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A Reality Check for Tech Oligarchs

A Reality Check for Tech Oligarchs

Yahoo28-05-2025
Technologists currently wield a level of political influence that was recently considered unthinkable. While Elon Musk's Department of Government Efficiency slashes public services, Jeff Bezos takes celebrities to space on Blue Origin and the CEOs of AI companies speak openly of radically transforming society. As a result, there has never been a better moment to understand the ideas that animate these leaders' particular vision of the future.
In his new book, More Everything Forever, the science journalist Adam Becker offers a deep dive into the worldview of techno-utopians such as Musk—one that's underpinned by promises of AI dominance, space colonization, boundless economic growth, and eventually, immortality. Becker's premise is bracing: Tech oligarchs' wildest visions of tomorrow amount to a modern secular theology that is both mesmerizing and, in his view, deeply misguided. The author's central concern is that these grand ambitions are not benign eccentricities, but ideologies with real-world consequences​.
What do these people envision? In their vibrant utopia, humanity has harnessed technology to transcend all of its limits—old age and the finite bounds of knowledge most of all. Artificial intelligence oversees an era of abundance, automating labor and generating wealth so effectively that every person's needs are instantly met. Society is powered entirely by clean energy, while heavy industry has been relocated to space, turning Earth into a pristine sanctuary. People live and work throughout the solar system. Advances in biotechnology have all but conquered disease and aging. At the center of this future, a friendly AI—aligned with human values—guides civilization wisely, ensuring that progress remains tightly coupled with the flourishing of humanity and the environment.
Musk, along with the likes of Bezos and OpenAI's CEO, Sam Altman, aren't merely imagining sci-fi futures as a luxury hobby—they are funding them, proselytizing for them, and, in a growing number of cases, trying to reorganize society around them. In Becker's view, the rich are not merely chasing utopia, but prioritizing their vision of the future over the very real concerns of people in the present. Impeding environmental research, for instance, makes sense if you believe that human life will continue to exist in an extraterrestrial elsewhere. More Everything Forever asks us to take these ideas seriously, not necessarily because they are credible predictions, but because some people in power believe they are.
[Read: The rise of techno-authoritarianism]
Becker, in prose that is snappy if at times predictable, highlights the quasi-spiritual nature of Silicon Valley's utopianism, which is based on two very basic beliefs. First, that death is scary and unpleasant. And second, that thanks to science and technology, the humans of the future will never have to be scared or do anything unpleasant. 'The dream is always the same: go to space and live forever,' Becker writes. (One reason for the interest in space is that longevity drugs, according to the tech researcher Benjamin Reinhardt, can be synthesized only 'in a pristine zero-g environment.') This future will overcome not just human biology but a fundamental rift between science and faith. Becker quotes the writer Meghan O'Gieblyn, who observes in her book God, Human, Animal, Machine that 'what makes transhumanism so compelling is that it promises to restore through science the transcendent—and essentially religious—hopes that science itself obliterated.'​
Becker demonstrates how certain contemporary technologists flirt with explicitly religious trappings. Anthony Levandowski, the former head of Google's self-driving-car division, for instance, founded an organization to worship artificial intelligence as a godhead​. But Becker also reveals the largely forgotten precedents for this worldview, sketching a lineage of thought that connects today's Silicon Valley seers to earlier futurist prophets. In the late 19th century, the Russian philosopher Nikolai Fedorov preached that humanity's divine mission was to physically resurrect every person who had ever lived and settle them throughout the cosmos, achieving eternal life via what Fedorov called 'the regulation of nature by human reason and will.'
The rapture once preached and beckoned in churches has been repackaged for secular times: In place of souls ascending to heaven, there are minds preserved digitally—or even bodies kept alive—for eternity. Silicon Valley's visionaries are, in this view, not all cold rationalists; many of them are dreamers and believers whose fixations constitute, in Becker's view, a spiritual narrative as much as a scientific one—a new theology of technology.
Let's slow down: Why exactly is this a bad idea? Who wouldn't want 'perfect health, immortality, yada yada yada,' as the AI researcher Eliezer Yudkowsky breezily summarizes the goal to Becker? The trouble, Becker shows, is that many of these dreams of personal transcendence disregard the potential human cost of working toward them. For the tech elite, these are visions of escape. But, Becker pointedly writes, 'they hold no promise of escape for the rest of us, only nightmares closing in.'​
Perhaps the most extreme version of this nightmare is the specter of an artificial superintelligence, or AGI (artificial general intelligence). Yudkowsky predicts to Becker that a sufficiently advanced AI, if misaligned with human values, would 'kill us all.'​ Forecasts for this type of technology, once fringe, have gained remarkable traction among tech leaders, and almost always trend to the stunningly optimistic. Sam Altman is admittedly concerned about the prospects of rogue AI—he famously admitted to having stockpiled 'guns, gold, potassium iodide, antibiotics, batteries, water, gas masks from the Israeli Defense Force, and a big patch of land in Big Sur I can fly to'—but these worries don't stop him from actively planning for a world reshaped by AI's exponential growth. In Altman's words, we live on the brink of a moment in which machines will do 'almost everything' and trigger societal changes so rapid that 'the future can be almost unimaginably great.' Becker is less sanguine, writing that 'we just don't know what it will take to build a machine to do all the things a human can do.' And from his point of view, it's best that things remain that way.
[Read: Silicon Valley braces for chaos]
Becker is at his rhetorically sharpest when he examines the philosophy of 'longtermism' that underlies much of this AI-centric and space-traveling fervor. Longtermism, championed by some Silicon Valley–adjacent philosophers and the effective-altruism movement, argues that the weight of the future—the potentially enormous number of human (or post-human) lives to come—overshadows the concerns of the present. If preventing human extinction is the ultimate good, virtually any present sacrifice can and should be rationalized. Becker shows how today's tech elites use such reasoning to support their own dominance in the short term, and how rhetoric about future generations tends to mask injustices and inequalities in the present​. When billionaires claim that their space colonies or AI schemes might save humanity, they are also asserting that only they should shape humanity's course. Becker observes that this philosophy is 'made by carpenters, insisting the entire world is a nail that will yield to their ministrations.'​
Becker's perspective is largely that of a sober realist doing his darnedest to cut through delusion, yet one might ask whether his argument occasionally goes too far. Silicon Valley's techno-utopian culture may be misguided in its optimism, but is it only that? A gentle counterpoint: The human yearning for transcendence stems from a dissatisfaction with the present and a creative impulse, both of which have driven genuine progress. Ambitious dreams—even seemingly outlandish ones—have historically spurred political and cultural transformation. Faith, too, has helped people face the future with optimism. It should also be acknowledged that many of the tech elite Becker critiques do show some awareness of ethical pitfalls. Not all (or even most) technologists are as blithe or blinkered as Becker sometimes seems to suggest.
In the end, this is not a book that revels in pessimism or cynicism; rather, it serves as a call to clear-eyed humanism. In Becker's telling, tech leaders err not in dreaming big, but in refusing to reckon with the costs and responsibilities that come with their dreams. They preach a future in which suffering, scarcity, and even death can be engineered away, yet they discount the very real suffering here and now that demands our immediate attention and compassion. In an era when billionaire space races and AI hype dominate headlines, More Everything Forever arrives as a much-needed reality check. At times, the book is something more than that: a valuable meditation on the questionable stories we tell about progress, salvation, and ourselves.
Article originally published at The Atlantic
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Everything you need to know about iOS 26 beta release: How to download it on your iPhone, new Apple features like Liquid Glass and more
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Your chats with Meta's AI might end up on Google — just like ChatGPT until it turned them off
Your chats with Meta's AI might end up on Google — just like ChatGPT until it turned them off

Business Insider

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Your chats with Meta's AI might end up on Google — just like ChatGPT until it turned them off

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Federal Reserve economists aren't sold that AI will actually make workers more productive, saying it could be a one-off invention like the light bulb
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Federal Reserve economists aren't sold that AI will actually make workers more productive, saying it could be a one-off invention like the light bulb

A new Federal Reserve Board staff paper concludes that generative artificial intelligence (genAI) holds significant promise for boosting U.S. productivity, but cautions that its widespread economic impact will depend on how quickly and thoroughly firms integrate the technology. Titled 'Generative AI at the Crossroads: Light Bulb, Dynamo, or Microscope?' the paper, authored by Martin Neil Baily, David M. Byrne, Aidan T. Kane, and Paul E. Soto, explores whether genAI represents a fleeting innovation or a groundbreaking force akin to past general-purpose technologies (GPTs) such as electricity and the internet. The Fed economists ultimately conclude their 'modal forecast is for a noteworthy contribution of genAI to the level of labor productivity,' but caution they see a wide range of plausible outcomes, both in terms of its total contribution to making workers more productive and how quickly that could happen. To return to the light-bulb metaphor, they write that 'some inventions, such as the light bulb, temporarily raise productivity growth as adoption spreads, but the effect fades when the market is saturated; that is, the level of output per hour is permanently higher but the growth rate is not.' Here's why they regard it as an open question whether genAI may end up being a fancy tech version of the light bulb. GenAI: a tool and a catalyst According to the authors, genAI combines traits of GPTs—those that trigger cascades of innovation across sectors and continue improving over time—with features of 'inventions of methods of invention' (IMIs), which make research and development (R&D) more efficient. The authors do see potential for genAI to be a GPT like the electric dynamo, which continually sparked new business models and efficiencies, or an IMI like the compound microscope, which revolutionized scientific discovery. The Fed economists did cautioning that it is early in the technology's development, writing 'the case that generative AI is a general-purpose technology is compelling, supported by the impressive record of knock-on innovation and ongoing core innovation.' Since OpenAI launched ChatGPT in late 2022, the authors said genAI has demonstrated remarkable capabilities, from matching human performance on complex tasks to transforming frontline work in writing, coding, and customer service. That said, the authors said they're finding scant evidence about how many companies are actually using the technology. Limited but growing adoption Despite such promise, the paper stresses that most gains are so far concentrated in large corporations and digital-native industries. Surveys indicate high genAI adoption among big firms and technology-centric sectors, while small businesses and other functions lag behind. Data from job postings shows only modest growth in demand for explicit AI skills since 2017. 'The main hurdle is diffusion,' the authors write, referring to the process by which a new technology is integrated into widespread use. They note that typical productivity booms from GPTs like computers and electricity took decades to unfold as businesses restructured, invested, and developed complementary innovations. 'The share of jobs requiring AI skills is low and has moved up only modestly, suggesting that firms are taking a cautious approach,' they write. 'The ultimate test of whether genAI is a GPT will be theprofitability of genAI use at scale in a business environment and such stories are hard to come by at present.' They know that many individuals are using the technology, 'perhaps unbeknownst to their employers,' and they speculate that future use of the technology may become so routine and 'unremarkable' that companies and workers no longer know how much it's being used. Knock-on and complementary technologies The report details how genAI is already driving a wave of product and process innovation. In healthcare, AI-powered tools draft medical notes and assist with radiology. Finance firms use genAI for compliance, underwriting, and portfolio management. The energy sector uses it to optimize grid operations, and information technology is seeing multiples uses, with programmers using GitHub Copilot completing tasks 56% faster. Call center operators using conversational AI saw a 14% productivity boost as well. Meanwhile, ongoing advances in hardware, notably rapid improvements in the chips known as graphics processing units, or GPUs, suggest genAI's underlying engine is still accelerating. Patent filings related to AI technologies have surged since 2018, coinciding with the rise of the Transformer architecture—a backbone of today's large language models. 'Green shoots' in research and development The paper also finds genAI increasingly acting as an IMI, enhancing observation, analysis, communication, and organization in scientific research. Scientists now use genAI to analyze data, draft research papers, and even automate parts of the discovery process, though questions remain about the quality and originality of AI-generated output. The authors highlight growing references to AI in R&D initiatives, both in patent data and corporate earnings calls, as further evidence that genAI is gaining a foothold in the innovation ecosystem. Cautious optimism—and open questions While the prospects for a genAI-driven productivity surge are promising, the authors warn against expecting overnight transformation. The process will require significant complementary investments, organizational change, and reliable access to computational and electric power infrastructure. They also emphasize the risks of investing blindly in speculative trends—a lesson from past tech booms. 'GenAI's contribution to productivity growth will depend on the speed with which that level is attained, and historically, the process for integrating revolutionary technologies into the economy is a protracted one,' the report concludes. Despite these uncertainties, the authors believe genAI's dual role—as a transformative platform and as a method for accelerating invention—bodes well for long-term economic growth if barriers to widespread adoption can be overcome. Still, what if it's just another light bulb? For this story, Fortune used generative AI to help with an initial draft. An editor verified the accuracy of the information before publishing. This story was originally featured on Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data

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