case AI attacks.
-
but he told me that he can’t really be sure how AI will stack up. “I just have to build the thing,” he said. He is building fast
-
Altman insisted that they had not yet begun GPT-5’s training run. But when I visited OpenAI’s headquarters, both he and his researchers made it clear in 10 different ways that they pray to the god of scale. They want to keep going bigger, to see where this paradigm leads. After all, Google isn’t slackening its pace; it seems likely to unveil Gemini, a GPT-4 competitor, within months. “We are basically always prepping for a run,
-
To think that such a small group of people could jostle the pillars of civilization is unsettling. It’s fair to note that if Altman and his team weren’t racing to build an artificial general intelligence, others still would be
-
Altman’s views about the likelihood of AI triggering a global class war, or the prudence of experimenting with more autonomous agent AIs, or the overall wisdom of looking on the bright side, a view that seems to color all the rest—these are uniquely his
-
No single person, or single company, or cluster of companies residing in a particular California valley, should steer the kind of forces that Altman is imagining summoning.
-
AI may well be a bridge to a newly prosperous era of greatly reduced human suffering. But it will take more than a company’s founding charter—especially one that has already proved flexible—to make sure that we all share in its benefits and avoid its risks. It will take a vigorous new politics.
-
I don’t think the general public has quite awakened to what’s happening. A global race to the AI future has begun, and it is largely proceeding without oversight or restraint. If people in America want to have some say in what that future will be like, and how quickly it arrives, we would be wise to speak up soon.
71More
shared by Javier E on 16 Nov 23
- No Cached
Opinion | With Covid, Is It Really Possible to Say We Went Too Far? - The New York Times - 0 views
www.nytimes.com/...covid-lockdown-failure.html
covid response backlash revisionist history crisis culture policy
![](/images/link.gif)
-
In 2020, many Americans told themselves that all it would take to halt the pandemic was replacing the president and hitting the “science button.”
-
In 2023, it looks like we’re telling ourselves the opposite: that if we were given the chance to run the pandemic again, it would have been better just to hit “abort” and give up.
-
you can see it in Bethany McLean and Joe Nocera’s book “The Big Fail: What the Pandemic Revealed About Who America Protects and Who It Leaves Behind,” excerpted last month in New York magazine under the headline “Covid Lockdowns Were a Giant Experiment. It Was a Failure.”
- ...68 more annotations...
-
we can’t simply replace one simplistic narrative, about the super power of mitigation policy, for another, focused only on the burdens it imposed and not at all on the costs of doing much less — or nothing at all.
-
McLean: I think it gets at things that had happened in America even before the pandemic hit. And among those things were, I think, a failure to recognize the limits of capitalism, a failure of government to set the right rules for it, particularly when it comes to our health care system; a focus on profits that may have led to an increase in the bottom line but created fragility in ways people didn’t understand; and then our growing polarization that made us incapable of talking to each other
-
How big is the failure? When I look at The Economist’s excess mortality data, I see the U.S. had the 53rd-worst outcome in the world — worse than all of Western Europe, but better than all of Eastern Europe.
-
McLean: I think one way to quantify it is to take all those numbers and then put them in the context of our spending on health care. Given the amount we spend on health care relative to other countries, the scale of the failure becomes more apparent.
-
o me, the most glaring example is the schools. They were closed without people thinking through the potential consequences of closing down public schools, especially for disadvantaged kids.
-
to compound it, in my view, public health never made the distinction that needed to be made between the vulnerabilities of somebody 70 years old and the vulnerabilities of somebody 10 years old.
-
In the beginning of the book you write, in what almost feels like a thesis statement for the book: “A central tenet of this book is that we could not have done better, and pretending differently is a dangerous fiction, one that prevents us from taking a much needed look in the mirror.”
-
This claim, that the U.S. could not have done any better, runs against your other claim, that what we observed was an American failure. It is also a pretty extreme claim, I think, and I wanted to press you on it in part because it is, in my view, undermined by quite a lot of the work you do in the book itself.
-
Would the U.S. not have done better if it had recognized earlier that the disease spread through the air rather than in droplets? Would it not have done better if it hadn’t bungled the rollout of a Covid test in the early months?
-
McLean: Everything that you mentioned — the point of the book is that those were set by the time the pandemic hit.
-
in retrospect, what we were doing was to try to delay as much spread as we could until people got vaccinated. All the things that we did in 2020 were functionally serving or trying to serve that purpose. Now, given that, how can you say that none of that work saved lives?
-
But the big question I really want to ask is this one: According to the C.D.C., we’ve had almost 1.2 million deaths from Covid. Excess mortality is nearly 1.4 million. Is it really your contention that there was nothing we might’ve done that brought that total down to 1.1 million, for instance, or even 900,000?
-
McLean: It’s very — you’re right. If you went through each and every thing and had a crystal ball and you could say, this could have been done, this could have been moved up by a month, we could have gotten PPE …
-
When I came to that sentence, I thought of it in terms of human behavior: What will humans put up with? What will humans stand for? How do Americans act? And you’ve written about Sweden being sort of average, and you’ve written about China and the Chinese example. They lock people up for two years and suddenly the society just revolts. They will not take it anymore. They can’t stand it. And as a result, a million and a half people die in a month and a half.
-
Well, I would tell that story very differently. For me, the problem is that when China opened up, they had fully vaccinated just under two-thirds of their population over 80. So to me, it’s not a failure of lockdowns. It’s a failure of vaccinations. If the Chinese had only achieved the same elderly vaccination rate as we achieved — which by global standards was pretty poor — that death toll when they opened up would have been dramatically lower.
-
What do you mean by “lockdown,” though? You use the word throughout the book and suggest that China was the playbook for all countries. But you also acknowledge that what China did is not anything like what America did.
-
Disparities in health care access — is it a dangerous fiction to think we might address that? You guys are big champions of Operation Warp Speed — would it not have been better if those vaccines had been rolled out to the public in nine months, rather than 12
-
. But this isn’t “lockdown” like there were lockdowns in China or even Peru. It’s how we tried to make it safer to go out and interact during a pandemic that ultimately killed a million Americans.
-
McLean: I think that you’re absolutely right to focus on the definition of what a lockdown is and how we implemented them here in this country. And I think part of the problem is that we implemented them in a way that allowed people who were well off and could work from home via Zoom to be able to maintain very much of their lives while other people couldn’t
-
And I think it depends on who you were, whether you would define this as a lockdown or not. If you were a small business who saw your small business closed because of this, you’re going to define it as a lockdown.
-
n the book you’re pretty definitive. You write, “maybe the social and economic disasters that lockdowns created would have been worth it if they had saved lives, but they hadn’t.” How can you say that so flatly?
-
I think there are still open questions about what worked and how much. But the way that I think about all of this is that the most important intervention that anybody did anywhere in the world was vaccination. And the thing that determined outcomes most was whether your first exposure came before or after vaccination.
-
Here, the shelter-in-place guidelines lasted, on average, five to seven weeks. Thirty nine of the 40 states that had issued them lifted them by the end of June, three months in. By the summer, according to Google mobility data, retail and grocery activity was down about 10 percent. By the fall, grocery activity was only down about 5 percent across the country
-
Nocera: Well, on some level, I feel like you’re trying to have it both ways. On the one hand, you’re saying that lockdowns saved lives. On the other hand, you said they weren’t real lockdowns because everybody was out and about.
-
I don’t think that’s having it both ways. I’m trying to think about these issues on a spectrum rather than in binaries. I think we did interrupt our lives — everybody knows that. And I think they did have an effect on spread, and that limiting spread had an effect by delaying infections until after vaccination.
-
Nocera: Most of the studies that say lockdowns didn’t work are really less about Covid deaths than about excess mortality deaths. I wound up being persuaded that the people who could not get to the hospital, because they were all working, because all the doctors were working on Covid and the surgical rooms were shut down, the people who caught some disease that was not Covid and died as a result — I wound up being persuaded about that.
-
We’re in a pandemic. People are going to die. And then the question becomes, can we protect the most vulnerable? And the answer is, we didn’t protect the most vulnerable. Nursing homes were a complete disaster.
-
There was a lot of worry early on about delayed health care, and about cancer in particular — missed screenings, missed treatments. But in 2019, we had an estimated 599,600 Americans die of cancer. In 2020, it was 602,000. In 2021, it was 608,000. In 2022, it was 609,000.
-
Nocera: See, it went up!But by a couple of thousand people, in years in which hundreds of thousands of Americans were dying of Covid.
-
Nocera: I think you can’t dispute the excess mortality numbers.I’m not. But in nearly every country in the world the excess mortality curves track so precisely with Covid waves that it doesn’t make sense to talk about a massive public health problem beyond Covid. And when you add all of these numbers up, they are nowhere near the size of the footfall of Covid. How can you look back on this and say the costs were too high?
-
Nocera: I think the costs were too high because you had school costs, you had economic costs, you had social costs, and you had death.
-
McLean: I think you’re raising a really good point. We’re making an argument for a policy that might not have been doable given the preconditions that had been set. I’m arguing that there were these things that had been put in place in our country for decades leading up to the pandemic that made it really difficult for us to plant in an effective way, from the outsourcing of our PPE to the distrust in our health care system that had been created by people’s lack of access to health care with the disparities in our hospital system.
-
How would you have liked to see things handled differently?Nocera: Well, the great example of doing it right is San Fran
-
I find the San Francisco experience impressive, too. But it was also a city that engaged in quite protracted and aggressive pandemic restrictions, well beyond just protecting the elderly and vulnerable.
-
McLean: But are we going to go for stay-at-home orders plus protecting vulnerable communities like San Francisco did? Or simply letting everybody live their lives, but with a real focus on the communities and places like nursing homes that were going to be affected? My argument is that we probably would’ve been better off really focusing on protecting those communities which were likely to be the most severely affected.
-
I agree that the public certainly didn’t appreciate the age skew, and our policy didn’t reflect it either. But I also wonder what it would mean to better protect the vulnerable than we did. We had testing shortages at first. Then we had resistance to rapid testing. We had staff shortages in nursing homes.
-
Nocera: This gets exactly to one of our core points. We had spent 30 years allowing nursing homes to be owned by private equity firms that cut the staff, that sold the land underneath and added all this debt on
-
I hear you saying both that we could have done a much better job of protecting these people and that the systems we inherited at the outset of the pandemic would’ve made those measures very difficult, if not impossible, to implement.
-
But actually, I want to stop you there, because I actually think that that data tells the opposite story.
-
And then I’m trying to say at the same time, but couldn’t we have done something to have protected people despite all of that?
-
I want to talk about the number of lives at stake. In the book, you write about the work of British epidemiologist Neil Ferguson. In the winter of 2020, he says that in the absence of mitigation measures and vaccination, 80 percent of the country is going to get infected and 2.2 million Americans are going to die. He says that 80 percent of the U.K. would get infected, and 510,000 Brits would die — again, in the abs
-
In the end, by the time we got to 80 percent of the country infected, we had more than a million Americans die. We had more than 200,000 Brits die. And in each case most of the infections happened after vaccination, which suggests that if those infections had all happened in a world without vaccines, we almost certainly would have surpassed two million deaths in the U.S. and almost certainly would’ve hit 500,000 deaths in the U.K.
-
In the book, you write about this estimate, and you endorse Jay Bhattacharya’s criticism of Ferguson’s model. You write, “Bhattacharya got his first taste of the blowback reserved for scientists who strayed from the establishment position early. He co-wrote an article for The Wall Street Journal questioning the validity of the scary 2 to 4 percent fatality rate that the early models like Neil Ferguson’s were estimating and that were causing governments to panic. He believed, correctly as it turns out, that the true fatality rate was much lower.”
-
Nocera: I know where you’re going with this, because I read your story about the nine pandemic narratives we’re getting wrong. In there, you said that Bhattacharya estimated the fatality rate at 0.01 percent. But if you actually read The Wall Street Journal article, what he’s really saying is I think it’s much lower. I’ve looked at two or three different possibilities, and we really need some major testing to figure out what it actually is, because I think 2 percent to 4 percent is really high.
-
He says, “if our surmise of 6 million cases is accurate, that’s a mortality rate of 0.01%. That is ⅒th the flu mortality rate of 0.1%.” An I.F.R. of 0.01 percent, spread fully through the American population, yields a total American death toll of 33,000 people. We have had 1.2 million deaths. And you are adjudicating this dispute, in 2023, and saying that Neil was wrong and Jay was right.
-
hird, in the Imperial College report — the one projecting two million American deaths — Ferguson gives an I.F.R. estimate of 0.9 percent.
-
Bhattacharya’s? Yes, there is some uncertainty around the estimate he offers. But the estimate he does offer — 0.01 percent — is one hundred times lower than the I.F.R. you yourselves cite as the proper benchmark.
-
Nocera: In The Wall Street Journal he does not say it’s 0.01. He says, we need to test to find out what it is, but it is definitely lower than 2 to 4 percent.
-
Well, first of all, the 2 percent to 4 percent fatality rate is not from Neil Ferguson. It’s from the W.H.O.
-
But I think that fundamentally, at the outset of the pandemic, the most important question orienting all of our thinking was, how bad could this get? And it turns out that almost all of the people who were saying back then that we shouldn’t do much to intervene were extremely wrong about how bad it would be
-
The argument then was, more or less, “We don’t need to do anything too drastic, because it’s not going to be that big a deal.” Now, in 2023, it’s the opposite argument: “We shouldn’t have bothered with restrictions, because they didn’t have an impact; we would have had this same death toll anyway.” But the death toll turned out to be enormous.
-
Now, if we had supplied all these skeptics with the actual numbers at the outset of the pandemic, what kind of audience would they have had? If instead of making the argument against universal mitigation efforts on the basis of a death toll of 40,000 they had made the argument on the basis of a death toll of more than a million, do you think the country would’ve said, they’re right, we’re doing too much, let’s back off?
-
McLean: I think that if you had gone to the American people and said, this many people are going to die, that would’ve been one thing. But if you had gone to the American people and said, this many people are going to die and a large percentage of them are going to be over 80, you might’ve gotten a different answer.
-
I’m not arguing we shouldn’t have been trying to get a clearer sense of the true fatality rate, or that we shouldn’t have been clearer about the age skew. But Bhattacharya was also offering an estimate of fatality rate that turned out to be off by a factor of a hundred from the I.F.R. that you yourselves cite as correct. And then you say that Bhattacharya was right and Ferguson was wrong.
-
And you, too, Joe, you wrote an article in April expressing sympathy for Covid skeptics and you said ——Nocera: This April?No, 2020.Nocera: Oh, oh. That’s the one where I praised Alex Berenson.You also cited some Amherst modeling which said that we were going to have 67,000 to 120,000 American deaths. We already had, at that point, 60,000. So you were suggesting, in making an argument against pandemic restrictions, that the country as a whole was going to experience between 7,000 and 60,000 additional deaths from that point.
-
when I think about the combination of the economic effects of mitigation policies and just of the pandemic itself and the big fiscal response, I look back and I think the U.S. managed this storm relatively well. How about each of you?
-
in this case, Congress did get it together and did come to the rescue. And I agree that made a ton of difference in the short term, but the long-term effects of the fiscal rescue package were to help create inflation. And once again, inflation hits those at the bottom of the socioeconomic distribution much harder than it does those at the top. So I would argue that some of what we did in the pandemic is papering over these long-term issues.
-
I think as with a lot of the stuff we’ve talked about today, I agree with you about the underlying problems. But if we take for granted for a moment that the pandemic was going to hit us, when it did, under the economic conditions it did, and then think about the more narrow context of whether, given all that, we handled the pandemic well. We returned quickly to prepandemic G.D.P. trends, boosted the wealth of the bottom half of the country, cut child poverty in half, pushed unemployment to historical lows.
-
What sense do you make of the other countries of the world and their various mitigation policies? Putting aside China, there’s New Zealand, Australia, South Korea — these are all places that were much more aggressive than the U.S. and indeed more than Europe. And had much, much better outcomes.
-
Nocera: To be perfectly honest, we didn’t really look, we didn’t really spend a lot of time looking at that.
-
McLean: But one reason that we didn’t is I don’t think it tells us anything. When you look at who Covid killed, then you have to look at what the pre-existing conditions in a country were, what percentage of its people are elderly. How sick are people with pre-existing conditions?
-
I just don’t think there’s a comparison. There’s just too many factors that influence it to be able to say that, to be able to compare America to any other country, you’d have to adjust for all these factors.
-
But you do spend a bit of time in the book talking about Sweden. And though it isn’t precisely like-for-like, one way you can control for some of those factors is grouping countries with their neighbors and other countries with similar profiles. And Sweden’s fatality rate in 2020 was 10 times that of Norway, Finland and Iceland. Five times that of Denmark. In the vaccination era, those gaps have narrowed, but by most metrics Sweden has still done worse, overall, than all of those countries.
-
On the matter of omniscience. Let’s say that we can send you back in time. Let’s put you both in charge of American pandemic response, or at least American communication about the pandemic, in early 2020. What would you want to tell the country? How would you have advised us to respond?
-
McLean: What I would want is honesty and communication. I think we’re in a world that is awash in information and the previous methods of communication — giving a blanket statement to people that may or may not be true, when you know there’s nuance underneath it — simply doesn’t work anymore
-
o I would’ve been much more clear — we think masks might help, we don’t know, but it’s not that big of an ask, let’s do it. We think the early data coming out of Italy shows that these are the people who are really, really at risk from Covid, but it’s not entirely clear yet. Maybe there is spread in schools, but we don’t know. Let’s look at this and keep an open mind and look at the data as it comes in.
6More
#Frisco5 protest: US 'police racism' hunger strike ends in San Francisco - BBC News - 0 views
-
Dubbed the Frisco Five, they accuse Greg Suhr of heading a racist force following the shootings by officers of three men from ethnic minority groups.
-
They said their cause would be better served by "staying and fighting" than by "starving and dying".
- ...3 more annotations...
-
A statement on the Hunger For Justice #Frisco5 Facebook page said that "the whole community" had asked for Sellassie Blackwell, Ilyich Sato, Edwin Lindo, Maria Cristina Gutierrez and Ike Pinkston to end their hunger strike on Saturday so they could "return to the front lines and help shape this movement and the pursuit of justice for the black and brown citizens of San Francisco".
-
Ed Lee was not in his office, but spoke to the hunger strikers by phone on Thursday, saying he had no plans to fire Mr Suhr.
-
There are more than 1,000 fatal shootings by police in the US each year, and those killed are disproportionately African-American.