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Anecdote of Knowledge

No story about any technology is complete without the Greek myth of the titan Prometheus. As the story goes, he uses his godly connections to introduce humans to the Olympian secret of fire and is cursed to have his entrails harvested for eternity. The punishment for Prometheus, seems quite extreme for his crime, compared to the multitude of affairs and abuses amongst the Greek Pantheon. What made introducing people to this technology so dangerous? Perhaps it was the fact that fire became a catalyst for human innovation and connection, allowing people to settle into caves and establish territories and shelters (Washburn 1961), as opposed to roaming around from precarious settlement to precarious settlement? It is no exaggeration to say that fire was massive in changing people from hunter-gatherers to agriculturalists. So, to truly make Prometheus worthy of his punishment, it would have almost certainly been the widespread diffusion of fire, allowing for its diverse applications such as in agriculture and colonization. Fire was the first true social innovation. It allowed humans to assert control over nature’s (the gods’) whims, becoming the seeming masters of it. The tradition of using technology and machinery to control and manipulate the complexity of the world continues today. It finds new life in Large Language Models trying to control intelligence itself.

The World of the Mechanist

The Science Delusion (Sheldrake 2012) was understandably controversial when biologist Rupert Sheldrake published his critique on contemporary scientific research. Despite his more dubious claims about the nature of science research, Sheldrake accurately assesses some of the fallacies and exploitations associated with mechanistic thinking. For example, he contextualized Descartes’s description of biological systems as a type of machinery within his cruel dog experiments undertaken to understand each “mechanical” part of the animal. While this example is rather specific, it demonstrates Sheldrake’s point that under a mechanistic view, nature is an expendable system that can be extracted from and reassembled, with no care or consideration for the whole. Whereby contrast, nature is something that can exhibit emergent “living” complexity and be permanently altered and violated just by mere changes to its parts and conditions. Importantly, this ideology even corresponds with how many professions, such as economists, discuss nature today. Rather than being an inherent part of the cost calculus, in economic exchanges between agents such as those regarding the use of natural resources and large-scale intelligence companies, nature is treated as an externality (Boudreaux and Meiners 2019), paid socially by other externalities (people) (Eisenstein 2011). So, from an economic perspective, the promise of AI’s unrealized efficiency and adaptability is too much to give up on, but the price of nature is negligible. The mechanists of Silicon Valley do not care about the cost to humans, they are only interested in the march of progress.

Human Obsolescence and the March of Progress

Frontier AI labs have promised untold benefits for humanity, but it remains hard to reconcile this in the face of the almost careless impact AI has had on human lives. News organizations are facing widespread plagiarism allegations in the face of training and enhancing computer models (“A.I., Journalism and the Uncertain Future of the Public Square” 2026). Traditional school assignments are failing to accomplish their purpose as students complete more of their assignments with AI systems eager to answer any question (Watson-Fore 2026). This is especially dangerous when a wide variety of studies are warning of AI’s massive negative impact on the learning process (Kosmyna et al. 2025), (Stromberg et al. 2026), (Rismanchian et al. 2026). AI companies are prioritizing the goal of solving mathematical problems rather than cooperating with the mathematical community to promote understanding and learning (Avila et al. 2026). Laborers not only are losing job opportunities as management opts for the nebulous technological marking hype of AI labs (Roy, n.d.) but are also finding that their carefully cultivated, work-based identities are under threat. After all, if AI can do any job, it becomes hard to argue that anything someone can do is human at all. If AI can solve any problem, what point is there in solving any problem at all? Institutions and their constituents are facing challenges with modern technology from the practical to the ontological. Increasingly, it seems rational to merely adopt to the new values of technology, as authors of Power and Progress paraphrase this sentiment:

“We couldn’t stop them if we wanted to, and it would be highly inadvisable to try. It is better to change ourselves—for example, by investing in skills that will be valued in the future.” (Acemoglu and Johnson 2024)

However, it is easy to forget in the midst of technological excitement that anxieties related to human obsolescence and innovation are not so new. Current trends in employable skills revolve around making sure you can use AI tools, but before that there was an “everyone should learn to code” phase, which followed an “everyone should get a degree” phase, among others. Even the Industrial Revolution was not without its growing pains and fair share of modernization pressures. Reflecting on his trip to mid-nineteenth century industrial London, American editor Horace Greeley wrote:

“On every side the onward march of Invention is constant, rapid, inexorable. The human Reaper of thirty years ago, finds to-day a machine cutting grain twenty times as fast as ever he could; he gets three days’ work as its waiter where he formerly had three weeks’ steady harvesting: the work is as well done as of old, and far cheaper; but his share of the product is sadly diminished.” (Acemoglu and Johnson 2024)

There is no shortage of things people should be doing and learning to avoid being replaced and excluded in their role for society. And yet, it seems inevitable that innovations, by default, work to exclude as many of these workers as possible, all in the name of saving costs.

Hoarding the Productivity

Who actually benefits from the explosion of modern AI? Following the money, it seems that a small minority of tech companies are enjoying spreading the wealth amongst themselves. It is more than clear in today’s landscape, satisfying users is not the primarily goal of software anymore. Rather, technology is now for the benefit of their creators, and users are merely tools for technology to exploit. Below is a simple graphic illustrating the flow of money between several of these tech companies, but there are far more examples of capital centralization than depicts.

For example, in 2025 Micron exited the consumer space entirely (Micron Announces Exit from Crucial Consumer Business Micron Technology, n.d.), opting to prioritize providing the latest in memory technology to businesses only, excluding consumers. Multiple companies, such as Delta Airlines, are beginning to experiment with AI-based dynamic pricing models (Weekend 2025) which comes with a variety of discrimination risks from model overfitting (Noble 2024) but, more importantly for Delta, there are potential profits gains from first degree price discrimination (Botta and Wiedemann 2020). It seems, despite the lofty promises of big tech and AI’s widespread industrial impact, that most people will not have a share in the new prosperity AI is supposed to bring. Can this technology be used for the people or will people be left behind while new age companies harvest untold wealth?

The People Left Behind?

AI is often presented as this novel problem, suggesting that there is no precedent and that the ability to cope with it is something that will only be developed over time. But history and fiction provide stories of similar situations. There are characters and archetypes who have learned to cope with their place in the world amidst their own uncertain times.

Miyamoto Musashi was a famous swordsman who lived through Japan’s Edo period, where Gunpowder was the defining technology of the age. Traditionally, soldiers and swordsmen were a rare resource because mastering the tools of war (swords, horses, spears, etc.) would take total dedication, if not many years of training. But the introduction of muskets changed this, making it far easier to become a soldier. As military historian Gwynne Dyer notes:

“Firearms take much less time to master and are much more democratic in their effects: samurai and commoners died with equal speed and equal futility in the Takeda clan’s desperate charges at Nagashino.” (Gwynne Dyer 2005)

On top of the change in military structure, a pervasive era of peace marked the Edo period, further casting doubt on the necessity of highly trained warriors. It is in this backdrop of the Edo period’s “uncertain times” for warriors that the historical fiction story of (Inoue et al. 2025) takes place. In this story, Musashi is a ronin desiring to “make a name for himself” through his skills with the sword, seeking recognition through his tangible feats of power when most have stopped regarding warriors as admirable. However, as he progresses through the story, Mushashi reflects on his ego driven desire to dominate. As Musashi’s mentor figure, the priest, Takuan Soho states:

“As long as you’re only concerned about your own life. Life has no worth. It is only through the support of others... that one’s life has any value.” (Inoue et al. 2025)

Musashi comes to realize his desire for strength was a self-isolating endeavor that ultimately brought him no satisfaction and everyone else immense suffering. Each fight he won only lead to more violence and never bought him “invincibility,” a thinly veiled desire to be untouched by nature. This contrasts against his famous historical rival Sasaki Kojiro, depicted as deaf and mute. Ironically, this sensory deprivation makes Kojiro’s swordsmanship stand out as it was entirely detached from the world’s perception of the sword. Free from the expectations of violence, dominance, and oppression associated with swords, Kojiro’s swordplay stands out as beautiful and pure to Musashi. It appears as a type of art where interpretation and expression are done through battle and is not muddled by societal pressure or the ego’s desire to prove itself. In other words, despite how little warriors mattered in this time, Kojiro’s swordplay still meant something, as evidenced by how popular Kojiro and Musashi’s myths are today. While Musashi seeks to be above nature and people as a swordsman, Kojiro integrates himself into the world through his swords. Musashi further engages with this as he journeys to a famine-stricken village and instead of traveling through, works to cultivate the land of the village. For the first time, Musashi is not working towards his own self-satisfaction but the satisfaction of others as well, using his strength to help build canals that integrate with nature to make rice fields, as well as defending the village from the onslaught of bandits. Not only are the villagers better off for it, but he is much better off for it as well, having obtained a much richer conception of strength that is not dependent on oppressing others but on lifting people up. It was when Musashi looked for meaning in others that he was able to find purpose in his own art.

Courage In Uncertainty

Contemporary news paints a bleak picture of modern technology. Some even go as far to say that AI is entirely worthless for most people. But AI is not without its merits as well. On the open-source platform Hugging Face  there is a huge database of models for technical users to experiment with, improve on, and apply to a wide variety of problems. Scientists have been able to accelerate discovery through machine learning applications such as predicting protein structures (Jumper et al. 2021). Important technological infrastructure is being secured thanks to ML powered vulnerability discovery (Vaughan-Nichols 2026). Even most current everyday workflows use AI, in the broadest sense of the word. Autocorrect and Word recommendations being the preeminent examples. But people must also avoid using AI to supplant the qualities of humanity. 

The Pope writes:

“The brain needs to be used, so our intelligence must also be exercised a little so as not to lose this capacity,” — Pope Leo XIV (Mares, n.d.)

Even priests are failing to resist the productivity AI provides in writing their homilies, but Pope Leo XIV points out that a homily is all about sharing faith with one’s community. Musashi learns this exact lesson. His life was not satisfied by his impressive feats of strength, but rather the community he was able to build. On the contrary, it was his desire to dominate and put himself over others that brought him deep dissatisfaction. By choosing to outsource opportunities for connection, people fail to recognize why exactly its so important in the first place.

Modern technology is suffering from a user design problem. AI’s potential to revolutionize how people work and what new tasks are possible is incredible. Yet people remain alienated from its impacts. Its power is drip-fed to people in the form of constricted pricey large language models. Modern technology is developed and marketed as an alternative to humanity, not an augmentation to bolster humanity (Wong 2026). Further, proponents of AGI technology declare that the modern advancements of technology can not be provided without widespread human replacements that permit a small minority to develop these products (“The Education of a Libertarian” 2009), (Gebru and Torres 2024), (Goertzel 2015). It is precisely this limiting narrative that obscures the ways that AI can benefit most people. This is no accident. It is by design. Or, more generally, it is inevitable when the development and application of technology is primarily done by a small minority.

More important than the capability of the technology, AI fundamentally cannot be allowed to supplant the need for humanity in many spaces. As much as AI could be capable of making any critical decision, it can never overcome the fact that a human needs to hold the responsibility for the decision because, “A computer can never be held responsible.” (Bonderud 2025) As much as AI could write a homily, it will struggle to tackle the essence of faith as it can not contend with its own and others existence and experience of reality. Contrary to the narrative that tech companies paint, “slowing down” to get technology right for people is not an obstacle of innovation. Rather, it is essential that the human is an integral consideration of the technology if it is to be truly innovative in the social and existential sense. Especially now, people -- with their diverse experiences and interactions with the world -- are necessary to develop novel tools that take advantage of new AI technology. As the story of Vagabond illustrates, Mushashi’s fading relevance as a swordsman did not make him a victim of the story’s transitional era, but it was because he devoted so much time towards his art that he still found purpose and wisdom in his time. Similarly, Kojiro found fame and a place in the world through his unique swordplay that displayed playfulness and curiosity. Both characters remained influential figures worthy of remembrance precisely because they embodied human qualities, not in spite of them.

In a final example, the humble computer arguably had much of the same potential for exploitation that AI and other modern innovations have today. But it was precisely through analyzing what made computers powerful and how humans could support this (Man-Computer Symbiosis, n.d.) that computers became the ubiquitous and respectful (compared to AI) tools that we know today. In the problem of modern technology and user-design the individual seemingly has an overwhelming challenge to overcome. But, thanks to the innovations of the past and the powerful computational systems of today, it has never been easier for an individual to make an impact. Whether its in novel ways like developing new open-source solutions, developing sociological models to understand AI agent dynamics, or even going through more traditional routes such as policy advocacy both online and in-person, it has never been easier to learn, develop, and make a change to the way the world works. People must reaffirm curiosity and ownership towards user-centered technology to bridge the massive design gap between modern technology and societal problems. As the story of Prometheus reminds us, AI and ML can not be treated as something to be afraid of, something to be ignored, or something to be delegated to those who will fit it. Because if the lofty promises of technology are to be accomplished and experienced by the most people, then it will not be by the efforts of frontier labs or an empowered monopoly. Rather, it will be the people of diverse professions, experiences, and communities who will accomplish this.

References

Acemoglu, Daron, and Simon Johnson. 2024. Power and Progress: Our Thousand-year Struggle over Technology and Prosperity. Public Affairs.

“A.I., Journalism and the Uncertain Future of the Public Square.” 2026. In The New York Times Company.

Avila, Artur, Manjul Bhargava, Caucher Birkar, et al. 2026. A Severe Misalignment of AI in Mathematics. Zenodo. .

Bonderud, Doug. 2025. AI Decision-Making: Where Do Businesses Draw the Line?  IBM. Https://www.ibm.com/think/insights/ai-decision-making-where-do-businesses-draw-the-line.

Botta, Marco, and Klaus Wiedemann. 2020. “To Discriminate or Not to Discriminate? Personalised Pricing in Online Markets as Exploitative Abuse of Dominance.” European Journal of Law and Economics 50 (3): 381–404. .

Boudreaux, Donald J., and Roger Meiners. 2019. “Externality: Origins and Classifications.” Natural Resources Journal 59 (1): 1–34. .

Eisenstein, Charles. 2011. Sacred Economics: Money, Gift & Society in the Age of Transition. Evolver Editions.

Gebru, Timnit, and Émile P. Torres. 2024. “The TESCREAL Bundle: Eugenics and the Promise of Utopia Through Artificial General Intelligence.” First Monday, ahead of print, April. .

Goertzel, Ben. 2015. “Superintelligence: Fears, Promises and Potentials: Reflections on Bostrom’s Superintelligence, Yudkowsky’s From AI to Zombies, and Weaver and Veitas’s ‘Open-Ended Intelligence’.” Journal of Ethics and Emerging Technologies 25 (2): 55–87. .

Gwynne Dyer. 2005. War: The New Edition. Vintage Canada.

Inoue, Takehiko, Eiji Yoshikawa, Yuji Oniki, and Steve Dutro. 2025. Vagabond. VIZ Media, LLC.

Jumper, John, Richard Evans, Alexander Pritzel, et al. 2021. “Highly Accurate Protein Structure Prediction with AlphaFold.” Nature 596 (7873): 583–89. .

Kosmyna, Nataliya, Eugene Hauptmann, Ye Tong Yuan, et al. 2025. Your Brain on ChatGPT: Accumulation of Cognitive Debt When Using an AI Assistant for Essay Writing Task. arXiv:2506.08872. arXiv. .

Man-Computer Symbiosis. n.d. Https://groups.csail.mit.edu/medg/people/psz/Licklider.html.

Mares, Courtney. n.d. “Pope Leo Tells Priests Not to Use AI to Write Homilies or Seek Likes on TikTok.” Text. In National Catholic Reporter. Https://www.ncronline.org/vatican/pope-leo-tells-priests-not-use-ai-write-homilies-or-seek-likes-tiktok; National Catholic Reporter.

Micron Announces Exit from Crucial Consumer Business Micron Technology. n.d. Https://investors.micron.com/news-releases/news-release-details/micron-announces-exit-crucial-consumer-business.

Noble, Tori. 2024. “To Fight Surveillance Pricing, We Need Privacy First.” In Electronic Frontier Foundation. Https://www.eff.org/deeplinks/2024/08/fight-surveillance-pricing-we-need-privacy-first.

Rismanchian, Sina, Hasan Uzun, Jeffrey Matayoshi, Eric Cosyn, and Eyad Kurd-Misto. 2026. Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build. arXiv:2605.21629. arXiv. .

Roy, Katica. n.d. “66% of CEOs Are Freezing Hiring While Betting Billions on AI. It’s a Costly Miscalculation.” In Fortune. Https://fortune.com/2026/03/18/corporate-america-ai-hiring-freeze-workforce-architecture/.

Sheldrake, Rupert. 2012. Science Set Free: Freeing the Spirit of Enquiry. Coronet.

Stromberg, David, Victor Lei, and Yanhui Wu. 2026. The Generative AI Learning Penalty: Evidence from Chinese Secondary Education. {{SSRN Scholarly Paper}} No. 6868618. Social Science Research Network. .

“The Education of a Libertarian.” 2009. In Cato Unbound. Https://www.cato-unbound.org/2009/04/13/peter-thiel/education-libertarian.

Vaughan-Nichols, Steven J. 2026. “Linux Kernel Czar Says AI Bug Reports Aren’t Slop Anymore.” Software in Theregister. Https://www.theregister.com/software/2026/03/26/linux-kernel-czar-says-ai-bug-reports-arent-slop-anymore/5226256.

Washburn, Sherwood. 1961. Social Life of Early Man.

Watson-Fore, McKenzie. 2026. “CU Delays ChatGPT Rollout After Backlash over $2M OpenAI Deal.” In The Boulder Reporting Lab.

Weekend, -Andrew Corkery Andrew Corkery is a national affairs producer at PBS News. 2025. “How Online Retailers Are Using AI to Adjust Prices by Mining Your Personal Data.” Economy in PBS News. Https://www.pbs.org/newshour/show/how-online-retailers-are-using-ai-to-adjust-prices-by-mining-your-personal-data.

Wong, Matteo. 2026. “Sam Altman Is Losing His Grip on Humanity.” Technology in The Atlantic. Https://www.theatlantic.com/technology/2026/02/sam-altman-train-a-human/686120/.