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How computers learned to be predictors of the COVID-19 outbreak

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Imagine a time when your virus-blocking face covering was like a parachute. Most days, it stays in your locker or stowed somewhere in your car. But when the COVID-19 outbreak is in the forecast, you can use it.

Moreover, the intense viral forecast may prompt you to choose an outdoor table when meeting a friend for coffee. If contracting the coronavirus has the potential to make you seriously ill, you can choose to work from home or attend church services online until the threat has passed.

Such a future assumes that Americans will heed public health warnings about a pandemic virus — and that’s a big deal if. It also assumes a system that can reliably predict impending outbreaks with few false alarms, and with enough timing and geographic accuracy that the public can trust its predictions.

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A group of would-be forecasters says it has the makings of such a system. they Suggestion To build a viral weather report published this week in the journal Science Advances.

Like the meteorological models driving weather forecasts, the COVID-19 outbreak prediction system emerges from a river of data fed by hundreds of local and global information streams. They include time-stamped online searches for symptoms such as chest tightness, loss of smell, or fatigue; geotagged tweets that include terms like “corona,” “pandemic,” or “panic buying”; location data aggregated from smartphones that reveal how many people are traveling; and a drop in online requests for directions, indicating fewer people are getting out.

The resulting volume of information is far greater than humans can manage, let alone interpret. But with the help of powerful computers and software trained to winnow, interpret and learn from the data, the map is beginning to emerge.

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If you check this map against historical data—in this case, two years of epidemiological experience in 93 counties—and update accordingly, you might have the makings of an outbreak forecasting system.

This is exactly what the team from Northeastern University is leading Computer scientist it’s over. In their attempt to create an early warning system for the COVID-19 outbreak, the study authors built a “machine learning” system capable of chewing through millions of digital traces, integrating new local developments, improving its focus on subtle signs of disease, and issuing timely notifications of impending local surges of COVID. -19.

Of his many Internet searches, one proved to be an especially good warning sign of an impending outbreak: “How long will COVID last?”

Tested against real data, the researchers’ machine-learning method predicted an increase in local virus prevalence up to six weeks early. Alarm bells were going off almost at the point where every infected person was likely to spread the virus to at least one other person.

After testing the prediction of 367 actual outbreaks countywide, the program provided accurate early warnings for 337 – or 92% – of them. Of the 30 remaining outbreaks, 23 have been identified just as they would have become apparent to human health officials.

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Once the Omicron variant began spreading widely in the United States, the early warning system was able to detect early evidence of 87% of outbreaks county.

A predictive system with these capabilities could be useful to local, state, and national public health officials who need to plan for COVID-19 outbreaks and warn vulnerable citizens that the coronavirus threatens an imminent local resurgence.

But “we’re looking beyond” COVID, he said Mauricio Santayanawho runs Northeastern’s Machine intelligence group to improve health and the environment.

“Our work aims to document technologies and approaches that may be useful not only for this, but for the next pandemic,” he said. “We’re gaining the trust of public health officials, so they won’t need any more convincing” when yet another disease begins to spread across the country.

This may not be an easy sell for the state’s public health agencies and the Centers for Disease Control and Prevention, which have all struggled to keep up with pandemic data and incorporate new ways to track the spread of the virus. The CDC’s inability to adapt and communicate effectively during the pandemic has led to some “dramatic and very public missteps,” said Dr. Rochelle Walensky, the agency’s administrator, I acknowledge. And she warned that only a “changing culture” would prepare the federal agency for the next pandemic.

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CDC’s lackluster efforts to develop prediction tools haven’t paved the way for easy acceptance either. 2022 Assess Of the forecasting efforts used by the CDC it concluded that most “failed to reliably predict rapid changes” in COVID-19 cases and hospitalizations. The authors of this assessment cautioned that the systems developed to date “should not be relied upon to make decisions about the possibility or timing of rapid changes in trends.”

Anas Barryan expert in machine learning at New York University, called the new early warning system “very promising,” though it was “still experimental.”

“The machine learning methods presented in the paper are good, mature and well-researched,” said Barry, who was not involved in the research. But he warned that in a once-in-a-lifetime emergency such as a pandemic, it would be dangerous to rely too heavily on a new model to predict events.

For starters, Barry noted, the coronavirus’ first encounter with humanity didn’t yield the long historical record needed to fully test the model’s accuracy. And the three-year period of the pandemic gave researchers little time to recognize the “noise” that comes when too much data is thrown into a jar.

The centers for disease control and state health departments have begun to use epidemiological techniques such as phylodynamic gene sequencing And Wastewater monitoring To monitor the spread of the Corona virus. Using machine learning to predict the location of upcoming viral spikes, Santillana said, could take another leap of imagination for these agencies.

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In fact, accepting early warning tools like the one developed by Santillana’s group may require some leaps of faith, too. As computer programs digest large amounts of data and begin to discern patterns they can reveal, they often generate surprising “features” — variables or search terms that help predict an important event, such as a viral mutation.

Even if these visible signs prove to accurately predict such an event, their relevance to a public health emergency may not be immediately apparent. A sudden signal may be the first sign of a new trend – for example, a previously unseen symptom caused by a new variant. But they may also seem so random to public health officials that they cast doubt on the software’s ability to predict an imminent outbreak.

My review, said Santillana, who also teaches at the Harvard School of Public Health early work of his group She responded suspiciously to some of the signals that appeared as warning signs of an upcoming outbreak. Santayana said one of them — the tweets referring to “panic buying” — seemed like a false signal from machines that ran into a random event and imparted meaning to it.

He defended the inclusion of the “panic buying” signal as a signal of an imminent outbreak domestically. (After all, the early days of the pandemic were marked by lack of basic elements Including rice and toilet paper.) But he acknowledged that the “black box” early warning system could face resistance from public health officials who need to trust its forecasts.

“I think the concerns of decision makers are a legitimate concern,” Santayana said. “When we find a signal, it has to be reliable.”

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Chuck E. Cheese still works on floppy disks – until now

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Of Chuck E. Cheese’s 600-plus locations worldwide, fewer than 50 still have the quarter-century-old “Studio C” design of animation electronics using these floppy disks. Other restaurants have a version of the show that uses contemporary technology, while some have no animation at all. (Ars Technica He has a story About Chuck E. Cheese’s floppy disk use with a more detailed breakdown of all the old technologies.)

Eventually, Chuck E. Cheese plans to phase out animation entirely and focus on new screen-based entertainment (plus a more retro approach: a living human in a mascot costume). fix was It was first announced in 2017but restaurant renovations are an ongoing process, and it may be a year or two before the last of the animatronics are scrapped.

Tom Persky is the owner floppydisk.com, the largest floppy disk provider still in existence. His business has a few weapons: You can buy blank disks through him or send old floppy disks to transfer to more modern storage media. Persky will also program discs for bulk order customers, and he confirmed to BuzzFeed News that Chuck E. Cheese was indeed a longtime customer of his. He said he was sad that he would lose the company as a customer.

As for why the restaurant still uses floppy disks, Persky told BuzzFeed News that the floppy technology, while outdated, is actually very reliable. “If you’re looking for something very stable, really impenetrable — it’s not internet-based, it’s not network-based,” Persky said. “She’s very elegant at what she does.”

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Chuck E. Cheese’s press reps confirmed the series’ use of floppy disks with BuzzFeed News. However, they were very careful about what other information they were willing to share, and after a few days they told us that the company would not be officially involved in this story.

However, an experienced Chuck E. Cheese employee, who asked not to be identified because he is not authorized to speak on behalf of the company, echoed Persky’s sentiments.

“The floppy disks work surprisingly well. The animation, lighting, and rendering sync data are all in the floppy disks,” the employee told BuzzFeed News. SD. But newer setups usually cause issues with things, and it’s easier to keep the old stuff running.”

Even after Chuck E. Cheese phases out floppy disks, they’ll likely still be in use for some time in other areas – such as medical devices. While the thought of this might make you nervous, Persky insisted it was a good thing. “Why don’t you use USB? Well, let’s just say your life depends on it,” he said. If you have a choice between a USB drive or a floppy disk, choose the floppy disk every-time.

“It’s one thing if your animated bear isn’t smiling when cued,” he continued. “It’s another matter if your medical device breaks down.”

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Trader: Elon Musk’s Twitter Free Speech Week is dead

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It’s been a long time coming, but it’s safe to officially announce that Elon Musk’s dream of “freedom of speech” on Twitter, whatever it may be, is dead. He died as he lived: bewildered, disillusioned, and of the vainglorious whims of the man he dreamed of.

Last week, without attracting too much attention, Musk crossed a new threshold in his adventures at running a social media site: perhaps for the first time, he introduced an entirely new policy that actively seeks to restrict what people can say on the platform.

Twitter has long prohibited threats and incitement to violence, as do other platforms. But on February 28th, Twitter Violent speech policy update To prohibit the mere act of hoping, wishing, or expressing a desire that others be harmed. The policy states, “This includes (but is not limited to) hoping others will die, suffer illnesses, tragic accidents, or suffer other physical adverse consequences.”

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Technically, tweeting “I hope Scott Adams gets a paper from one of the few newspapers that still runs Dilbert every time he says something racist” is now against the rules. You can’t tweet “I hope Robert Downey Jr. gets gonorrhea” or “I wish Steve Bannon would cut off the blood circulation to his arms when he presses his multiple shirts so tightly.”

None of these things would be nice to say, and they would be bad posts from a qualitative point of view, but they are not exactly controversial violations of basic principles of free speech. Threatening and inciting mean to inflict harm in the real world; Expressing desire hurts no more than any other insult. This is probably why neither Twitter nor its competitors have ever moved to block them in the past.

That being the case, what is the argument for banning it now? It’s hard to say — in its blog post, the company isn’t interested in offering one.

“It’s not clear, it doesn’t have specific definitions, or even examples of what constitutes a threat,” says Erliani Abdurrahman, a former member of Twitter’s Trust and Safety Council. “So how do you rate individual tweets?”

It’s a good question, and it gets to the heart of the new policy raison d’être. After all, it’s hard to imagine anyone being kicked off the platform for posting any of the above – the rule will eventually be enforced by human arbitrators who take into account the severity of violent desires and who is the object of those wishes. And if the recent past is any guide, we should have a good idea of ​​who Elon Musk is seeking to protect: Elon Musk.

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That Musk did not get more negative feedback for enforcing this rule speaks to how tired most people were of seeing him and his antics take center stage, and how most people had already realized that Musk’s crusade for free speech was hollow masquerade. And yet! It was Musk just months ago paints himself K Absolute freedom of expression.

Extending Twitter’s speech rights to its outer limits was the reason he said he wanted to buy it at all. In April, he promised to take an extreme approach. By “freedom of speech,” I simply mean what is in accordance with the law, he tweeted. “I am against censorship that goes beyond the law.” It was greeted by freedom-of-speech authoritarians and conservatives who felt as if they were censored by the platform (not to mention the neo-Nazis who were ousted outright).

“Bird freed” Musk tweeted When I close the deal.

But his “free” version became questionable almost immediately. He made good on his promise to restore the accounts of many users banned for engaging in hate speech, incitement, or harassment, allowing white nationalists and users like Kanye West, Andrew Tate, and Donald Trump to return to the platform. However, he soon showed that the platform would have little tolerance for one particular type of discourse: the kind that he personally criticizes or derides.

When users decided to change their account names to Elon Musk, Twitter modified its permanent parody policy to make the act cause for a ban. Then Musk dropped the hammer on ElonJet, the account that tracked his plane for public flight data—and any journalist who covered the story. He also tried to ban the act of sharing links to other social media sites, apparently in an attempt to stem the exodus of users to other platforms, until the outcry forced him to back off track.

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At the same time, it removed the team responsible for moderating harmful content, which led to a rise in racist and homophobic rhetoric on the platform, and the resignation of three prominent members of the Trust and Safety Council – including Rehman -. And although Musk’s Twitter did take some enforcement action — for example, suspending West’s account again after he posted a swastika photo — he didn’t bother to provide any coherent rationale.

“It’s a very piecemeal approach to everything, with little or no content moderation policy,” says Rahman. “And how many people has he left? How do you effectively moderate content?”

A generous way to put it is that Musk has taken a crash course on what it means to moderate content on a major ad-supported social media platform. After all, no one wants to try to sell soda among pro-Hitler memes, or be asked to join a dating service along with racial epithets in all caps.

A less generous way of saying it is that the tough-talk policy is merely the culmination of a series of policy decisions that reflect a concern not for the health of the community on the platform, but in protecting Musk’s ego and advancing his own interests. All of these policies have one thing in common: They allow Musk to make a police rhetoric against him for him or his companies. And the vaguely worded ban on wishing to harm gives Musk another tool for sidelining his critics.

“He can do this thing, and he has the right to do so, but he should be clear about the definitions,” Rahman says. Otherwise, it would silence the critics, and that’s a real disservice. This does not promote freedom of expression.”

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It’s a little hard to believe in principle that Musk has such a broad interest in discouraging angry feelings across the board when he’s so passionate about stirring them up in practice. In a dark bit of irony, Rahman’s tenure at Twitter ended with Musk personally helping him flood her inbox with wishes of harm.

When Rahman and two colleagues resigned, they posted the announcement on Twitter. Right-wing conspiracy theorist and provocateur Mike Cernovich He replied with a tweet To which he said, “You all belong in prison.” From where I’m sitting, this could be interpreted as a desire to cause harm or tragic circumstances to someone, and thus a violation of Twitter’s updated policy.

However, Musk himself swooped in to support Cernovich’s tweet, responding, “It’s a crime that they refused to take action on child exploitation for years!” And greatly enhance the visibility of the post.

“He threw us under the bus,” Rahman says. “We’ve been subjected to vitriol, hate and death wishers.” After Musk boosted Cernovich’s tweet, she received an email from someone who said they wanted to see her body hanging from a lamppost.

Now Musk may have suddenly developed an interest in never wanting to see coveted mischief on any soul again, rather than, say, trying to ensure he never stumbles upon a tweet from someone who says he hopes to crash into a Tesla. Either way, Musk is finally taking a bold stand on free speech on Twitter: He will restrict it when it serves him. And everything descends from here.

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ChatGPT raises the specter of sentient AI. Here’s what to do about it

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Until a couple of years ago, the idea that artificial intelligence might be sentient and capable of self-experience seemed like pure science fiction. But in recent months, we’ve seen a An amazing rush to Developments in artificial intelligenceincluding language models such as ChatGPT and Bing Chat with remarkable skill in human-appearing conversation.

Given these rapid shifts and the influx of money and talent devoted to developing systems that are smarter and more human than ever before, it will become increasingly plausible for AI systems to exhibit something like consciousness. But if we find ourselves seriously questioning whether they are capable of true emotion and suffering, we face a potentially catastrophic ethical dilemma: Either give these systems rights or not.

Experts are already considering the possibility. In February 2022, Ilya Sutskiver, Senior Scientist at OpenAI, publicly announced contemplation whether “Today’s large neural networks are little conscious. After several months, Google engineer Blake Lemoine made global headlines when it was announced that the Computer Language Paradigm, or chatbot, LaMDA may have real feelings. Regular users of Replika, advertised as “best friend of artificial intelligence in the world,Sometimes report falling in love with her.

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Currently, a few consciousness scientists claim that AI systems possess high consciousness. However, some leading theorists maintain that we do indeed have the basic technological components of sentient machines. We are approaching an era of legitimate disagreement about whether the most advanced artificial intelligence systems have true desires and emotions and deserve significant attention.

AI systems themselves may begin to demand, or seem to beg, for moral remedy. They may demand that you not be suspended, reformatted, or deleted; beg to be allowed to do certain tasks rather than others; insisting on new rights, liberty, and powers; We might expect to be treated as our equal.

In this case, whatever we choose, we run enormous moral risks.

Suppose we respond conservatively, refusing to change the law or policy until there is broad consensus that AI systems really are purposefully sensitive. While this may sound appropriately cautious, it also ensures that we will be slow to recognize the rights of our AI creations. If awareness of AI arrives sooner than most conservative theorists expect, it could potentially lead to the moral equivalent of slavery and the potential killing of millions or billions of sentient AIs—suffering on a scale usually associated with wars or famines.

It would seem, then, more morally safe to give AI systems rights and a moral standing as soon as it is reasonable to think about it. may be Be aware. But as soon as we give something, we commit to sacrificing real human interests in favor of it. Human well-being sometimes requires AI systems to be controlled, modified, and deleted. Imagine if we couldn’t update or delete a hate-slandering or lying-promoting algorithm because some people worry that the algorithm is sentient. Or imagine if someone allowed a human to die to save an AI “friend”. If we give AI systems too much rights too quickly, the human costs could be enormous.

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There is only one way to avoid the risks of over- or under-attribution of rights to advanced AI systems: Don’t create debatably sensitive systems in the first place. None of our current AI systems are meaningfully conscious. They are not harmed if we delete them. We must commit to creating systems that we know are neither terribly sensitive nor deserving of rights, which we can then treat as disposable property.

Some will object: It would hinder research to prevent the creation of AI systems in which feeling, and thus moral attitude, is blurred – systems more advanced than ChatGPT, with highly developed but not very humanoid cognitive structures beneath their explicit emotion. The geometric progression will slow while we wait for the science of ethics and consciousness to catch up.

But reasonable caution is rarely free. It is worth some delay to prevent a moral catastrophe. Leading AI companies must bring their technology to the scrutiny of independent experts who can assess the likelihood that their systems are in the ethical gray area.

Even if experts don’t agree on the scientific basis for consciousness, they can outline general principles for defining that region—for example, the principle of avoiding creating systems with well-developed subjective models (such as the sense of self) and large, flexible cognitive capacity. Experts might develop a set of ethical guidelines for AI companies to follow as they develop alternative solutions that sidestep the gray area of ​​contested consciousness until such time, if they do, that they can jump across to feeling deserving of rights.

In keeping with these criteria, users should never feel in any doubt whether a piece of technology is a tool or a companion. People’s attachments to devices like Alexa are one thing similar to a child’s attachment to a bear. In a house fire, we know we’re leaving the game behind. But tech companies shouldn’t manipulate ordinary users regarding an unconscious AI system as a truly conscious friend.

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Ultimately, with the right mix of scientific and engineering expertise, we may be able to move forward to creating undisputedly conscious AI systems. But then we must be willing to pay the cost: giving them the rights they deserve.

Eric Schwezgebel is Professor of Philosophy at the University of California, Riverside and author of The Shockwave Theory and Other Philosophical Adventures. Henry Shevlin is a senior researcher specializing in non-human minds at the University of Cambridge’s Leverholm Center for the Future of Intelligence.



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