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AI Is Reshaping American Cities - But Not Equally
by Daniele Quercia May 8, 2025

May 8, 2025

May be of interest… AI Is Reshaping American Cities - But Not Equally Daniele Quercia [cid:image001.png@01DBBFF9.91B8F060] Darker colours represent higher AI impact within MSAs. Grey areas indicate regions outside the boundaries of MSAs, which generally have lower population densities and are not included in the analysis due to limited data availability. Artificial intelligence promises to transform how we work, automating tasks, boosting productivity, and opening up new economic frontiers. But beneath the optimism lies a stark reality: AI's impact is far from evenly spread. In a new study<https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-025-0…> published in Springer EPJ Data Science, we examined how AI is likely to affect labour markets across U.S. metropolitan areas. The results reveal a troubling pattern: one that risks deepening America’s existing economic divides. By analysing 24,758 AI-related patents filed between 2015 and 2022 and linking them to 17,879 occupational tasks, we developed a fine-grained map of where AI is likely to hit hardest. The findings defy the assumption that only major tech hubs are vulnerable. In fact, many of the most at-risk places are mid-sized cities whose economies hinge on a single sector. Dalton, Georgia, for example, is tightly bound to carpet manufacturing. Columbus, Indiana depends on the automotive industry. Rochester, Minnesota, renowned for its healthcare sector, also faces elevated risk. In each case, a heavy reliance on routine-intensive industries leaves these places exposed to automation, with few alternative sectors to soften the blow. In contrast, some of the least-impacted cities in our analysis such as Daphne-Fairhope-Foley in Alabama, Coeur d’Alene in Idaho, and Grants Pass in Oregon share a different trait: economic diversity. These cities spread employment across a broader range of industries, making them better equipped to absorb shocks and adjust as AI transforms specific sectors. We also found that the East Coast, on average, is more exposed to AI disruption than the West. Though highly innovative hubs like the Bay Area and Seattle remain high-impact outliers. Cities experiencing rapid growth in “creative class” jobs such as engineers, scientists, designers are also more likely to face disruption. Knowledge work, it turns out, is not immune to automation; in some cases, it is on the front lines. AI is not just a story of technological progress. It is a story of geography, resilience, and inequality. Left unchecked, it could entrench existing divides, fuelling growth in already-advantaged regions while sidelining those with fewer resources to adapt. The policy response must match the scale of the challenge: support for economic diversification, investment in re-skilling, and a renewed focus on regions at risk of being left behind. To help individuals and policymakers better understand what AI might mean for them, we’ve also made our data public. On our interactive platform<http://social-dynamics.net/aii>, users can explore how AI is projected to affect different occupations, and even drill down to specific tasks within those jobs to see which are most susceptible to automation. The AI revolution is underway. With the right tools and the right foresight, we can ensure it lifts more communities than it leaves behind.

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European Data Sovereignty, iniziative italiane?
by Marco Fioretti May 8, 2025

May 8, 2025

Buongiorno a tutti, devo scrivere (entro domani sera...) un breve commento, molto generale, su questo tema. Qualsiasi segnalazione di iniziative e proposte italiane in proposito, nonche' ad esempio di posizioni e commenti dei politici, e' benvenuta. Idem per vostre opinioni sul tema. NON so se riusciro' a usare quanto ricevero' stavolta, ma potrei proporlo come seguito del primo post. Grazie in anticipo, Marco

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AI and Internet Hygiene
by Daniela Tafani May 7, 2025

May 7, 2025

Non mi pare sia stato segnalato a suo tempo AI and Internet Hygiene we are going to have to re-learn how to use the computer Kate Wagner Oct 01, 2024 I’m from a very specific generation, the first one in which learning how to use the open Internet was a skill taught in childhood. There’s not much that’s good about being from this generation (I will never own a house, be out of student loan debt, and the idea of having children takes on an air of fantasy) but at least I learned how to be proficient at the computer. This proficiency was out of necessity. You see, back in the days before total market saturation, the big tech companies had an incentive to educate. They couldn’t sell a technology people were so intimidated by. Classes were taught in schools, libraries, and community centers, and a cottage industry of computer instruction sprung up everywhere. A wealth of educational materials flooded the market targeted towards new computer and Internet users, which, in the early 1990s, was pretty much anyone not working in a previously computerized industry. Some of these were even for children: <https://www.youtube.com/watch?v=SzQLI7BxfYI> The Internet of the 1990s and 2000s and the Internet of the present couldn’t be more different. Both the early and middle Internet shared a commonality of being mostly decentralized and much less closed-source than it presently is under platformization. While so many of us are nostalgic for this now, in an era when five corporations own the entire web, at the time it was a double-edged sword. In some ways, the basic HTML and blinking GIFs Internet of the past was utopian in scope — millions of people learning how to express themselves and communicate with one another in real time, each around a certain skill level. But in other ways, it was an experimental void in which a mix of anonymity and technological prowess could be used not to contribute knowledge or become better-connected but to exploit those just figuring out how to use this brand new technology. Later, when the Internet reached more people, when it evolved into more expansive communities, blogs, content aggregators and early social media sites such as YouTube or MySpace, and when storage space became more conducive to hosting big files, threats and dangers adapted to this new environment in ever-more savvy ways. In other words, the old Internet was not exactly safe. This was especially true during the Windows XP era when that operating system achieved an unprecedented and long-lasting market share, making it a common target. Pop-up ads, scams, drive-by downloads, and wretched computer viruses were extremely common. If you ended up somewhere you weren’t supposed to, the consequences could be dire: your computer would be crippled, hijacked and made slow; sometimes you could even lose everything, all from clicking a link you weren’t supposed to. People my age (30) remember this well. It was a rite of passage in those days to give your family computer a particularly terrible virus (such as one of those fake anti-virus programs that is actually malware) while trying to download custom content for The Sims 2. Hence, because of this fraught webscape, by the age of ten, I knew how to clean up after these kinds of messes — going into the registry, system restoring, booting the computer into Safe Mode so as to run an anti-virus or uninstall a harmful program — all of which required understanding on a basic, structural level, how the computer worked. But more importantly, I learned how to avoid getting into all that trouble in the first place by being able to spot suspicious search engine results, inspect links, and generally discern through visual cues and precedence what parts of online seemed legitimate versus illegitimate. I practiced what is sometimes called Internet hygiene. While computer viruses never stopped being a threat (everyone should still employ the services of an antivirus software) the nature of that threat has changed. Organized hackers are less interested in giving your PC a fake antivirus and more interested in targeting large scale legacy systems such as those used in governments, hospitals, and corporations. Rather than THEMATRIX_(1999).mov.exe, social engineering, ransomware, click fraud, cryptojacking, and data leaks are the orders of the day. Meanwhile, the platformized, app-driven Internet, through moderation and centralization, have made websites into closed systems more impervious to old-school threats such as pop-up ads or drive-by downloads. New Internet-based licensing protocols (increasingly based on monthly subscriptions instead of one-time software licenses) such as Adobe Creative Cloud and Steam, and streaming media services such as Spotify and YouTube that provide swaths of content for little to no cost have not only decimated physical media (and price gouged creators and users alike) — they’ve also chipped away at piracy and the once-overwhelmingly common practice of peer-to-peer sharing, another virus hotbed. Ad-blockers, while a wicked problem for the old-web economy of click-based revenues, also do their part in keeping users safe. I can remember very clearly when I stopped being able to use the computer. It was around 2012, when I switched to MacOS, which (I feel) is a much less transparent operating system than Windows, one that held less of a market share and was thus less commonly targeted by widespread Internet booby traps. (This is not to say Macs don’t get viruses — they absolutely do.) Meanwhile, Internet consumption shifted to smartphones, and the app-based ecosystem only reinforced the closedness and opaqueness of platforms as other websites gradually disappeared. I myself have no idea how a smartphone works, nor the full extent to which my data is being tracked. In fact, we are so inured to sharing data that the very concept of Internet (and personal) privacy itself is eroding more and more. As a result of these massive transformations, computer and Internet usage have been remarkably deskilled among ordinary users. The knowledge of how the Internet or an operating system works, things that used to be necessary simply for using both, has become obfuscated and, as a result, relegated to those in the privatized technology sector. Now, however, the Internet is changing massively yet again. The premature unleashing of AI and large language models (LLMs) in particular onto the open Internet is already having dire consequences for what were, for years, considered stabilized, centralized (if flawed) systems, such as the search engine. AI, thanks to the scope of its spread, its rogue unreliability (it lies — often), the way it poisons search results, hijacks SEO, and is increasingly being used for disinformation and fraud, is reintroducing a fundamental and destabilizing distrust back into the Internet. Once more, I can no longer trust the results Google provides me. On a daily basis I have to ask myself increasingly familiar questions: Is this first result a legitimate news source? Is this image of a protest real? Is that picture of a Kandinsky painting really his or is an AI forgery of his work? Across the board, it’s becoming increasingly hard to tell. For me and countless others, what used to be rote Internet usage has now turned into a nightmarish amount of wasted time spent discerning what is and isn’t real. As far as I, the ordinary user, am concerned, AI is evolving not into a life-changing and labor-saving technology as was promised by its capitalist overlords, but rather into a form of malware that targets, whether unwittingly or not, critical Internet infrastructure. The problem is, the deskilling of Internet usage has made many users helpless against this new threat. While it’s (barely) possible for the savvy among us to use prior knowledge of existing resources and databases, or search engine filters (e.g. by date) to avoid AI-generated content, the more AI becomes enmeshed in critical infrastructure, the more we will once more have to develop a new type of Internet hygiene out of necessity. As I had to navigate this new web more and more, I began noticing that being able to tell the signs of whether a publication is legitimate or AI slop was not so different on its face than being able to tell whether that link to a repository of videogame content is giving virus. AI generated content has a visual and rhetorical trace that is becoming more and more consolidated as the software feeds on its own entrails. Just like landing pages with five DOWNLOAD links and janky websites gave pause in the aughts, fake journalism sites that didn’t exist before 2021 and are just ads and links should give pause now. The good news is, we’ve developed Internet hygiene before and we can do it again. Faced with this threat, new guides to healthy and safe Internet use will have to be written for the common user — especially since it looks like the big tech companies aren’t going to do anything to stem the rot. This is a project that should, in a just society, be taken on by libraries and other public outreach programs. Universities and schools should develop curricula not about how to use or embrace AI but to teach a new form of Internet literacy and usage protocol in order to protect students from scams and disinformation. Hopefully, new tools — a kind of AI anti-virus — will be developed to block AI’s web crawlers or even scan for ersatz content, though this might be wishful thinking considering how the technology works. This task will become especially critical in fields such as medicine, engineering, and law, where AI poisoning has the potential to cause incredible damage that puts human life at risk. But first, all of this requires actually recognizing the existential, infrastructural threat AI poses to the tools modern society now runs on. Those systems faced threats at the dawn of their creation that were no less existential. Call me nostalgic, but the old-school virus prevention framework, I think, is a helpful and time-tested one. Finally, as terrible as the AI infection of the Internet at large is, perhaps a re-skilling of the computer-using population is a silver lining. After two generations of Internet illiteracy, an embrace of new tools for empowerment and understanding can help salvage not only the Internet (if such a thing is still possible) but maybe even some of that old utopianism it once promised. At its core, the computer and the Internet are tools for creation, education, commerce, play, and communication. We as a society shouldn’t have to throw the baby out with the bathwater. <https://www.late-review.com/p/ai-and-internet-hygiene>

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Curl sotto DDoS da AI
by Giacomo Tesio May 7, 2025

May 7, 2025

Gli sviluppatori di Curl banneranno chi segnala bug individuati da AI. <https://archive.is/IZOug> That's it. I've had it. I'm putting my foot down on this craziness. 1. Every reporter submitting security reports on #Hackerone for #curl now needs to answer this question: "Did you use an AI to find the problem or generate this submission?" (and if they do select it, they can expect a stream of proof of actual intelligence follow-up questions) 2. We now ban every reporter INSTANTLY who submits reports we deem AI slop. A threshold has been reached. We are effectively being DDoSed. If we could, we would charge them for this waste of our time. We still have not seen a single valid security report done with AI help.

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AI as Normal Technology
by Daniela Tafani May 6, 2025

May 6, 2025

AI as Normal Technology An alternative to the vision of AI as a potential superintelligence By Arvind Narayanan and Sayash Kapoor April 15, 2025 We articulate a vision of artificial intelligence (AI) as normal technology. To view AI as normal is not to understate its impact—even transformative, general-purpose technologies such as electricity and the internet are “normal” in our conception. But it is in contrast to both utopian and dystopian visions of the future of AI which have a common tendency to treat it akin to a separate species, a highly autonomous, potentially superintelligent entity. The statement “AI is normal technology” is three things: a description of current AI, a prediction about the foreseeable future of AI, and a prescription about how we should treat it. We view AI as a tool that we can and should remain in control of, and we argue that this goal does not require drastic policy interventions or technical breakthroughs. We do not think that viewing AI as a humanlike intelligence is currently accurate or useful for understanding its societal impacts, nor is it likely to be in our vision of the future. The normal technology frame is about the relationship between technology and society. It rejects technological determinism, especially the notion of AI itself as an agent in determining its future. It is guided by lessons from past technological revolutions, such as the slow and uncertain nature of technology adoption and diffusion. It also emphasizes continuity between the past and the future trajectory of AI in terms of societal impact and the role of institutions in shaping this trajectory. In Part I, we explain why we think that transformative economic and societal impacts will be slow (on the timescale of decades), making a critical distinction between AI methods, AI applications, and AI adoption, arguing that the three happen at different timescales. In Part II, we discuss a potential division of labor between humans and AI in a world with advanced AI (but not “superintelligent” AI, which we view as incoherent as usually conceptualized). In this world, control is primarily in the hands of people and organizations; indeed, a greater and greater proportion of what people do in their jobs is AI control. In Part III, we examine the implications of AI as normal technology for AI risks. We analyze accidents, arms races, misuse, and misalignment, and argue that viewing AI as normal technology leads to fundamentally different conclusions about mitigations compared to viewing AI as being humanlike. Of course, we cannot be certain of our predictions, but we aim to describe what we view as the median outcome. We have not tried to quantify probabilities, but we have tried to make predictions that can tell us whether or not AI is behaving like normal technology. In Part IV, we discuss the implications for AI policy. We advocate for reducing uncertainty as a first-rate policy goal and resilience as the overarching approach to catastrophic risks. We argue that drastic interventions premised on the difficulty of controlling superintelligent AI will, in fact, make things much worse if AI turns out to be normal technology— the downsides of which will be likely to mirror those of previous technologies that are deployed in capitalistic societies, such as inequality <https://www.aisnakeoil.com/p/ai-as-normal-technology>

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183° Mercoledì di Nexa | 14 maggio 2025, ore 17.00
by Nexa - Media May 6, 2025

May 6, 2025

Gentilissime, gentilissimi, Vi invitiamo a partecipare al 183° Mercoledì di Nexa, che si terrà mercoledì 14 maggio, alle ore 17.00, con un incontro dal titolo "I segni di Proteo". Ospite dell'incontro: Massimo Leone (Università degli Studi di Torino). L'incontro si terrà IN PRESENZA e ONLINE. SEDE FISICA Centro Nexa su Internet e Società, Politecnico di Torino, Via Boggio 65/a, Torino (1° piano). Per accedere alla sala si raccomanda di suonare al citofono Portineria e di seguire le indicazioni segnalate lungo il percorso. QUI<https://nexa.polito.it/contatti> maggiori informazioni su come raggiungerci. STANZA VIRTUALE dell'incontro: https://didattica.polito.it/VClass/NexaEvent Di seguito maggiori dettagli: https://nexa.polito.it/mercoledi-183 Cordiali saluti, -- Valeria Bergantino Communication Manager Nexa Center for Internet & Society Politecnico di Torino - DAUIN Via Pier Carlo Boggio, 65/A - 10138 Torino web: https://nexa.polito.it/ mail: valeria.bergantino(a)polito.it<mailto:valeria.bergantino@polito.it> tel: 3473443585

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Gazaweb, Aiuta a piantare gli "Alberi della Rete" a Gaza
by graffio May 5, 2025

May 5, 2025

Buongiorno lista. Invio questa richiesta di aiuto per un progetto di solidarietà con l'umanità intrappolata nella striscia di Gaza. Da inizio Ottobre 2023 il traffico internet a Gaza è diminuito di oltre l’80%. Le interruzioni sono state causate da una combinazione di attacchi diretti alle infrastrutture di telecomunicazione civili, restrizioni all’accesso all’elettricità e interruzioni tecniche dei servizi di telecomunicazione. L'ong ACS ha avviato da più di un anno il progetto "Gazaweb - Alberi della Rete", sistema internet alternativo per aggirare il blocco israeliano a Gaza. In un contesto devastato da bombardamenti e infrastrutture distrutte, questa rete consente alla popolazione di mantenere legami sociali, comunicare con affetti dispersi nella Striscia e condividere emergenze. L’intervento di emergenza più rapido sul quale *GazaWeb* si è impegnato sono gli eSIM-hotspots, ovvero gli *Alberi della Rete*. Una serie di cellulari di ultima generazione consentono il collegamento ai network internazionali anche con le *eSIM*, carte sim virtuali che (tramite l’attivazione di un codice) svolgono le stesse funzioni di una SIMcard tradizionale. Non potendo inviare materiale fisico all''interno della striscia, è sufficiente inviare il codice di attivazione eSIM (qrcode) a chi possiede uno di questi dispositivi per attivare collegamenti alle reti cellulari egiziane o israeliane dall’interno della striscia di Gaza. La ong *ACS* ha allestito, in coordinamento con i cooperanti presenti a Gaza, una serie di hot-spot via wi-fi connessi a internet tramite eSIM, ognuno dei quali permette la connessione a circa 50 ulteriori dispositivi. In questo modo anche chi non è in possesso di cellulari di ultima generazione può agganciarsi a internet tramite il segnale wi-fi irradiato dall’*Albero della Rete*. ACS ha intenzione di “piantare” un buon numero di Alberi della Rete nei campi profughi e nelle altre aree dove le reti telefoniche non sono accessibili o sono sotto lo stretto controllo delle autorità israeliane. Oltre a essere una soluzione tecnica, questa soluzione rappresenta un simbolo di resilienza collettiva, offrendo connessione umana e speranza in un territorio isolato dal conflitto. *Più eSIM si riescono ad attivare, più si infittisce il bosco degli Alberi della Rete e le relative connessioni.* *Sottoscrivi per far crescere gli alberi della rete: https://aiutagazaweb.vado.li* Per approfondire https://www.acs-italia.it/gazaweb-e-gli-alberi-della-rete/ https://peertube.mesnumeriques.fr/w/26vP1HYDgTgxcz6XMk9stJ Serve aiuto!! grazie -- Maurizio "Graffio" Pillole di informazione digitale - https://pillole.graffio.org/ "C.I.R.C.E. - https://circex.org" AvANa -https://avana.forteprenestino.net/

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Argomentazione morale e biomedicina nell’era dell’AI
by Cristiano Cali' May 5, 2025

May 5, 2025

Carissimi, mi permetto di ricordare il Workshop su Argomentazione morale e biomedicina nell’era dell’AI, che si terrà questa settima, l’8 e il 9 maggio, presso l’Università degli Studi di Torino. In allegato il programma. Un cordiale saluto. Cristiano Calì, PhD Research Fellow in Moral Philosophy Dipartimento di Filosofia e Scienze Dell'Educazione - Università degli Studi di Torino Institute for Ethics and Emerging Technologies - Boston Via Sant'Ottavio, 20 - 10124 Turin, Piedmont, Italy +39 3491489788 <tel:+393491489788> cristianocali30(a)gmail.com <mailto:cristianocali30@gmail.com> <https://unict.academia.edu/CristianoCali> <https://scholar.google.com/citations?user=zRTES68AAAAJ&hl=it> <https://www.linkedin.com/in/cristianocal> <https://www.researchgate.net/profile/Cristiano-Cali> <https://philpeople.org/profiles/cristiano-cali> <https://orcid.org/0000-0002-5235-2177>

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A weird phrase is plaguing scientific papers – and we traced it back to a glitch in AI training data
by Alberto Cammozzo May 4, 2025

May 4, 2025

<https://theconversation.com/a-weird-phrase-is-plaguing-scientific-papers-an…> theconversation.com A weird phrase is plaguing scientific papers – and we traced it back to a glitch in AI training data Rayane El Masri Earlier this year, scientists discovered a peculiar term appearing in published papers: “vegetative electron microscopy”. This phrase, which sounds technical but is actually nonsense, has become a “digital fossil” – an error preserved and reinforced in artificial intelligence (AI) systems that is nearly impossible to remove from our knowledge repositories. Like biological fossils trapped in rock, these digital artefacts may become permanent fixtures in our information ecosystem. The case of vegetative electron microscopy offers a troubling glimpse into how AI systems can perpetuate and amplify errors throughout our collective knowledge. A bad scan and an error in translation Vegetative electron microscopy appears to have originated through a remarkable coincidence of unrelated errors. First, two papers from the 1950s, published in the journal Bacteriological Reviews, were scanned and digitised. However, the digitising process erroneously combined “vegetative” from one column of text with “electron” from another. As a result, the phantom term was created. Decades later, “vegetative electron microscopy” turned up in some Iranian scientific papers. In 2017 and 2019, two papers used the term in English captions and abstracts. This appears to be due to a translation error. In Farsi, the words for “vegetative” and “scanning” differ by only a single dot. An error on the rise The upshot? As of today, “vegetative electron microscopy” appears in 22 papers, according to Google Scholar. One was the subject of a contested retraction from a Springer Nature journal, and Elsevier issued a correction for another. The term also appears in news articles discussing subsequent integrity investigations. Vegetative electron microscopy began to appear more frequently in the 2020s. To find out why, we had to peer inside modern AI models – and do some archaeological digging through the vast layers of data they were trained on. Empirical evidence of AI contamination The large language models behind modern AI chatbots such as ChatGPT are “trained” on huge amounts of text to predict the likely next word in a sequence. The exact contents of a model’s training data are often a closely guarded secret. To test whether a model “knew” about vegetative electron microscopy, we input snippets of the original papers to find out if the model would complete them with the nonsense term or more sensible alternatives. The results were revealing. OpenAI’s GPT-3 consistently completed phrases with “vegetative electron microscopy”. Earlier models such as GPT-2 and BERT did not. This pattern helped us isolate when and where the contamination occurred. We also found the error persists in later models including GPT-4o and Anthropic’s Claude 3.5. This suggests the nonsense term may now be permanently embedded in AI knowledge bases. By comparing what we know about the training datasets of different models, we identified the CommonCrawl dataset of scraped internet pages as the most likely vector where AI models first learned this term. The scale problem Finding errors of this sort is not easy. Fixing them may be almost impossible. One reason is scale. The CommonCrawl dataset, for example, is millions of gigabytes in size. For most researchers outside large tech companies, the computing resources required to work at this scale are inaccessible. Another reason is a lack of transparency in commercial AI models. OpenAI and many other developers refuse to provide precise details about the training data for their models. Research efforts to reverse engineer some of these datasets have also been stymied by copyright takedowns. When errors are found, there is no easy fix. Simple keyword filtering could deal with specific terms such as vegetative electron microscopy. However, it would also eliminate legitimate references (such as this article). More fundamentally, the case raises an unsettling question. How many other nonsensical terms exist in AI systems, waiting to be discovered? Implications for science and publishing This “digital fossil” also raises important questions about knowledge integrity as AI-assisted research and writing become more common. Publishers have responded inconsistently when notified of papers including vegetative electron microscopy. Some have retracted affected papers, while others defended them. Elsevier notably attempted to justify the term’s validity before eventually issuing a correction. We do not yet know if other such quirks plague large language models, but it is highly likely. Either way, the use of AI systems has already created problems for the peer-review process. For instance, observers have noted the rise of “tortured phrases” used to evade automated integrity software, such as “counterfeit consciousness” instead of “artificial intelligence”. Additionally, phrases such as “I am an AI language model” have been found in other retracted papers. Some automatic screening tools such as Problematic Paper Screener now flag vegetative electron microscopy as a warning sign of possible AI-generated content. However, such approaches can only address known errors, not undiscovered ones. Living with digital fossils The rise of AI creates opportunities for errors to become permanently embedded in our knowledge systems, through processes no single actor controls. This presents challenges for tech companies, researchers, and publishers alike. Tech companies must be more transparent about training data and methods. Researchers must find new ways to evaluate information in the face of AI-generated convincing nonsense. Scientific publishers must improve their peer review processes to spot both human and AI-generated errors. Digital fossils reveal not just the technical challenge of monitoring massive datasets, but the fundamental challenge of maintaining reliable knowledge in systems where errors can become self-perpetuating.

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Tech oligarchs are gambling our future on a fantasy | Adam Becker | The Guardian
by Alberto Cammozzo May 4, 2025

May 4, 2025

<https://www.theguardian.com/commentisfree/2025/may/03/tech-oligarchs-musk> Tech oligarchs are gambling our future on a fantasy It’s tempting to believe that tech billionaires’ embrace of Donald Trump and the far right is a sudden rupture with the usual political ideology of Silicon Valley. Op-eds in the New York Times and elsewhere have made this case. Even Marc Andreessen, one of the billionaires in question, claims that this is what happened – he said that it was a change in the Democratic arty that pushed him and his fellow oligarchs into the arms of the GOP. Yet this is a serious misunderstanding of the situation. There wasn’t a sudden shift in the politics of tech – it was a homecoming. While it’s true that Silicon Valley has long supported Democratic candidates for political office – and that rank-and-file tech workers still vote overwhelmingly for Democrats – the fundamental ideology underpinning the culture of Silicon Valley’s venture capitalists and CEOs has always had a far-right libertarian core. This is even true for Andreessen: while he likely believed what he said while he was saying it, his own words and actions make it clear that he wasn’t giving an accurate assessment of his own motivations, much less anyone else’s. His venture capital firm, Andreessen Horowitz, has long opposed government regulation of any sort that touches on their investments; Andreessen himself posted a “techno-optimist manifesto” that, despite its claim to be politically neutral, promotes an authoritarian vision of unfettered power for tech oligarchs. He even lovingly paraphrases Filippo Marinetti, the co-author of the Fascist Manifesto. But the place where the longstanding rightwing ideals of the leaders of the tech industry are most obvious are in their visions of the future. Elon Musk dreams of Mars; Sam Altman claims super-intelligent AI is around the corner. It’s easy to dismiss these as fantasies, deliberate distractions from their present actions. But this is another mistake, closely related to the first. These futures are central to the tech billionaires’ worldview. And these ideas about the future have always contained a political element aligned with dreams of total autocratic control. Take Mars. Musk has been fairly specific about it: he says he wants a million people living on Mars by the year 2050 in a self-sufficient colony, serving as a backup for humanity in the event of a catastrophe on Earth. He has framed this as an existential struggle, claiming that SpaceX’s Starship rocket “is the key to making life multi-planetary & protecting the light of consciousness”. Jeff Bezos has derided Musk’s plans for Mars, instead saying that we should aim at having a trillion people in space several generations from now, living in a fleet of giant space stations, each with interiors the size of a major city. The alternative, he says, is a brutal future of population control, rationing and “stagnation”. Bezos is right to pan Musk’s plans for Mars: they will not work. Mars is awful. The gravity is too low, the radiation levels are too high, there’s basically no air and the dirt is made of poison. But Bezos’s plans don’t work either, for a similar litany of reasons. And more fundamentally, there’s no good argument for humans to leave Earth in the first place. The idea of Mars as a backup for humanity in the event of a disaster on Earth is laughable, precisely because Mars is so awful – there’s in effect no disaster, not even nuclear war or a massive asteroid strike, that could make Earth less hospitable for humans than Mars. And the math behind Bezos’s fears of stagnation and rationing – which are really fears about the end of growth – aren’t significantly alleviated by going to space, where resources are just as finite as they are here on Earth. What these fantasies of space do allow are visions of total corporate control free of governments, a libertarian paradise. Musk’s Starlink user agreement has a clause maintaining that “the parties recognize Mars as a free planet and that no Earth-based government has authority or sovereignty over Martian activities”. (This is in direct violation of international treaties governing space.) Residents of Musk’s Mars colony would be wholly dependent on SpaceX for everything, even the air they breathe; it would be a more total company town than any possible here on Earth. Meanwhile, Bezos’s fleet of space stations wouldn’t be a company town – they would be a company civilization. And with the constant peril of decompression and asphyxiation at hand, Musk and Bezos (or their corporate heirs) would have a ready-made excuse to exercise autocratic control over the residents of these space habitats. Space is the location of the tech billionaires’ futuristic dreams, but AI is the magic that fuels them. Such AI is always depicted as being able to do as least as much as humans can, if not more. Yet there’s little reason to think that AI like that is coming anytime soon. In a recent survey of AI researchers, 76% said that neural networks, the general architecture that underlies nearly all advanced AI, are fundamentally unsuitable for creating “AGI”, a hypothetical AI that can do everything humans can do. Even more of those researchers said that “the current perception of AI capabilities” is overblown. Nonetheless, in the world of Silicon Valley CEOs and venture capitalists (and among credulous journalists and policymakers), there is a widespread belief that AGI is coming very soon, within a few years. This unquestioned faith in AGI is linked to a broader myth about the future of technology in general. Once AGI arrives, the story goes, it will quickly and inevitably become super-intelligent, far surpassing individual humans or even humanity as a whole in its capabilities. This will lead to an explosion in scientific and technological development that dwarfs the Industrial Revolution, known as the Singularity. The Singularity will reshape the lives of all humans, enabling seemingly magical results like easy space travel, immortality or near-immortality, perfect virtual reality and limitless energy, all within a few years or less – and the AI’s super-intelligent beneficence will render democracy obsolete. This vision of technological salvation is baked into the heart of Silicon Valley’s collective unconscious, and has been for decades. Futurist groups in the 1980s and 90s whispered promises of a singularity powered by machine intelligence over early internet email lists, alongside diatribes against democracy and affirmative action and paeans to free markets. The idea of a singularity and all its attendant miracles can be traced back through these groups to mid-20th-century science-fiction – with its trappings of robots and rocket ships conquering the final frontier – and back beyond that to apocalyptic Christian religious movements of the late 19th and early 20th century. These ideas about the future were originally about using technology to ascend to heaven and live forever in the presence of God. They have come down to today’s tech oligarchs with AI playing the role of the deity and space as a substitute for paradise, but they are no less of a religion than they were a century ago. The tech billionaires’ unshakable faith in this religion of technological salvation leads them to believe the end of this world, and the advent of a perfect one, is nigh. AI and space colonization will lead to utopia, algorithmically guaranteed. This is why they need to believe that AI is amazing, beyond the fact that it’s propping up a bubble – it’s central to their entire worldview. They must believe that AI can be used to replace essential government workers, improve productivity in the workplace and accelerate scientific research, despite all evidence to the contrary. Tech billionaires are even gambling the planet on the imminent arrival of AGI. Eric Schmidt, the billionaire venture capitalist and former CEO of Google, claims that pursuing AGI is the best path forward to solve the climate crisis, despite the enormous carbon footprint of AI data centers, because of his certainty that AGI will fix the problem for us after its imminent arrival. Sam Altman agrees, and he’s even explained how he thinks that would work. “I think once we have a really powerful super-intelligence, addressing climate change will not be particularly difficult for a system like that,” he says. “If you think about a system where you can say, ‘Tell me how to make a lot of clean energy cheaply,’ ‘Tell me how to efficiently capture carbon,’ and then ‘Tell me how to build a factory to do this at planetary scale’ – if you can do that, you can do a lot of other things too.” Altman’s plan to solve global warming by asking a nonexistent machine for three wishes is not something our civilization can afford to indulge. The tech oligarchs are confident that their godhead will arrive and deliver us to paradise. This offers them moral absolution for their actions and gives them a sense of meaning. But their faith offers nothing for the rest of us, who cannot afford to live anywhere other than the real world. Adam Becker is a science journalist, astrophysicist, and author of More Everything Forever: AI Overlords, Space Empires, and Silicon Valley’s Crusade to Control the Fate of Humanity

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