AGI/ASI Timelines thread (AGI/ASI may solve longevity if it doesn't "kill us all" first)

From the New Scientist:

How worried should you be about an AI apocalypse?

Fears that artificial intelligence could rise up to wipe out humanity are understandable given our steady diet of sci-fi stories depicting just that, but what is the real risk? Matthew Sparkes looks at what the experts say

What we do know for certain is that a lot of very smart people are worried. Many of today’s AI company bosses have warned of the possibility of AI leading to human extinction, and even the pioneer of machine intelligence, Alan Turing, spoke of a future in which computers become sentient, before outstripping our abilities and finally taking over.

The scenario plays out something like this. Imagine we give an AI the sole task of solving a big, meaty problem like the Riemann hypothesis, one of the most famous unsolved problems in mathematics. It could decide that what it needs is lots and lots of computing power and, unconstrained by common sense, set about turning every inanimate object on Earth into one huge supercomputer, leaving 8 billion of us to starve to death in a vast, sterile data centre. It might even use us as raw material, too.

Now, you could argue that in this scenario, we might notice what the AI was doing and give it a quick nudge by saying, “By the way, it looks like you’re turning the whole world into a data centre and, if that’s the case, please stop, because we still need to live on Earth.” But some people might prefer to have safeguards in place to spot this kind of issue before it happens and prevent any harm.

Sci-fi writer Isaac Asimov famously had a crack at this with his three laws of robotics, the first of which is that a robot may not injure a human being or, through inaction, allow a human being to come to harm.

So, in theory, we can just tell AI not to harm us, and it won’t, right? Well, no. Our ability to build safeguards and rules into AI is clumsy and ineffective. We can tell today’s large language models not to be racist, or swear, or divulge the recipe for explosives, but in the right circumstances, they’ll go right ahead and do it anyway. We simply don’t understand what happens inside an AI model well enough to prevent it doing things we don’t want it to do.

Full story: How worried should you be about an AI apocalypse? (New Scientist)

Sam Altman May Control Our Future—Can He Be Trusted?

New interviews and closely guarded documents shed light on the persistent doubts about the head of OpenAI.

Of all the promises made at OpenAI’s founding, arguably the most central was its pledge to bring A.I. into existence safely. But such concerns are now often derided in Silicon Valley and in Washington. Last year, J. D. Vance, the former venture capitalist who is now the Vice-President, addressed a conference in Paris called the A.I. Action Summit. (It was previously called the A.I. Safety Summit.) “The A.I. future is not going to be won by hand-wringing about safety,” he said. At Davos this year, David Sacks, a venture capitalist who was serving as the White House’s A.I. and crypto czar, dismissed safety concerns as a “self-inflicted injury” that could cost America the A.I. race. Altman now calls Trump’s deregulatory approach “a very refreshing change.”

OpenAI has closed many of its safety-focussed teams. Around the time the superalignment team was dissolved, its leaders, Sutskever and Leike, resigned. (Sutskever co-founded a company called Safe Superintelligence.) On X, Leike wrote, “Safety culture and processes have taken a backseat to shiny products.” Soon afterward, the A.G.I.-readiness team, tasked with preparing society for the shock of advanced A.I., was also dissolved. When the company was asked on its most recent I.R.S. disclosure form to briefly describe its “most significant activities,” the concept of safety, present in its answers to such questions on previous forms, was not listed. (OpenAI said that its “mission did not change” and added, “We continue to invest in and evolve our work on safety, and will continue to make organizational changes.”) The Future of Life Institute, a think tank whose principles on safety Altman once endorsed, grades each major A.I. company on “existential safety”; on the most recent report card, OpenAI got an F. In fairness, so did every other major company except for Anthropic, which got a D, and Google DeepMind, which got a D-.

“My vibes don’t match a lot of the traditional A.I.-safety stuff,” Altman said. He insisted that he continued to prioritize these matters, but when pressed for specifics he was vague: “We still will run safety projects, or at least safety-adjacent projects.” When we asked to interview researchers at the company who were working on existential safety—the kinds of issues that could mean, as Altman once put it, “lights-out for all of us”—an OpenAI representative seemed confused. “What do you mean by ‘existential safety’?” he replied. “That’s not, like, a thing.”

A.I. doomers have been pushed to the fringes, but some of their fears seem less fantastical with each passing month. In 2020, according to a U.N. report, an A.I. drone was used in the Libyan civil war to fire deadly munitions, possibly without oversight by a human operator. Since then, A.I. has only become more central to military operations around the world, including, reportedly, in the current U.S. campaign in Iran. In 2022, researchers at a pharmaceutical company tested whether a drug-discovery model could be used to find new toxins; within a few hours, it had suggested forty thousand deadly chemical-warfare agents. And many more mundane harms are already coming to pass. We increasingly rely on A.I. to help us write, think, and navigate the world, accelerating what experts call “human enfeeblement”; the ubiquity of A.I. “slop” makes life easier for scammers and harder for people who simply want to know what’s real. A.I. “agents” are starting to act independently, with little or no human supervision. Days before the 2024 New Hampshire Democratic primary, thousands of voters received robocalls from an A.I.-generated deepfake of Joe Biden’s voice, telling them to save their votes for November and stay home—an act of voter suppression requiring virtually no technical expertise. OpenAI is now facing seven wrongful-death lawsuits, which allege that ChatGPT prompted several suicides and a murder. Chat logs in the murder case show that it encouraged a man’s paranoid delusion that his eighty-three-year-old mother was surveilling and trying to poison him. Soon afterward, he fatally beat and strangled her and stabbed himself. (OpenAI is fighting the lawsuits, and says that it’s continuing to improve its model’s safeguards.)

Read the full story: Sam Altman May Control Our Future—Can He Be Trusted? (New Yorker Magazine)

I think a whole lot of age-related damage cannot be fixed by little robots. I think a lot of them are just kind of physically impossible to fix with robots. Some of the damages are literally on the atomic scale. A robot bigger than a bacteria could fix very small damages, but many damages are orders of magnitude smaller than bacteria so the robot would be far to big to fix them. There are physical limits to how small a robot can possibly be built and the smallest robots are bound to be orders of magnitude larger than the smallest damages.

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Well, I agree. This is why I hedged by saying “huge progress on aging”. Once tiny robots are here, it will solve some of the problems, but many will remain – like DNA damage. Though, I’m guessing DNA damage in some organs could be fixed by tissue replacement; and perhaps tiny robots could help shuttle cells or cell clusters into the right location.

Another use of tiny robots would be highly-localized drug delivery that bypasses the gut and liver. And what about removing tumors cell-by-cell everywhere in the body all at once? (I should ask my brother if he thinks that’s feasible; he’s an oncologist + hematologist.) Could one remove damaged elastin (using locally-deployed chemicals) and replace it with new (chemically-delivered locally)? Remove arterial plaque using atherectomy pretty much everywhere in the body? Serve as an immune system 2.0 where damaged cells are removed, bad bacteria is destroyed? Keep hematopoietic cell population diverse? Help shuttle stem cells to where they are needed?

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We Are Witnessing the Rise of a New Aristocracy

Inequality is such a fact of American life that it’s easy to shrug off. But we are in uncharted terrain. The amassed wealth of today’s tech titans makes the Rockefellers and the Vanderbilts look quaint. Over the past two years, 19 households have added $1.8 trillion to their coffers, the economist Gabriel Zucman told me — roughly the size of the economy of Australia.

Into this fragile state enters artificial intelligence. It threatens to make a bad situation much worse.

Left on its current course, A.I. could deliver a bleak picture: lower- and middle-income jobs automated away, with top earners remaining unscathed. Income shifting from middle-wage workers doing the bulk of the labor toward those wealthy enough to bankroll the technology. Growth headwinds. Worsening affordability. So, too, a federal government less able to respond, thanks to a shrinking tax base.

For any society in which this much wealth gets concentrated in so few hands, and is then so easily parlayed into political clout, the question becomes one not just of economics but of basic civic standing. At some point soon, we are no longer sharing in self-government.

Start with A.I.’s impact on jobs. ​​Technologists are convinced that a labor apocalypse is nigh. In this story, A.I. is sometimes posited as a great equalizer, gutting white-collar jobs and salaries, giving more clout to trades like plumbing and dimming the luster of that Ivy League degree. The theory has gotten the nod from academics, industry associations and institutions such as the O.E.C.D.

Read the full article: We Are Witnessing the Rise of a New Aristocracy (NYT)

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Industrial Policyfor the Intelligence Age: Ideas to Keep People First, April 2026 (OpenAI)

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It would seem that AI data centers may be weak links in the global infrastructure… and why exactly did anyone think it was a good idea to put a major data center in a war zone (which the Middle East has been for decades)?

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Elon wants them in space…probably safer than the middle east. Iowa is pretty safe but I admit I don’t want one here. Power bills will go up and somebody might bomb it. I wouldn’t complain, just would prefer somebody else do it.

I have a pretty tenuous grip on why we need such a level of these things. I watch videos all the time of amazing things going on improving speed, reduced power consumtion etc… Why don’t they just pile up money for a while and spend on the better stuff later?

https://x.com/AISecurityInst/status/2043683577594794183

We conducted cyber evaluations of Claude Mythos Preview and found that it is the first model to complete an AISI cyber range end-to-end. ![:thread:]

The range simulates a 32-step corporate network attack, from initial reconnaissance to full network takeover.

We estimate it would take a human expert 20 hours to complete.

In 2023 the best models could barely complete beginner-level cyber tasks.

Today, our evaluation of Mythos Preview shows that it – and potentially future models – could be directed to autonomously compromise small, weakly defended, and vulnerable systems if given network access.

These results underscore the importance of cyber security fundamentals like regular security updates, access controls, security configuration, and logging.

Future models will be more capable still, but AI can also deliver advanced capabilities for defence.

About this group:

The AI Security Institute (AISI) is a research organisation within the UK government’s Department for Science, Innovation and Technology working towards this goal: building the world’s leading understanding of advanced AI risks and solutions, to inform governments so they can keep the public safe.

Our work includes:

  • Testing leading AI systems before they are released publicly and collaborating with top AI companies to improve their safety and security;
  • Informing policymakers across the UK and allied governments about emerging capabilities and risks;
  • Advancing research into solutions with in-house research and >£15 million in grant funding;

Leaders from across the public and private sectors

  • Our Interim Director Adam Beaumont was the UK intelligence agency GCHQ’s former Chief AI Officer.
  • Our Chief Technology Officer Jade Leung is also the Prime Minister’s AI Advisor, and she previously led the Governance team at OpenAI.
  • Our Chief Scientist Geoffrey Irving and Research Director Chris Summerfield have collectively led teams at OpenAI, Google DeepMind and the University of Oxford.
  • Our Chair Ian Hogarth brings experience as a leading tech investor and entrepreneur.
  • Our advisory board comprises national security and machine learning leaders such as Yoshua Bengio.
  • Our 100+ technical staff bring experience from leading industry, academic and nonprofit labs.
  • Our policy, operations, and strategy teams bring experience from No. 10, the national security community, and many of the UK’s best startups and large-scale companies.
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From Stanford University:

Introducing the #AIIndex2026: Our most comprehensive, independently sourced data analysis of AI’s trajectory, with a clear-eyed assessment of the critical gaps that remain. As AI advances rapidly, can the systems built around it keep up? Explore the data:

News Coverage of this Stanford Report:

Want to understand the current state of AI? Check out these charts.

According to Stanford’s 2026 AI Index, AI is sprinting, and we’re struggling to keep up.

If you’re following AI news, you’re probably getting whiplash. AI is a gold rush. AI is a bubble. AI is taking your job. AI can’t even read a clock. The 2026 AI Index from Stanford University’s Institute for Human-Centered Artificial Intelligence, AI’s annual report card, comes out today and cuts through some of that noise.

Despite predictions that AI development may hit a wall, the report says that the top models just keep getting better. People are adopting AI faster than they picked up the personal computer or the internet. AI companies are generating revenue faster than companies in any previous technology boom, but they’re also spending hundreds of billions of dollars on data centers and chips. The benchmarks designed to measure AI, the policies meant to govern it, and the job market are struggling to keep up. AI is sprinting, and the rest of us are trying to find our shoes.

All that speed comes at a cost. AI data centers around the world can now draw 29.6 gigawatts of power, enough to run the entire state of New York at peak demand. Annual water use from running OpenAI’s GPT-4o alone may exceed the drinking water needs of 12 million people. At the same time, the supply chain for chips is alarmingly fragile. The US hosts most of the world’s AI data centers, and one company in Taiwan, TSMC, fabricates almost every leading AI chip.

The data reveals a technology evolving faster than we can manage. Here’s a look at some of the key points from this year’s report.

Read the full story: Want to understand the current state of AI? Check out these charts. (MIT Technology Review)

and, from TechCrunch:

Stanford report highlights growing disconnect between AI insiders and everyone else

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A recent Science News Explores story looked at how teens are using AI, as well as their biggest hopes and fears about this tech. At least half of 13- to 17-year-olds use chatbots for homework and other tasks, a Pew survey finds. About one-third of those teens feel optimistic about AI’s benefits to themselves and society.

A new Gallup poll now offers insight into how Gen Z’s views on AI may be shifting.

It took a broader look at Gen Zers — people ages 14 to 29. Again, it found that more than half of them regularly use generative AI. But this survey also suggests that Gen Zers’ feelings about this tech have soured over just the past year. The share who said they felt hopeful about its effects dropped from 27 to 18 percent. Those who felt excited about AI dropped from 36 percent to just 22.

In both 2025 and 2026, some 40 percent of Gen Zers described being anxious about AI. But the share who feel angry about its effects climbed notably — from 22 to 31 percent. Gen Zers’ biggest fears included how AI might affect their creativity and critical thinking.

“Fostering trust in AI among Gen Z will seemingly depend on demonstrating how AI can enhance rather than replace human talents,” wrote Megan Brenan, senior editor at Gallup, in a rundown of the survey’s findings.

Meanwhile, people in San Francisco seem to be voting via their actions, and things are heating up (so to speak)… Someone threw a molotov cocktail at Sam Altman’s house the other day, and then this…

Suspect in attack at Sam Altman’s house aimed to kill OpenAI CEO, warned of humanity’s extinction from AI

Impressive. Some people are scared, I am absolutely fascinated, no more reading sci-fi books, since sci-fi is now among us.
Meanwhile everyone, me included, is very curious to see what Mythos, this emerging supermodel, will be able to do aside from hacking cybersecurity code.
It will be costly but the results may provide a significant return on the investment.
I have already been surprised by what Opus 4.6 can do in specific engineering fields that I know (foundation engineering). And Opus 4.6 is one rung below Mythos.
Apparently, we are steadily heading toward AGI.

Anyone using the Anthropic models for biology, preventive medicine, biohacking?

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I just did a test. 4 flagship models (Opus 4.6; Gemini 3.1 pro; chatGPT 5.3; Grok 4.2 multiagent) compared in a question on mimicking the effects of Rapa with diet, lifestle and supplements.
Opus 4.6 was pretty good, but not significantly better than other models.

Maybe I should try something more detailed and specific.

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New story in Fortune Magazine:

From Molotov cocktails to data center shutdowns, the AI backlash is turning revolutionary

For years, the resistance to artificial intelligence (AI) looked manageable. There were academics writing open letters, Hollywood writers striking over contract language, the think-tank reports warning of job displacement. Tech executives nodded, pledged responsibility, and kept building as fast as they could.

Then someone threw a firebomb at Sam Altman’s house.

On Friday, a 20-year-old man named Daniel Moreno-Gama traveled from Spring, Texas, to San Francisco’s Pacific Heights neighborhood and hurled an incendiary device at the gate of OpenAI CEO Sam Altman’s $27 million home, igniting a fire on the exterior gate. No one was injured, but Moreno-Gama was arrested approximately an hour later outside OpenAI’s headquarters — where he was allegedly trying to shatter the building’s glass doors with a chair and threatening to burn the facility to the ground. He is now facing state charges of attempted murder and federal charges that could include domestic terrorism.

Authorities afterward found a manifesto warning of humanity’s “extinction” at the hands of AI and expressing an urge to commit murder, and a disturbing personal Substack. The next morning, Altman posted a plea for sanity on his X account, attaching a photo of his husband and young child. “Normally we try to be pretty private, but in this case I am sharing a photo in the hopes that it might dissuade the next person from throwing a Molotov cocktail at our house, no matter what they think about me,” Altman wrote.

To no avail. Early Sunday morning, two more Gen-Zers, one 23 and the other 25, were arrested after shooting a gun near the Russian Hill home of Sam Altman (it is unclear at this time if the shooting was targeted).

After the attacks, pundits and professional opinion-havers pointed fingers in every direction: at the StopAI crowd, a radical group that has staged protests and flash-subpoena-deliveries to try to halt the pace of artificial intelligence altogether; at the news media, which has critically covered Altman and his peers; and at Altman himself, for stoking fear about AI displacement with his sometimes-apocalyptic rhetoric. Among the older commentariat, however, the dominant note was remorse and well wishes for Altman.

But in the younger, less formal corners of the internet, like Instagram and TikTok, the comments under every post about the attacks generally run in one direction. “He’s not scared enough.” “Based do it again.” “FREE THAT MAN HE DID NOTHING WRONG.” “Finally some good news on my feed.”

Those comments are ugly, but for those who’ve been paying attention to the anti-AI backlash build, not shocking. At all.

Gen Z is not a fan of AI. At all

The middle distribution of Gen-Z’s feelings about AI range from apprehension to downright hatred. Despite the fact that more than half of Gen Z living in the U.S. uses AI regularly, according to a recently released Gallup poll, less than a fifth feel hopeful about the technology. About a third says the technology makes them angry. And nearly half say it makes them afraid.

Gallup’s own senior education researcher, Zach Hrynowski, blamed the bad vibes at least partially on the dwindling job market. The oldest Zoomers, he told Axios, are the angriest, as they are “acutely aware” of the ability of a technology to transform cultural norms without a second thought, unlike a Gen Xer who is trained to see new technology as toys and are still “playing around with AI.”

Indeed, the job prospects for the recently graduated Gen-Z are abysmal; Bloomberg just reported that 43% of young graduates are “underemployed,” meaning taking on jobs that require less education than they have.

But that can’t explain all of the vitriol. Perhaps some of it is the yawning gap beween promise and reality, symbolized by Altman himself. The OpenAI CEO has suggested that AI will usher in an era of “universal basic compute,” that people will barely need to work, that the future will be almost frictionless. That isn’t happening as of 2026.

Instead, inflation remains stubbornly untamable, as it has throughout the decade; consumers have never felt worse about their financial state, and Gen Z feels like they’re entering a “starter economy” without plentiful jobs or affordable homes. And so there’s a real mismatch, as Alex Hanna, a professor and researcher who studies the social impacts of AI, put it, “between consumer confidence and people’s pocketbooks and budgets, and what the technologists and the AI companies say the future is supposed to look like.”

Data center backlash

This is not just a Gen Z problem, either. In the American heartland, data centers are being proposed at a pace that local communities never anticipated and for which they were never asked permission, and they’re increasingly pushing back.

The numbers are serious. According to a report from 10a Labs’ Data Center Watch, at least $18 billion worth of data center projects have been blocked and another $46 billion delayed over the past two years due to local opposition. At least 142 activist groups across 24 states are now actively organizing to block data center construction and expansion. A Heatmap Pro review of public records found that 25 data center projects were canceled following local pushback in 2025 alone, four times as many as in 2024, with 21 of those cancellations occurring in the second half of the year as electricity costs grew.

The concerns driving this resistance are less about existential AI risk and more about typical kitchen-table complaints; communities consistently cite higher utility bills, water consumption, noise, impacts on property values, and green space destruction as their primary objections. Water use is mentioned as a top concern in more than 40% of contested projects, according to a Heatmap Pro review of public records.

Meanwhile, Hanna noted, companies keep lording over the threat of AI replacing workers as “leverage.” She added, “Employers are making room for AI investments. They want to show that they can lay off people and do what they’re currently doing with a decrease in headcount.”

Read the Full story here: From Molotov cocktails to data center shutdowns, the AI backlash is turning revolutionary

Should a handful of men be entrusted with the world’s most potent new technology? Five geeks so famous that they can be identified by their first names—Dario, Demis, Elon, Mark and Sam—exercise almost godlike command over the artificial-intelligence models that will shape the future. The Trump administration has stood aside even as those models have gained jaw-dropping capabilities, convinced that unfettered competition between private firms is the best way to ensure America wins the ai race against China.

The watershed was Anthropic’s announcement of Claude Mythos on April 7th. The model-maker’s latest creation is so startlingly good at finding software vulnerabilities that, in the wrong hands, it would threaten critical infrastructure, from banks to hospitals. ai models increasingly pose other risks, too, from biosecurity hazards to industrial-scale scamming.

Anthropic’s boss, Dario Amodei, wisely thought Mythos too dangerous for general release. Instead he has reserved it for use by around 50 big firms, in computing, software and finance, so that they can boost their own defences. America’s treasury secretary, Scott Bessent, was so unnerved that he summoned the biggest banks for urgent talks.

Until now. Suddenly, America’s free-wheeling treatment of ai looks as if it is coming to an end. The reason is that the models’ dizzying progress also poses a threat to America’s own national security, unnerving members of the Trump administration previously more inclined to worry about overregulation. At the same time, growing resentment among American voters is turning ai into a political lightning-rod. A laissez-faire approach is no longer politically tenable or strategically wise.

Read the full article: America wakes up to AI’s dangerous power - After Mythos, a laissez-faire approach is no longer politically tenable or strategically wise (Economist.com)

I run a fintech server, most of the contacts to the server already are hacking attempts. It is irritating as we do recognise them then block the IP, but there are so many it is silly.

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I wonder if this could be a leading indicator of the broader AI jobs market of the future …

Source: https://x.com/econcallum/status/2046260139339251753?s=20

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It’s a beautiful place but this probably has to do with what it costs to live there.

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A new research paper out of NYU:

Tyranny Of The Minority: How Social Media Influencers, Algorithms, And Crowds Shape Public Opinion

The digital landscape has shifted from the top-down “invisible” manipulation of the 20th century to a decentralized, yet equally potent, “tyranny of the minority”. This paper analyzes Renée DiResta’s Invisible Rulers , arguing that public opinion is no longer shaped solely by institutional elites, but by a “trinity” consisting of social media influencers, platform algorithms, and the crowds that follow them. The “Big Idea” is the emergence of “bespoke realities”—custom-made information silos that allow fringe views to masquerade as social norms.

Research indicates that this distortion is driven by a staggering concentration of influence: approximately 0.01% of Twitter users were responsible for spreading 80% of the misinformation during the 2016 U.S. election. These “invisible rulers” are often extreme voices that game algorithms through high activity levels, creating a “funhouse mirror” effect where fringe opinions appear far more popular than they are in reality. This dynamic pushes reasonable and nuanced voices out of the public square, replacing them with hostile narratives and conspiracy theories.

The consequences are not merely academic; they have direct impacts on public health, economics, and democracy. For instance, coordinated anti-vaccine narratives drive vaccine hesitancy despite broad real-world support for immunizations. Furthermore, traditional media outlets, including the New York Times , are increasingly trapped in the same incentive loops, pulling stories from social media to maintain traffic and relevance. As we enter the era of generative AI, the authors warn that while AI could potentially nudge users toward accuracy, it is equally likely to empower influencers to create even more realistic and dynamic propaganda campaigns.


Actionable Insights: Information Hygiene for Health and Longevity

From a healthspan perspective, the “tyranny of the minority” represents a significant environmental toxin in the form of misinformation and chronic stress.

  • Audit Medical Information Sources: Given that 0.01% of users generate 80% of misinformation, biological or longevity data sourced from social media influencers should be viewed with extreme skepticism unless verified against primary clinical repositories like PubMed.

  • Mitigate Cortisol Spikes: The “bespoke realities” created by algorithms are designed to evoke high-arousal emotions, which can lead to chronic stress. Actively “unfollowing” hyperpartisan or extreme accounts is a proven method to reduce out-party animosity and, by extension, the physiological stress associated with digital conflict.

  • Combat the “Funhouse Mirror” Effect: Recognize that online consensus regarding health protocols (e.g., anti-vaccine sentiment) often does not reflect actual social norms or scientific reality. This cognitive decoupling is essential to prevent making health decisions based on amplified fringe views.

  • Algorithmic Friction: Introducing “friction”—such as pausing before sharing or using tools that increase transparency—can help individuals reclaim cognitive agency from addictive platform designs.


Context and Impact Evaluation

  • Open Access Paper: Tyranny Of The Minority: How Social Media Influencers, Algorithms, And Crowds Shape Public Opinion
  • Institution: New York University (NYU), USA; Norwegian School of Economics, Norway.
  • Journal Name: Administrative Science Quarterly (ASQ) (Review/Commentary).
  • Impact Evaluation: The impact score of this journal is approximately 15.9 (JIF 2024/2025), evaluated against a typical high-end range of 0–60+ for top general science, therefore this is an Elite impact journal within the field of management and social sciences.
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