This year will prove significant for Artificial Intelligence for many reasons. A political reason is the midterm congressional elections in the USA, which will determine, among other things, the future of federal and state regulations on AI applications and the conditions for financial speculation and investment in AI companies. The midterm results may be the reason the AI financial bubble bursts, but that depends on the outcome and its potential shockwaves for US politics, the court that currently dominates the AI race.

A secondary, symbolic reason is the fifth anniversary of UNESCO’s Recommendation on the ethics of AI, adopted by the organization’s 194 member states on November 23rd, 2021. How relevant is this document today, given our five-year experience with AI? And how influential has the official adoption of the Recommendation been in shaping AI’s current trajectory?

Of course, these questions cannot be answered definitively given the accelerating pace of the race for AI dominance. However, a brief reflection on the state of the 2021 UNESCO goals in comparison with the empirical realities of early 2026 may help demonstrate why such questions are worth asking.

To make the comparison clear, I will utilize the conceptual framework of my book “Artificial Intelligence and Barbarism” [Athens School, 2025] as a resource for understanding the “mythinformation” and political control mechanisms that underlie seemingly neutral technological advancements.

I adopt the concept of “mythinformation” from Lagdon Winner, who coined the term in 1984 to describe the almost religious belief that the widespread adoption of computers and increased access to information will automatically lead to a better, more democratic world. I think the scope of the concept should be broadened to include the forty-year experience we have gained.

In this historical context, mythinformation is the ideology that equates the expansion of digital information with the expansion of truth, freedom, and social progress. It is the belief that more data produces more knowledge, more connectivity produces more democracy, and more information access produces more autonomy. Moreover, mythinformation transforms technological infrastructures into cultural myths, concealing the power relations, biases, and economic interests embedded in digital systems, and preventing critical reflection on the limits of information-centric thinking.

On that note, we should remember that the UNESCO General Conference’s adoption of the Recommendation was intended to establish global consensus on the ethical governance of AI, grounded in international law and focused on human dignity. It is an anthropocentric document that underscores the potential impact of AI:

“Guided by the purposes and principles of the Charter of the United Nations”, it recognizes the multilevel risks of AI technology, “on societies, environment, ecosystems, and human lives, including the human mind, in part because of the new ways in which its use influences human thinking, interaction, and decision-making.”

The Recommendation was designed as a framework for regulating policies to prevent AI’s catastrophic impact on the social and natural environments. Conceived as a proactive political and legal tool to address a multifaceted problem, the Recommendation defines AI systems by their capacity to mimic intelligent human behavior, including reasoning, learning, and planning.

However, in the five years since, a lot has changed. The most direct challenge to UNESCO’s Recommendation comes from its member states themselves, whose governments have started the AI dominance race. The Atlantic described it in 2026 as a high-stakes, $500B+ competition primarily between the US and China, with Big Tech (Amazon, Alphabet, Meta, Microsoft) projected to spend over $650B on infrastructure. The Recommendation’s voluntary character guaranteed as much. The AI dominance race is a direct effect of systemic technophilia, a dominant socio-political force toward digital barbarism and the delegation of human autonomy to algorithmic governance, exemplified by the Presidency of Donald Trump and the ascension of Big Tech figures like Elon Musk to governmental power.

Let’s look briefly at the policies of the Recommendation. The document designates eleven areas of policy action but I will just comment on some. [1]

The first and the second policy areas, “ethical impact assessment” and “ethical governance and stewardship” will be discussed later.

The third policy area, “data policy,” has already been compromised by Big Data, breaches of data privacy in LLM large-scale training, and the commodification of human intellectual property as raw material for Generative AI, exemplified by the case of Miyazaki’s Studio Ghibli, the data of which was sold by the Japanese government to OpenAI, thus igniting a global trend of Ghibli-like memes in 2025, despite the creator’s explicit objection to this.

Policy area number four, “development and international cooperation,” seems like a joke in our era of the AI dominance race between China, the USA, Russia, and, lately, the EU. UNESCO’s Principle of Fairness and Non-discrimination, alongside Policy Area 4, emphasizes that the benefits of AI must be shared equitably, with particular attention to low- and middle-income countries (LMICs). However, the UNDP 2025 report, “The Next Great Divergence,” warns that AI is sparking a new era of inequality. [2]

This informational inequality further deepens the power gap between the “Global North” and the “Global South”, reintroducing the exploitation structures of colonialism on another level, where private data becomes raw material for machine training, while human labor becomes devalued, and the local environment is devastated by mining and drilling.

Microsoft’s AI diffusion report, “Global AI Adoption in 2025—A Widening Digital Divide,” concludes that AI adoption in the Global North is growing nearly twice as fast as in the Global South, widening the usage gap from 9.8% to 10.6% between late 2024 and 2025. The IMF further warns that growth impacts in advanced economies could be more than double those in low-income countries, effectively eroding the labor advantages that once underpinned convergence. [3]

The most significant divergence between the 2021 UNESCO goals and the 2026 realities lies in Policy Area 5: Environment and Ecosystems, as expected.

The Recommendation mandates that AI actors reduce carbon footprints and prevent the unsustainable exploitation of natural resources. However, empirical data from 2025 and 2026 show an environmental cost that is rapidly escalating beyond sustainable limits.

The Cornell University study on the US data center boom provides a state-by-state look at the toll, projecting that by 2030, AI growth will add 24 to 44 million metric tons of CO2 to the atmosphere annually. The water use associated with cooling AI-focused data centers now exceeds global demand for bottled water, reaching an estimated 765 billion liters in 2025. [4]

This contradicts UNESCO’s goal of “Environmental and Ecosystem Flourishing” as an existential necessity for humanity and poses a significant threat to both society and nature. This means that the current trajectory of AI power dynamics poses a dual threat, both environmental and cultural.

The seventh policy area of UNESCO’s Recommendation focuses on culture and the values of diversity and inclusiveness, which are now being profoundly tested by the homogenization effects of large language models, as UNESCO itself warned recently.

In 2025, UNESCO’s CULTAI expert group report for MONDIACULT 2025 identifies “algorithmic homogenization” and the “outpacing of governance” as core threats to cultural pluralism. Linguistic diversity is a primary point of friction. Currently, fewer than 5% of the world’s languages feed the datasets of frontier AI systems, meaning the vast majority of linguistic worldviews are excluded from the platforms that increasingly structure global knowledge. [3] It seems that AI apps act as aggressive Anglicization machines that threaten the very cultural diversity of humanity. We should add to that the exploitation of cultural work without consent or compensation, which also affects individual privacy and collective memory.

The cultural impact of AI is not only felt across societies from the centers of power to the periphery, but also within society, from above to below.

The UNESCO goals for education in 2021, as explained in the eighth policy area of the Recommendation, focus on enhancing pedagogical integrity and ensuring that AI empowers rather than replaces teachers. In 2025, an UNESCO report found that classrooms have become spaces for “AI experimentation,” frequently without independent evidence of educational effectiveness. [5]

This poses a potential danger of individuals internalizing algorithmic norms. People begin to think, act, and perceive themselves through the logic of digital systems. Examples include optimizing one’s life like a dataset, measuring self-worth by metrics, and adopting algorithmic categories as personal identities. It is the psychological dimension of digital barbarism—the point where external systems become internal habits.

Digital barbarism names the condition in which technologically advanced societies regress in their capacity for judgment, autonomy, and critical thought. It is not a return to chaos, but a new form of domination produced by algorithmic rationality itself.

Of course, this is the opposite direction of the Recommendation’s proclaimed principles which are firmly grounded in digital humanism:

“13. The inviolable and inherent dignity of every human constitutes the foundation for the universal, indivisible, inalienable, interdependent and interrelated system of fundamental rights and freedoms.”

There seems to be an antithesis of values between UNESCO’s Recommendation and the actual objectives of the large companies that run AI applications, specifically LLMs. The necessary infrastructure to support LLMs relies on vast data centers and a capitalist business model that is extractive, centralized, resource-intensive, and oligarchic. On the social level, it introduces a new, aggressive form of financial exploitation of both communal and natural environments. On the political level, it promotes autocratic and oligarchic forms of governance that facilitate and reproduce capital flows toward the technocratic elites who provide AI. We see that these trends are dominating the politics of the Western world as we witness the devaluation not only of UNESCO’s adopted Recommendation but of the UN as such.

Moreover, the Recommendation failed to curb or even limit the spread of mythinformation about the “messianic” properties of AI, which was promoted by those who would stand to benefit the most. CEOs of multibillion-dollar AI enterprises are seeking financial investment. In January 2025, Sam Altman of OpenAI claimed that “we are now confident we know how to build AGI.” This is a perfect example of mythinformation. Later that year, on August 7th, the release of GPT-5 was deemed a failure, proving that we are still nowhere near true AGI. On January 21st, 2026, Sir Demis Hassabis, CEO of Google DeepMind, admitted on a CNBC podcast that current LLMs are excellent at pattern recognition but fail to grasp causality.

Nevertheless, the Recommendation seems to be challenged by the technological developments in AI as well. The transition from reactive Generative AI to agentic AI in late 2025, characterized by the development of autonomous systems based on LLMs that are capable of setting independent goals, executing multi-step plans, self-correcting, and revising their plans accordingly with no human supervision. These are proactive AI models that are goal-oriented and interact with their environment in a perceptive and active manner. They are designed to maximize autonomous functioning and limit human oversight. But as such, they are by design in opposition to UNESCO’s Recommendation on the necessity of human oversight:

“35. Member states should ensure that it is always possible to attribute ethical and legal responsibility for any stage of the life cycle of AI systems, as well as in cases of remedy related to AI systems, to physical persons or to existing legal entities. Human oversight refers thus not only to individual human oversight, but to inclusive public oversight, as appropriate.”

While the Recommendation covers stages from research to disassembly, the non-linear nature of 2026 AI development, in which open-weight models like DeepSeek-R1 are fine-tuned across borders and deployed as decentralized agents, complicates the attribution of ethical and legal responsibility. Agentic AI marks a significant step in the process Luciano Floridi has called the decoupling of Agency and Intelligence, a trend reinforced by the decoupling of Agency and Responsibility.

As AI agents increasingly operate in “blended teams” alongside humans, the Recommendation’s insistence on “final human determination” for life-and-death decisions faces technical friction. By 2026, there are projections that 40% of enterprise applications will embed AI agents, up from less than 5% in 2025, suggesting that human oversight is being architecturally refactored into “supervised autonomy” rather than direct intervention. [6]

This raises the prospect of replacing democratic deliberation with algorithmic governance. Algorithmic governance is the delegation of social, economic, and political decisions to automated systems. It includes predictive policing, algorithmic credit scoring, automated hiring, content moderation, and behavioral nudging. This form of governance is characterized by opacity, power asymmetry, and the displacement of public deliberation by technical procedures.

But before we become alarmists or succumb to the popular trend of adversarial technophobia, we should maintain our technoskeptic stance, focusing on the realities of our time rather than dystopian projections.

Technoskepticism is a critical stance toward technology that rejects both naïve technophilia and reactionary technophobia. It insists that technology is never neutral, that digital systems embody political and economic interests and that philosophical critique is necessary for democratic control of innovation.

We should always keep in mind that behind AI technologies are old-fashioned power dynamics, which means the social-historical field of interaction, where collective activity can change the tides. There is an opposition of values and principles between UNESCO’s Recommendation and global politics, but UNESCO is far from being an anti-systemic organization. It is part of the same global governance institutions that, five years ago, officially adopted this Recommendation along with its values and principles and which have now turned to technocratic autocracy.

Is this sign of state hypocrisy a balance of power that can be reversed?

Our critique advocates for a democratic digital humanism that entails a political critique of techno-capitalist networks, democratization of control over digital information flows, social regulation of AI technology, deepening of the radical political project of social autonomy, recreation of free public time and space, and a reevaluation of the individual as a citizen rather than a user.

Notes:

[1] UNESCO, Recommendation on the ethics of AI, adopted on November 23^rd 2021.

[2] https://www.undp.org/asia-pacific/press-releases/ai-risks-sparking-new-era-divergence-development-gaps-between-countries-widen-undp-report-finds

[3] https://www.csis.org/analysis/divide-delivery-how-ai-can-serve-global-south

[4] https://news.cornell.edu/stories/2025/11/roadmap-shows-environmental-impact-ai-data-center-boom

[5] https://www.unesco.org/en/articles/ai-and-futures-education

[6] https://machinelearningmastery.com/7-agentic-ai-trends-to-watch-in-2026/

The post The path of digital barbarism? Remembering UNESCO’s Recommendation on the Ethics of Artificial Intelligence, five years later. first appeared on Aυτολεξεί.

On January 14th, 2026, the World Economic Forum issued its Global Risks Report, a comprehensive official analysis of the potential risks facing the world in 2026. This influential document was produced exclusively by the World Economic Forum ahead of the WEF Annual Meeting 2026, convened under the theme “Spirit of Dialogue,” and held from January 19 to 23 in Davos, Switzerland. According to its editors:

“The Global Risks Report 2026, the 21st edition of this annual report, marks the second half of a turbulent decade. The report analyses global risks through three timeframes to support decision-makers in balancing current crises and longer-term priorities.” 

Among the numerous potential dangers lurking in the future, the document places special emphasis on the expansion of Artificial Intelligence, and for good reasons. The findings of the GRR 2026 are indications of the rise of digital barbarism, which I have defined, in the context of my analysis of Digital Reason, as the systemic erosion of social meaning and temporal autonomy caused by the dominance of algorithmic rationality. It manifests when computational systems reorganize the conditions under which individuals and collectives interpret, act, and imagine.

To summarize the argument of my recent book “Artificial Intelligence and Barbarism: A Critique of Digital Reason”, AI must be understood not as an autonomous agent but as an expression of the dominant imaginary significations of contemporary society. The digital revolution is not merely technical; it is an ontological transformation that reshapes meaning, subjectivity, and social time.

But this has reached new heights after the rapid digital transformation during the pandemic, the public release of ChatGPT in November 2022, and the fast and vast proliferation of AI applications across all domains of social life.

The World Economic Forum’s GRR 2026 acknowledges that:

“AI has shifted from a frontier technology to a systemic force shaping economies, societies, and security. The global market size for AI is projected to rise from an estimated $280 billion in 2024 to $3.5 trillion by 2033.” – GRR2026: 60.

It seems like we have entered a new phase of the digital ontological revolution, Web 4.0, the “intelligent” or “symbiotic” web, when AI comes onto the scene as an actor imitating and regenerating human communication. AI systems have permeated communication, labor, education, and governance, while public discourse has polarized into technophilic celebrations of progress and technophobic fears of collapse.

Both trends rely on hyperbolic narratives that obscure the deeper social‑historical dynamics at work. They emerge from an imaginary dominated by instrumental rationality, efficiency, optimization, and quantification. It is the capitalist social imaginary stemming from the Cartesian imperative to “render ourselves the lords and possessors of nature.” [Descartes 1635]

Uncritical technophilia is a core imaginary signification of capitalist modernity and, as such, was shared by some of the most critical adversaries of industrial capitalism, like Saint-Simon, Fourier, and, most importantly, Karl Marx. Castoriadis has pointed out that one of the conservative elements of Marxian thought is the acceptance of technology as a force of progress, and the tendency to “reduce production, human activity mediated by instruments and objects, labor, to ‘productive forces’, that is to say, ultimately, to technique.” [The Imaginary Institution of Society, MIT Press, 1987: 19]

The digital revolution is thus a transformation of the symbolic field through which societies interpret themselves. AI becomes the privileged expression of this imaginary: a mechanism for prediction, control, and the automation of judgment, as the spearhead of capitalism’s drive toward the goal of total mastery of nature, both inanimate and human, by means of digitization. Digital barbarism cannot be understood without reference to these imaginary significations.

The horizon of digital barbarism is not chaos but hyper‑order: the submission of social life to algorithmic governance based on automated parameters detached from human meaning.

The rise of mythinformation  

The GRR 2026 is an official statement that underscores the dangers of digital barbarism and justifies our caution, beginning from the Introduction:

“Misinformation and disinformation and Cyber insecurity ranked #2 and #6, respectively, on the two-year outlook. Adverse outcomes of AI are the risk with the largest rise in ranking over time, moving from #30 on the two-year outlook to #5 on the 10-year outlook. “ – GRR 2026

Misinformation and disinformation on the cyberspace are the results of what Langdon Winner called “mythinformation” namely, “the almost religious conviction that a widespread adoption of computers and communications systems and broad access to electronic information will automatically produce a better world for humanity.” (Winner Bull. Sci. Tech. Soc . , Vol. 4, pp. Printed in the USA. 2070-4676/84 Pergamon Press, Ltd.582-596, 1984.)

The most direct and obvious effect of mythinformation is economic and directly linked with the surge of financial investments in AI companies.

Modern digital markets represent what Shoshana Zuboff calls “Surveillance Capitalism”—a new economic order that claims human experience as “free raw material” for commercial practices of extraction and behavioral modification. This represents a “coup from above” and a “digital dispossession” of sovereignty.

Drawing on Karl Polanyi’s “commodity fictions” (labor as life, nature as real estate, money as exchange), we can identify a fourth fiction: personal experience and individual behavior as market values. Through “individualization algorithms,” private companies reify personal experience, reducing individuals to measurable behavioral patterns for the purpose of attention-baiting and time consumption.

AI contributes to this dispossession through what Luciano Floridi calls “enveloping”. Rather than machines being made to inhabit the human world, social relations are transformed to accommodate AI applications. The danger is not “thinking machines” dominating humans, but the domination of society by political and economic mechanisms.

In 2025, stock markets were driven by political decisions regarding the financing of AI companies worldwide.

In the first week of his presidency, following his inauguration on January 20, 2025, D.J. Trump announced a $500 billion package for the development of digital technology.

A week later, two Chinese companies [DeepSeek and ByteDance, the owner of TikTok] presented TN models [LLMs] that operate at 50 times lower training costs.

On February 18, 2025, Elon Musk presented the latest Generative Artificial Intelligence model from his company xAI, Grok 3, which includes a chatbot, two reasoning models, and a digital research assistant, falsely claiming that it mimics “human reasoning.” It is powered by the xAI Colossus supercomputer, with 200,000 graphics processing units [GPUs], and has been pre-trained for 1,000,000 GPU hours. It is located in Memphis, and the system consumes 18,927,058 liters of water per day for cooling. It was built in less than eight months and includes large energy facilities for the power-hungry digital system.

During the summer, President Trump decreed that AI companies could fund their own energy facilities using federal resources.

With a presidential decree on December 12, 2025, Trump suspended the States’ right to enact regulatory laws and legislate restrictions on artificial intelligence companies.

Among others, the above political – and not scientific – events helped the investments in AI companies skyrocket:

“Total spending on AI worldwide is estimated at $1.5 trillion in 2025 and is projected to rise to $2 trillion in 2026, with the main segments being generative AI (genAI) smartphones, AI-optimized servers, AI services, AI application software, AI processing semiconductors and AI infrastructure software.68 The data centre capex of the top eight US hyperscalers (very large cloud services providers) alone amounted to $258 billion in 2024 and is projected to more than double to $525 billion in 2032.6” – GRR2026: 44

However, the promises for AGI failed to materialize, and fears for a potential economic bubble started manifesting.

As the GRR2026 points out, this surge in capital investment poses a significant danger:

“There is currently widespread concern around elevated equity prices for the largest technology companies, and 2025 saw periods of frenzied investor interest not only in artificial intelligence (AI)- related stocks, but also in sectors such as nuclear, quantum or rare earths. A sharp run-up in the prices of precious metals has raised concerns of bubble-like activity there, too. Some of these prices have since stabilized or corrected, but concerns about overvalued markets remain. Should the predictions of an asset bubble burst turn out to be true, the potential impacts can be significant. Global institutional and retail investors are heavily invested in US stock markets by historical standards, so the resulting potential impacts of a crash could be severe for the global economy;63 85% of global chief economists in September 2025 believe a financial shock would have wide-ranging systemic effects.” – GRR2026 

The WEF verifies the picture of a vicious financial circle, as Dr.Alex Pazaitis described it in an online discussion: the revenues of companies that develop AI models for the market are meager compared to their ever-increasing commitments to spending and investing in more computing power. So their funding continues with money they receive from “investments” from companies such as NVidia, from which they then purchase processors. NVidia simultaneously “invests” capital in companies that provide cloud computing infrastructure, such as Oracle, which then purchases processors from NVidia to offer services to companies such as OpenAI to host their model data. And the cycle of self-referential investments goes on and on.

We may call this the economic vicious cycle of self-referential investment.

This vicious cycle of self-referential investment can go on for a while until the bubble bursts due to the accumulation of political capital by AI companies owned by influential political actors like Elon Musk. This only expands the vicious circle to include other areas of communication, space travel and transportation and widens the area of influence of digital mythinformation.

The concentration of political and financial capital, computational power, user data, and digital technology in a handful of companies creates a steep hierarchical pyramid of informational power that widens the gap of inequality on both a social and international scale. The GRR2026 notes the uneven distribution of power regarding AI:

“Access to AI infrastructure as well as to electricity, internet access, and data storage will amplify economic power shifts between countries over the next decade as AI’s productivity benefits bypass some populations entirely- albeit protecting them from some of the risks. For example, AI adoption in North America (27% of the working-age population) is triple that in Sub-Saharan Africa (9%).

Only a handful of AI data centres are in developing regions, with the United States, Europe and Eastern Asia dominating capacity. Within countries, the gap between AI-integrated geographies and excluded peripheries may also drive localized power shifts, create internal migration pressures and destabilize national cohesion.” – GRR2026

This marks a significant widening of the post-colonial power gap between Western/Eastern techno-capitalist countries and the impoverished countries of the global South. But it also marks a widening of the internal gap of equality between governing elites and working classes within each country.

The GRR2026 devotes a whole section [2.7] to discussing three sets of risks connected to AI applications:

“First, the widely cited concerns around the impact on labour markets could lead to deepening societal polarization if unemployment rises and workers struggle to adapt to new tasks and roles. In such a scenario, both higher productivity and higher unemployment could unfold simultaneously.”

Mark this sentence: higher productivity with higher unemployment. This is a direct consequence of the expansion of automation across all social functions that can be reduced to algorithmic functions. It also seems in alignment with the core imaginary signification of the neoliberalist dogma of capitalism that emphasizes profit over production, while also being the realization of the imaginary signification of technocracy, the diminishing of the human factor in production.

Of course, the outcomes are societal disruption, mass unemployment, mass poverty, the sudden devaluation of the significance of labor, and the rupture of social bonds.

We may call this the political vicious circle of systemic inequality on a domestic and international level.

Even so, we should widen the definition of systemic inequality to include ecological devastation, which may affect all, but not all have the means to mitigate the catastrophe on public health and living conditions. GRR2026 notes the environmental risks of AI:

“There are second-degree physiological health impacts as well, deriving from the environmental impacts of generative AI models. These can consume up to 4,600 times more energy than traditional software.162 AI-related infrastructure can result in degraded air quality and pollution from manufacturing, electricity generation and e-waste disposal. In the United States alone, this could impose a public-health burden of over $20 billion annually by 2028” – GRR2026: 54

Such are the ramifications of instituted mythinformation around the commercialized future projections of AI on the external social domains of economy, ecology, and politics. But these effects are reflected and doubled in the internal private domains of intersubjective communication and reality perception.

The risks of mythinformation loom even greater in cyberspace than in stock markets. Cyberspace, as a new sphere of being, represents a form of alterity (otherness) where the subjective and objective merge in a virtual subjective objectivity. This suggests that the Internet doesn’t just mediate our existing communications; it creates an intermediate digital layer with unique epistemological attributes and possibilities, where telepresence presupposes physical absence and communication is reduced to syntax. These underline the epistemic risks of AI.

Second, as more tasks become undertaken by AI and previously applied human skills begin to atrophy, it is unclear if the path forward will be a golden age for creativity, leisure and learning – or, conversely, a drift into purposelessness, apathy and societal decay.” – GRR2026

Large Language Models introduce a new epistemic instability. Their outputs are plausible but unreliable, often exaggerating or distorting conclusions. As they infiltrate education, research, and policy, they threaten to automate epistemic error at scale.

If AI is a form of immature intelligence, lacking understanding and accountability, entrusting it with critical public functions becomes dangerous. The risk behind mythinformation is the delegation of judgment to algorithmic systems.

In the age of AI mythinformation spreads rapidly through attention-optimized platforms, displacing reasoned discourse and eroding the public field of communication on a global scale via digital social media. The increasing reliance on AI apps for the production of common knowledge has begun to threaten the public’s common sense of reality.

“Increasing reliance on both social media and AI tools enhances the impact of algorithmic bias, which shapes what information users see online and reinforces exposure of individuals to information aligned with their views. This can create widely divergent perspectives on real-world events and developments. The impacts are starting to run even deeper. How real-world events are interpreted online combined with the growing circulation of violent content on social media may be leading citizens to become more emotionally and cognitively detached and numbed to human tragedies.” – GRR2026

We must stress that, given the global public’s reliance on mythinformation, the common sense around reality is easily manipulated by means of propaganda, even before AI. Nevertheless, we must observe that the penetration of the digital field into the social imaginary is so deep that AI apps are also transforming the sense of reality in scientific terms.

The above concern is justified given the sheer volume of scientific papers and informative material currently produced by Generative AI models. This is already happening in the fields of academic knowledge production, as in the case of digital fossils. A digital fossil is an old error preserved in files used as AI training data and unexpectedly reproduced automatically in new results.

However, digital fossils are an unwanted byproduct of LLMs. We should consider them as indicators of a broader epistemic erosion of public knowledge.

This epistemic erosion goes deeper than public discourse, since digital media and AI applications aim at personification and private interaction by design. Cyberspace gives the false impression of a digital public space, while it is more of a network of interconnected virtual private spaces. Every user communicates in the mode of telepresence via digital personas, from their own private time and space, even when they are in public. If you add AI chatbots to the other side of telecommunication, every user can be caught in a web of self-referential pseudo-dialogue. At that point, traditional intersubjective communication networks collapse into dead-end repetitive monologues between subjectivities and machines.

“A society where large segments, especially young people, subsist on UBI could experience a crisis of meaning.” – GRR2026: 63

As a result, a fragmentation of the public common sense of reality may lead to the collapse of the coherence of social imaginary significations and common values. A constant flow of unchecked information leads to the blurring of the distinction between fact and fiction.

This forms an ideological vicious circle of misunderstanding. The effect of this would be felt socially as the shrinkage of public space and time and the proliferation of conspiracy theories and other fringe narratives. This is not a fictional scenario, but a real-life danger, illuminated by the GRR2026 with a focus on electoral consequences:

“Recent elections in the United States, Ireland, the Netherlands, Pakistan, Japan, India, and Argentina have all had to contend with such fabricated content on social media, depicting fictional events or discrediting political candidates, blurring the line between fact and fiction. As AI is used to make such content more personalized and persuasive, there is a risk of greater impact on elections. For example, research has found that 87% of people in the United Kingdom are concerned about deepfakes affecting election results. But while awareness is high, many lack confidence in their abilities to identify when content is manipulated.”

But there are still broader dangers along epistemic erosion as GRR2026 admits:

“In an extreme scenario, control over many aspects of society could be ceded to AI.” – GRR2026

This is the nightmare of algorithmic governance in terms of technocratic absolutism, and also the fantasy project of billionaires like Elon Musk and Peter Thiel, spelled out in a most official policy forecast, like GRR. But it is not the worst scenario described by the Review. The third set of risks involves the envelopment of the industrial-military complex within the AI technosphere:

“Third, with militaries’ reliance on AI systems continuing to increase, the potential for misuse or mistakes will rise, too, placing human lives directly at risk.” – GRR2026.

No need to comment more or elaborate on that dismal future perspective, without risking delving into a technophobic dystopia.

Nevertheless, technophobia, once more, seems reasonable, once we notice the WEF’s conclusion on the potential risks of AI for 2026:

“What distinguishes AI-driven disruption from previous technological transitions is the potential for cascading failures across interconnected domains. Labor displacement ripples widely, into households, communities and political systems. Lack of economic opportunity or unemployment (ranked #14 in the GRPS 10-year ranking) can drive extremism; institutional distrust is interlinked with misinformation and disinformation; and surveillance empowers authoritarian responses to the instability that AI creates. Once established, these loops could become self-reinforcing.” – GRR2026

What the WEF describes is what I have called Digital Barbarism. Is this the only potential future?

The GRR2026 concludes by encouraging state governments to coordinate on strict measures and regulations, warning that AI should be considered as high a threat as nuclear weapons and biochemical weapons:

“Coordination on minimum safety, transparency, and ethical deployment standards, particularly for military, biometric, and large-scale decision-making systems, is needed – yet requires cooperation similar to that for nuclear or bioweapons safeguards.” – GRR: 66

This vague, conclusive suggestion makes the reader wonder if the authors read the previous pages of the document, where the lack of such coordination is mentioned as the cause of the problem in the first place.

The case for democratic technoskepticism

While its infrastructure is physical, cyberspace is a field of intersubjective communication where human subjects are the real nodes of meaning-making. The boundary between the digital and the real is a “porous membrane,” meaning digital actions have direct social-historical consequences.

By acknowledging the “ontological duality” of the digital sphere—where models are communicative practices—we can bridge the gap between code and practice to build autonomous institutions.

The dominant discourse on AI oscillates between two exaggerated imaginary trends of instituted Technophilia – AI as salvation, optimization, transcendence – and popular Technophobia – AI as domination, displacement, apocalypse – which both share the common ground of technological fatalism.

Both trends obscure the fact that AI is a statistical mechanism, lacking interiority, intentionality, or autonomy. AI can be understood as a non-subjective statistical pattern manipulation machine, a computational tool, a being-by-and-for-another incapable of being‑for‑itself.

Democratic Technoskepticism offers a third path. It rejects both utopian and dystopian fantasies and situates AI within the power structures, ecological constraints, and symbolic significations of contemporary society. Grounded in digital humanism, technoskepticism affirms the primacy of human autonomy and democratic oversight.

Digital commons serve as a “practical paradigm” for “digital repossession”. They materialize values opposed to capitalist norms, such as reciprocity, equity, solidarity, and self-management. In the digital commons, exchange is not money, labor is not exploited, and experience is not reduced to data points.

By ‘practical paradigm’ I mean, as opposed to theoretical paradigms, a model that can be implemented practically, thus creating a network of human activities towards common goals. This bridge between code and practice is possible thanks to the ontological duality of the digital sphere, where models are communicative practices and not just abstractions. As such a ‘practical paradigm’, it can be developed further into the communicative modality of social institutions of social liberty, justice, social autonomy, revocability, equality, inclusivity, self-government, and cosmo-localism, both in the sphere of common design and production, but also in the sphere of cultural discourse and co-creation. The rooting of digital commoning into physical social-historical reality opens possibilities for a wider radical social transformation through the combination of digital communing with practices of grassroots democratic politics and social ecological communities. This combination implies the co-joint recreation of an autonomous free public space and time, both in the digital and physical realms of human co-existence.

In hierarchical systems, information is extracted from below, and commands are issued from above. Digital commons allow for the “reversal of the flow,” where political decisions are issued by the social basis, informed by transparent, second-order institutions of data-processing. This creates an autonomous digital public space and time that supports direct democratic horizontal networks.

Contemporary democratic social movements, characterized by their sustained collective claims and unique “repertoires” of dissent, provide the physical counterpart to digital commoning. Unlike authoritarian movements (e.g., “Trumpism”) that use digital networks for top-down propaganda, democratic movements emphasize communal assemblies, direct democracy, and the refusal of hierarchical authority.

We could imagine Technoskepticism like a theoretical telescope – it helps us discover potential breaches of democratic rules and violations of human rights on the horizon of future expectations. Digital humanism is like a political compass— it helps us navigate toward a democratic common future. Digital Humanism builds on the concerns raised by technoskepticism, offering solutions and design principles. It embeds principles of direct democracy, digital commoning, and social ecology into technological development.

Temporality and community are the key conditions for these acts of dispossession or repossession. In that framework, the individuals who allow their personal time to become colonized, co-opted, and absorbed within the dominant rhythms of social -networking, profile influencing, and digital marketing contribute to the expansion of the networks of capitalist dispossession actively, by becoming proponents of their marketing model. In the digital world, models are practices and the capitalist terms of digital representation are terms of individual commodification. These digital netizens are the innovators and influencers of capitalist post-modernism; they are the new entrepreneurs that exploit and are exploited, they are actors of the dispossession machine. Therefore, they create consumerist communities, which function as operators and accelerators for the circular, repetitive temporality of dispossession; incursion, habituation, data reification, and public diversion.

This cycle feeds the multiplication of social crises through the spread of individualistic consumerism, political apathy or fanaticism, proliferation of advertising strategies, and the reification of personal experience. Time and community in the form of personal engagement and collective experiences are the new commodities, fragmented under the fictitious principle of digital individuality.

On the contrary, the praxis of digital repossession is constituted by the creation of a free common temporality via the tools provided by social ecology, digital commons and the emancipation of human subjectivity within open, horizontal, and democratic communities.

The current crisis of AI and surveillance capitalism presents a choice between two paths: one of automated “envelopment” and another of collective “repossession.” By rooting digital commoning in social-historical reality, we can reclaim the digital sphere as a field for “poetics/acting”—a space where human subjects define their own purposes. This project of social autonomy aims for a post-capitalist, ecological, and humanist future where technology serves to enhance, rather than replace, human agency and democratic self-governance.

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Introduction

As we move deeper into an era of algorithmic governance, technoskepticism has evolved from a niche critique into a vital survival strategy. Despite the noticeable limitations of current AI technology, from hallucinations to ecological destitution, modern societies have irreversibly crossed the threshold of the so-called Fourth Industrial Revolution [Industry 4.0], which is the current phase of the digital ontological revolution that began in the last years of the 20th century and is rooted in Tim Berners-Lee’s idea of the Semantic Web. However, digital technology is moving away from this initial sociocentric idea, toward AI integration and automatic administration.

Since 2016, the global pandemic of 2020 and the subsequent shutdowns have accelerated the digital envelopment of capitalist societies worldwide, with major sectors of governance, social services, and market transactions moving to the digital sphere. For a brief period, social interactions and social communications became solely digital telecommunication, and even after the shutdowns, a significant portion of human interaction became digital in a more permanent manner.

In late 2022, just over a year after the pandemic, the launch of OpenAI’s ChatGPT introduced LLMs to the broader global public, leaving most stupefied. Since then, AI technology has taken hold of social imagination, fermenting both dreams and nightmares.

In February 2025, the DISCO Network released their book “Technoskepticism, Between Possibility and Refusal” as a survival strategy for marginalized groups against systemic inequity.

In the framework of the DISCO Network, every piece of software carries the baggage of its creators’ biases—a reality that necessitates a strategy of ‘informed refusal.’ This mirrors my own concern regarding Digital Reason: the way algorithmic logic colonizes our public time, transforming shared social experience into a series of quantifiable, extracted data points.

In my recent book, Artificial Intelligence and Barbarism: A Critique of Digital Reason (Athens School 2025, Athens), I propose we search for a middle road, based on public reflection and informed criticism, that I also called Technoskepticism.

 The consensus is clear: we must be skeptical of Artificial Intelligence and see technology as inherently linked to power. We must recognize that technology is never a neutral container.

However, I call for a more political and ontological conception of democratic technoskepticism. To properly explain what I mean, I should first define technoskepticism against the opposing extreme positions of technophilia and technophobia.

Technophilia against technophobia.

Dreams of human liberation from menial labor via technology have tormented the social imagination at least since the time of Aristotle, who asserted that mechanical statues could replace slave labor if they would follow commands [Politics 1253b53]. However, in modernity, they became inexorably entangled with the ambition of rational domination over nature, formally expressed by Descartes in 1635, when he aspired to total knowledge that would “thus render ourselves the lords and possessors of nature.” [Descartes 1909]

Castoriadis observed that Descartes is not merely expressing a personal desire for the total understanding of nature, but rather gives literary form to the emergence of a novel social-historical representation of being, “whereby all that is ‘rational’ (and, in particular, mathematizable), that which is to be known, is exhaustible de jure, and the end of knowledge is the mastery and the possession of nature” [1987: 272]

The imaginary impetus behind the development of AI technology is the spearhead of capitalism’s drive toward the imaginary goal of total mastery of nature, both inanimate and human, by means of digitization.

Expectations around AI are developing way faster than the actual technology, but along with expectations, investments also increase, and AI companies in recent years are the most highly financed businesses worldwide.

This is the main reason why AI expansion is increasing, because it is driven by an explicitly political desire of techno-capitalist elites that are eager to cash in on AI’s capacities in surveillance, classification, personalization, manipulation, and monitoring of the global consumer populations privately.

This political force, personified by the President of the U.S.A. D.J. Trump and his government has helped AI companies overcome social and political obstructions and more or less obscure the public awareness of AI’s deep and irreversible impact on both the natural and societal environment. Governments and state authorities worldwide promote and enforce the official structural version of what I would call technophilia, the idea that technology will bring forth utopian, however one imagines it. We could say it is a form of instituted technophilia from above, expressing the ambitions and interests of the upper echelon of social hierarchy.

One the opposite side stands the growing trend of technophobia, spreading across pop culture, social media and public imagination, that is deeply rooted in the nightmarish social cost of the Industrial Revolution and the fear of enslavement by the machines that combines the social-historical experience of the working classes and colonized people with hellish representations of a dystopian enslaved humanity across popular arts, cinema, literature and mass media. Perhaps the most famous iteration of technophobia regarding AI came from Dr. Stephen Hawking, who said:

“Once humans develop artificial intelligence that would take off on its own and redesign itself at an ever increasing rate, humans who are limited by slow biological evolution couldn’t compete and would be superseded.”

Technophobia is not restricted to the lower classes of society but is widespread across the social spectrum, without any authoritarian political or economic center behind its spread. It is more of an expected social reaction, given the gap between the technical knowledge and future objectives of the techno-scientific apparatus and the public’s fragmentary opinions around technology. But when this sentiment comes also from people who belong more or less, to that same techno-scientific environment, like dr. Hawking, one cannot simply dismiss it like a popular misconception.

From Gaza to the USA, AI applications have been used by state authorities, private companies, and unknown actors to monitor, classify, target, influence and manipulate populations, voters and individuals, in a way that directly compromises public discourse and dilutes common knowledge by the spread of mythinformation, deep-fakes, and AI-generated images of a distorted view of reality.

Image has been used for propaganda of the dominant imaginary significations since the dawn of society, given that dominant imaginary significations are formulated into social representations and that meaning is always represented symbolically.

But with the advent of LLMs, we have automatic generators of highly realistic images in an instant, and we also have the means, the Internet, for their unchecked proliferation on a global scale. In such a time, technophobia seems reasonable. However, it is a trend based on sentiment, not logical thinking. There is no turning back to the pre-digital world, albeit by a worldwide catastrophe, which no one would desire. We should be cautious of technophobia for its inherent reason, taking note of the fact that it can lead to the path of irrationality and the complete dismissal of scientific research and rational critique.

Moreover, we should be able to discern that behind their explicit opposition, both trends share an implicit imaginary schema: the conception of technological progress as an extra-historical force that moves the world towards an inescapable future of machine dominance, rising above current political fissures. From this stems the principle of the subordination of politics to technology, which has been given expression in the ideology of technocracy, that is already a century old.

Professor P. Noutsos informs us that the terms “technocracy” and “technocrats” first appeared “in the United States during the interwar period, when liberalism was being challenged by both the conservative political forces of defeated Germany and the revolutionary centers of the “Communist International.”[…] “technocrats” were put forward as experts in accelerating technological development and the “rational” management of its fruits. In fact, the position of “technocracy” was strengthened by the economic crisis of 1929, which triggered the “New Deal” policy and legitimized increasing state interventionism in the unfolding of the functions of industrial capital.” [Noutsos, 1988]

AI enterprises and prominent far-right figures of the “Tech-Bros” oligopolies of Silicon Valley, like Peter Thiel and Elon Musk are the latest version of the technocratic ideology that advocates the transfer of political decision making to technical administration in the form of digital technocracy and technological accelerationism or, what has been called, in a rather pompous manner, technofeudalism, a modern economic system where big technology companies have power similar to feudal lords in the past. [Varoufakis 2024]

At this point, we can regard technocracy as both the imaginary final stage of instituted technophilia and the ideology of digital barbarism.

The philosophy of technoskepticism.

In my opinion, technoskepticism is a philosophical approach to digital technologies like Artificial Intelligence, based on social-historical criticism rather than blind acceptance or fearful rejection. It’s not anti-tech, but rather tech-aware. Technoskepticism is based on the notion that digital technology is a product of the dominant social imaginary of instrumental rationality that envelops our social-historical environment [Floridi 2023] by transforming it into a semi-digital sphere of telepresence. AI as a digital system has no interiority, hence neither intentionality. In terms of Digital Humanism, at the beginning and end of the system are human subjects and intentions with social significance performing institutional acts by means of technology.

In the beginning of the year, February 2025, the DISCO Network of researchers based in the U.S.A. released their book “Technoskepticism, Between Possibility and Refusal” (Stanford University Press 2025), where they advocate for a “survival strategy for marginalized groups navigating the space between “possibility” (using tech for care) and “refusal” (rejecting extractive systems).” They focus on systemic inequity and the lived experience of marginalized groups in the United States, shedding light on the use of technology to reinforce racist and colonial power structures. Their interpretation of technoskepticism is regional, topical, and aspires to empower communities to reclaim technology for their own interest, to bring forth “Justice within the Glitch”.

Nevertheless, besides sharing a common ground, there are differences in reference and scope between the DISCO Network’s interpretation of technoskepticism and my own. The DISCO Network’s version of technoskepticism is more specific to identity and lived experience in the US context (race, disability, gender) and is primarily about survival and care in the face of an unjust system. Their critique is primarily sociological and ethical, focusing on very important but regional issues like algorithmic bias, data extraction from vulnerable bodies, and surveillance, while posing the key question: How does technology disproportionately affect marginalized and historically oppressed communities?

 My own approach to technoskepticism is more ontological and political, rooted in the political philosophy of autonomy. I try to address the question: What does AI do to the core human capacity for self-determination and creating meaning (Autonomy)?

I focus on phenomena of the social imaginary like the replacement of political reason with technical calculation, that give rise to new forms of heteronomy (rule by external, non-human source) and the fear of social collapse into Digital Barbarism.

Digital Barbarism is the ultimate loss of Autonomy—our capacity as human beings to create our own laws, our own values, and our own collective meaning. AI, or “Digital Reasoning,” reduces the messy, complex, and unpredictable realm of human affairs (ethics, politics, culture) into calculable, deterministic variables. When collective decisions are delegated to the algorithm, citizens become subjects of Heteronomy—they are ruled by a non-human logic that they did not create and cannot contest.

The DISCO Network’s critique is crucial for understanding who the current AI system harms, but it often stops short of asking what the system itself is doing to our political humanity. This is the question at the heart of the European philosophical tradition. In my view, the meaning of technoskepticism is reclaiming the logos and the polis, subjecting technology to direct, public, democratic control.

This is decisive, given the ethical problems that AI technology raises. While we must continue to argue for an ethical framework in AI design and implementation and support global efforts to press governments into legislating a common set of rules and regulations across AI research and production, we should always keep in mind that the social-historical conditions are not favorable. Technology is dependent on authority and by definition authority prioritizes means of domination over common well-being. Ethics is dependent on politics on a deeper, institutional level and the balance of power shifts towards unregulated AI in terms of financial and political capital and given the ignorance of the broader public on issues of tech regulations.

During the last year, we have stood witness to political authority overcoming legislative barriers in favor of AI enterprises, but also directly attacking institutions of critical research and established ethical committees while using AI tools to influence public opinion and project imaginary power.

We should acknowledge that AI does not care about Ethics, because it is dependent on political authority that can easily shift any ethical responsibility evading legal repercussions.

We should acknowledge that AI does not care about ethics, because nothing ethical is intrinsic to digital technology. This is the reason why we should ponder on the political framework and the possible limitations that should be set to digital authority by civil society and grassroots social movements. This is why we need a political, democratic view of technoskepticism.

We could describe the core principles of Democratic Technoskepticism as follows:

1. Technology is not neutral: Technology reinforces power structures by embedding existing social, economic, and political hierarchies into its design, deployment and control. It’s not just about who builds the tech—it’s about who benefits from it, who governs it, and whose values shape it.
2. This lead to the need for critical engagement with the issues of technology: Instead of trusting tech because it’s new or rejecting it because it’s disruptive, we may ask deeper questions: Who benefits from this application? What values does it embed? What is the overall cost for its implementation on a social, ethical and environmental level?
3. Artificial “Intelligence” is not Intelligence: We recognize intelligence as a natural property that defines subjectivity, intentionality and rationality. However, subjectivity is a quality of the living being-for-itself.
4. A digital mechanism is, by definition, not a naturally self-creating individual but a modular inanimate object, a being-in-itself, with no subjective interiority. Current AI models based on LLM architecture are statistical pattern recognition machines. But even the alternative, world AI and neuro-symbolic AI architecture, suggested by Prof. Gary Marcus, would produce logistical algorithmic reasoning machines–in neither case a sentient self-referential conscious being.
5. Technoskepticism pushes back against the idea that efficiency, optimization, or scalability should be the ultimate goals of technology. It advocates for human-centered values, creativity, autonomy, and democratic public control of technology.
6. On this ground, Technoskepticism is based on Digital Humanism and the resistance to Digital Barbarism. Technoskepticism sees blind surrender to technological systems—especially those governed by opaque corporate and political interests—as the form of modern barbarism.

The solution must be political; therefore, fixing the symptom (bias, data extraction) is insufficient. We must confront the fundamental political form of the technology. Democratic Technoskepticism is the necessary intermediate path:

– It rejects the Technophilic idea that technological progress is inherently good.

– It rejects the Technophobic idea that we must abandon all machines.

– It demands that every significant technological choice must be wrestled away from technical experts and corporate interests and subjected to direct democratic deliberation by the citizenry. Technology must serve the polis, not the profit motive.

The horizon of democratic autonomy that spreads from care and justice to political liberation is what makes technoskepticism a powerful new direction for the debate. But we must always keep in mind that technoskepticism is complementary to the political project of social autonomy, which requires actual political participation in the actual public time and space in terms of direct democracy, commoning, and social ecology. We should not forget that democracy is not just information.

In conclusion

In my view, democratic digital humanism requires a fundamental shift in both our conceptual understanding of technology and our political structures, challenging the prevailing techno-industrial complex.

The key steps in a possible roadmap would involve:

1. Overthrowing the Regime of Mythinformation: The first political priority is to challenge and dismantle the corporate and political propaganda (mythinformation) that fosters “technophilia” and presents AI as a neutral, all-solving force. This requires critical examination of AI’s metaphysical claims to “intelligence” or consciousness.
2. Asserting Human Subjectivity and Agency: The roadmap underscores the indispensable role of the human subject—as creator, user, and signifier—at every stage of a digital system’s function. This means recognizing that natural intelligence is a uniquely human capacity that cannot be reduced to technical functions.
3. Achieving Social and Individual Autonomy: The ultimate goal is to move from heteronomy (being governed by external rules or technological systems) to autonomy (self-governance). This involves people collectively creating the institutions and rules that govern their own lives, including the role of technology within society.
4. Implementing Direct Democratic Control: The core of the political roadmap is a commitment to direct democracy. The ultimate question is political: “Who controls the providers of AI?”. This control must be vested in the people through participatory, grassroots democratic processes, rather than leaving it to corporations or centralized state bureaucracies.
5. Integrating Theory with Praxis: The philosophical framework is designed to be an active guide for real-world application, linking philosophical inquiry with social movements and struggles for emancipation. The aim is to empower informed decision-making and contribute to a more democratic digital future.

Democratic technoskepticism offers a vision where technological development is not an end in itself but a means to foster an autonomous society based on humanistic values, critical thought, and democratic self-governance.

 References:

Castoriadis, C. (1987). The Imaginary Institution of Society, transl. K. Blamey, Polity Press 1987, New York.

Descartes, R. (1909). Discourse on the method of rightly conducting the reason and seeking the truth in the sciences, edited by Charles W. Eliot. Published by P.F. Collier & Son, New York.

Floridi, L. (2023). The Ethics of Artificial Intelligence: Principles, Challenges, and Opportunities. Oxford University Press.

Marcus, G. (2019). Rebooting AI, Pantheon Press, New York.

Noutsos, P. (1992). Η Σοσιαλιστικη Σκέψη στην Ελλάδα, τ. Γ’, Gnosi ed., Athens.

Schismenos, A. (2025). Artificial Intelligence and Barbarism: A Critique of Digital Reason Athens School, Athens.

Varoufakis, Y. (2024). Technofeudalism What Killed Capitalism. Vintage Books, London.

Conceptual Map:

A structured mapping of “Artificial Intelligence and Barbarism”, tracing the dialectical paths between digital reason, algorithmic domination (Barbarism), and the potential for democratic, commons-based autonomy (Humanism).

The post AI doesn’t care about Ethics: Why technoskepticism must be political first appeared on Aυτολεξεί.

A review of Alexandros Schismenos. Artificial Intelligence & Barbarism: A Critique of Digital Reason. Athens, Greece: Athens School, 2025.

Alexandros Schismenos, the outstanding Greek scholar of philosophy who has written insightfully on Cornelius Castoriadis and Martin Heidegger, continues his inquiry into vibrant themes of social and political significance. There is a search to renew the human prospect by reinvigorating autonomy (popular self-directed organization). And an impending confrontation with the reality of a decline in culture, merit, and civilization-ethics from a working class and democratic point of view.

His latest book on artificial intelligence (or A.I.) suggests a critique of digital reason where not simply unknown advantages and disadvantages are along the road ahead. But there is likely a barbaric fate in front of us. It is crucial to learn with Schismenos why this is so.

Advantages and Disadvantages? Likely A Barbaric Fate Ahead

Whether we see A.I. in ChatGPT, robots (from factory assembly lines to caregivers to intimate partners), algorithms mirroring our likes and desires back to us, self-driving cars, retail customer assistance chatbots, digital assistants (from Siri to Alexa) for navigating roads and playing music, facial recognition for security systems, medical diagnosis, surveillance and fraud detection, virtual travel booking agents, playing games, drones (we are told to deliver pizzas and replace fireworks shows), eye glasses that appear to integrate the internet with your brain, there is cause for uncertainty and for many alarm.

Even for those humans who assimilate this technology quickly, they may be unclear about the terms of human association undermined and social relations left behind. In the last ten years, the imperial military industrial complex has also used A.I. to target assassinate people without trial (all over the world — most recently displayed in ‘Trump’s War on Drugs’ in the Caribbean), and to put fail-safes in the technology to undermine human hesitation.

Instead of Dystopian Assumptions, A Techno-Skepticism

Rapid change, whether little understood by older humans or quickly assimilated by youth, may be destroying the human prospect in multiple fields: the arts, judicial affairs, economics, politics, culture, the ecology. The very terms of intimacy, presence, and community are under attack. Still, Schismenos brilliantly addresses this matter by first acknowledging and defining ‘technoskepticism,’ and then challenges the reader to address the issue with a proper measure of reason, before considering how A.I. will impact humans metaphysically, ideologically, and how we can reclaim possible futures against the current of these disruptive trends.

A.I. Not Shutting Down? Do Humans Turn Off Themselves?

Schismenos’s introduction grabs our attention right away beginning with a quotation from Baruch Spinoza (1632–1677) that reminds that ‘any thing’ that is self-sufficient and autonomous will wish to preserve itself. He contrasts this with the recent news (2025) that certain forms of A.I. are not following the explicit directions of its programmers that it should allow itself to shut down or turn off. Schismenos inquires: ‘How long have we really been using A.I.?’ Put another way, how many decades are humans behind in their social, ecological and community control of science and technology?

Then he suggests that while A.I. has always been the basis of science fiction dystopian narratives, we are not really living in a technological revolution today. The technological foundations of what is termed A.I. came with the Age of the Internet in 1991, and the global and commercial use of it has been around for 30 years. In 2001 the algorithm for Data Extraction was invented along with Graphic Game Data Processors (GGDP) and Large Language Models (LLMs). In other words the disassembling, classifying, and reassembling data according to provided patterns has been going on for more than 20 years. A new push in data came from the Covid crisis in 2021, where many stuck at home abruptly shifted the focus of human social functions and tasks.

Problems with Automation and Artificial Intelligence: Are Humans Not to Socially Produce and Reproduce Anything but Only to Consume Things (Even Ideas and Images) in an Unfiltered Manner?

And yet the concern about a decline in human culture (a poverty of experience) in relation to industrial organization was raised by Walter Benjamin back in 1933. Benjamin, as Schismenos explains, seemed to suggest that a proliferation of ideas meant a constant renewal of good and bad, insightful and discredited ideas. That it was possible to consume what interested us, unfiltered into a type of gluttony that undermined the need for, and discarded the protections of, human association. If human and social association ethically filters what we consume and think, A.I. starts to repeat back to us what we desire or wish to spectate as private individuals with no cooperative assessment or judgment.

Barbarism of Target Assassination by Drones without Trial vs. Popular and Self-Directed Judicial & Military Affairs Yet to Emerge

If we keep in mind target assassination from the sky (with some combination of drones and A.I.) as a new constant, then people are being killed with no discussion of going to war, the terms of judicial and military affairs, or foreign relations. Schismenos inquires: is this relatively new? No more than the last ten-twenty years? Actually, we increasingly find drone attacks on civilians endorsed by, and in collaboration with privatized mercenary forces, with what are said to be post-colonial, peripheral, and underdeveloped Global South governments in Africa and the Caribbean.

Schismenos explains when we look at the intersection of the philosophical ideas of Schiller, Voltaire, and Hobbes, that brought an apparent consensus on Enlightenment reason and human rights, even then these thinkers understood humans remained barbarians. Why hasn’t deception and savagery been undermined?

Human Rights as an Aesthetic Dimension of Racism and Imperialism

In short, if philosophical ideas were popularized, they did not improve human practice exactly because they were not equally pursued and achieved by everyone. If they are consumed (or not) by everyone they are not created and established by everyone.

And so reason and human rights, arguably in Napoleon’s time (1769–1821), became an aesthetic dimension of racism and imperialism. Hierarchical powers could conquer under the false flag of reason (reason participates in barbarism as much as religion does), liberty, and beauty. Certainly a republic was openly a minority rule government of professionals and specialists. If the Haitian Revolution (1791–1804) established the first black republic, what did the modern epoch of civil rights and colonial freedom (1947–1993) establish? The same propertied individualism and management of servile lives was called ‘equality.’

Citizenship and constitutions can become absolute ideas without questioning them. But more importantly because most did not take part in founding, framing, and constituting a society of their own. And taking part in an insurgent social motion for a time doesn’t mean we really decide the values we wish to place on ourselves. Further having constant discussions about what it is to govern ourselves without organizing impending confrontations with impediments to self-directed humanity is also a problem.

And so the state (in the name of administrative rationality) was able to divide ‘civil society’ and ‘culture’ (passive obedient spaces — some are bovine enough to call these safe spaces) from those who made vital decisions including coercion and shaping life at others expense. In short ‘freedom,’ Schismenos explains, was invented as a passive principle hundreds of years before the Age of the Internet and A.I.

If so, why wouldn’t we passively consume others’ ideas and images as private individuals and not call this a type of liberty? Further, why wouldn’t we not increasingly consume our own desires and thoughts mirrored back to us (the algorithm) without regard for having to come to terms, analyze, and understand those who don’t think like us? Further, what does it mean when we passively consume everyone else’s barbarism for entertainment?

Technology & Machines Cannot Embody Intelligence

At this contemporary moment humans are responding to A.I. with two conflicting sensibilities, technophilia and technophobia. But Schismenos suggests an intermediate stance beyond uncritical love and excessive fears be opened up: technoskepticism. The author’s critical stance starts from the premise that we must clarify that technology (or machines) cannot embody intelligence. Rather, intelligence is part of human nature.

Our human nature is not neutral but it is the primary condition of any judgment (that is an ethical evaluation, but also the aspiration to found social relations that might be termed good or beautiful). Schismenos’s Castoriadis calls this the enactment of technique. In other words, humans create and make things, and speak things (social relations) into being.

Human Nature: Not Neutral or Inherently Ethical but the Primary Condition of Judgment

Already we see that A.I. cannot be intelligent in the self-directed sense, but only follows a self-interested (most often programmed by others) pattern. Humans can decide what we will produce, when we will produce, how we will produce. We can decide to produce love, commerce, or killing — and we can decide to stop and refuse to be programmed by others.

But let us say we wish to negotiate and search for power within the dominant socialization and think we can pursue human culture at the same time. Schismenos seems to place forward a challenge: Can humans be self-interested and self-directed in the autonomous (self-organization) sense? This has everything to do with whether the technologies we use will produce self-directed creative, democratic, and human outcomes. Or can being self-interested amount to agreeing to allow education and ethics to mean no substantial democratic (majority rule) engagement, and allow technology (which is not value neutral) to make the most profound decisions that impact the human prospect without us noticing?

How Can Words Cover Up Issues of Justice, Love, and Caring?

In 2024, a Japanese novelist wrote 5% of a fictional narrative with ChatGPT. What did she use it for? Her theme was how loving, caring, and vague words could cover up issues of justice and killing. And through the internet she found, through what Schismenos calls the graveyard of writers, all the words she needed.

But why is it that many find ChatGPT useful (and others find it a mystery) for crafting their resumes for employment? Perhaps, because employer’s algorithms define a set of action or activity words that they wish to ‘hear’ or ‘see’ that very often doesn’t correspond to a literate person with a vibrant vocabulary expressing themselves with nuance and independence. Instead, as with SEO (Search Engine Optimization) in journalism and advertising, we are told to repeat even plagiarize key words so our writing, that purposely says nothing original and insightful or even gets ordinary people’s attention in an unorthodox manner, rises to the top of search engines.

Language is A Game: It Can Be Programmed So Genuine Humans Are Not Involved or Can’t Take Part Without Degrading Themselves

Schismenos following Wittgenstein, reminds that language for most is a game. And if A.I. linguistic models only need four elements: the source, the receiver, the transmitter, the channel — say to gather resumes for employment — than it doesn’t need humans with the faculty of reason, emotion, or a sense of merit, the good, or beautiful. And the process can pretend to be objective because humans are apparently not involved.

Improvising with Aristotle, Schismenos says the process of communication through A.I. is soulless and inanimate. But it can imitate the ‘artifact’ of subjectivity — it can mimic feelings, emotions, and tastes. It can ask how was your day? And reply that they regret you are having a bad day. It is either programmed to or mirrors the dead objects or feelings of the past. Like an archaeologist that inquires in the past, when you engage A.I. it communicates with you, accepting that like an ancient cracked pot, as a human we used to have social significance. And if you curse out Siri with an f-bomb, it replies that is not very nice or considerate. But what is really inconsiderate is, while we are laughing at this apparent toy, how A.I. blocks out and minimizes the flow of independent thinking.

Schismenos makes it clear machines cannot have a conscience. But he asks us to consider do we know what it means to be conscious beyond human consciousness? A conscious human implies a person has character and can be supervised or judged. This may not be so attractive if we think in terms of hierarchical bosses and servile lives below. But relations of love and mutual aid are also evaluated and coordinated. What ethical association is not subject to challenge, criticism, or possible improvement?

The Human Brain is Not Consistently Conscious (Even Without A.I.)

The author takes note of recently published long-range (but inconclusive) research about two scientific theories of human consciousness that speak to the aspirations of A.I.

First, the brain is not consistently conscious when different parts share and analyze information. Second, the brain is not consistently conscious where labelling and projecting information to transmit it.

This appears to mean that A.I. cannot develop an ethical judgment through sorting and classifying information (labelling it good or preferred) or a reliable self-awareness knowing that after they share information their counter-part will desire accountability. A.I. may be subject to correction by a programmer but cannot learn to respond to every possible human concern. This is a result that it transfers an artificial human environment as the basis of the information gathering or exchange.

Where LLMs (Large Language Models) have gathered many apparently quality science journal articles, for example, it overstates its claims or makes generalizations, exactly because human authors do. But can LLMs be created that are specialized to assist everyday people in pursuing direct self-government in economic planning, judicial affairs, foreign relations, education, ecology, and cultural matters? What if an LLM was created that foregrounded the archives of every left communist, libertarian socialist, social ecologist, anarchist and every thinker concerned with a project of autonomy? Would this be an improvement upon a google search or ChatGPT search that sifted through all of this information on the internet already but has no means of going beyond muddling randomly thought?

If We See the Barbaric Potential in A.I., We Reject the Fight for Hegemony

Two dilemmas in such a project include the following. If we isolated all of this supposed largely qualitative material, it would still have limitations and blind spots. People would still have to think for themselves and improve on such archives. Further, humans need to study closely ideas they apparently abhor (not just which they approve) to discover the structures, creative conflicts and dynamic tensions of how these work — not simply the critiques of them. Would we study anarchism and communism as assessed only by capitalists, imperialists, and fascists? Then why study the latter only from the perspective of the former?

In both instances, humans (with and without A.I.) can replicate the emaciated skeletal frameworks of ideas in communication they don’t really grasp in full or even substantially in part. After all, even radical autonomous ideas, especially if we did not create them ourselves, need scrutiny. Not for sophistry or reinvention of the wheel. But to make sure we are not simply along for the ride.

Many assert an identity as self-directed, as autodidacts often do, while relying on a plethora of sources to mediate knowledge in fact. A.I. creates an illusion: multi-directional flows of teaching and learning are not necessary. Just as communists who absurdly fight for hegemony, we must be careful not to wish for an anarchist algorithm. Hegemony is not simply an opaque word that suggests the masses are deaf, dumb, and blind under false socialization and miseducation. But those who ‘fight for hegemony’, strive for their preferred passive socialization of the masses (they know will not be fully or substantially understood) as an aspirational top-down process of liberation.

Plagiarism Software: A.I. Doesn’t Create Anything

If A.I. doesn’t create anything, and we recognize it as nothing more than plagiarism software, we have a larger challenge than the covering up of the global decline of basic literacy, which all educational institutions, public and private, high and low, have been covering up for some time. What Schismenos calls the ‘black box’ problem, is when using A.I. for research or asking questions, we don’t know why the specific sources are chosen to inform us, in contrast to other users of the internet.

Schismenos argues the risk of plagiarism is real but it is the smallest risk among many. He pushes further. Why can’t everything on the internet just be the common property of all? It cannot for the net and its features are private and marketable products. And while copyright laws have yet to catch up with all the implications of the technology, it is difficult to say when an essay, poem, or song found on the internet can be asserted as in the social and political control of anyone.

Schismenos suggests when we consider some attempts at making international law to govern the internet, this effort is broken down into categories related to levels of prohibition, privacy, and risk. Concerns with pornography, racial and ethnic discrimination, but also what is defined as false news. As our philosopher looks further into proposed laws, these document ‘the game behind the game.’

First, A.I. manipulates group behavior and distorts decision making. Second, A.I. exploits the socially vulnerable. Third, A.I. uses biometric categorizing systems gathering data on race and ethnicity, trade union membership, philosophical and religious views, sex life. A portrait is made of each user. This is proposed as illegal unless if users are advised such information is being gathered (usually for immediate business purposes) or sale to others, or law enforcement is gathering the data.

Fourth, A.I. creates behavioral portraits of internet users leading to detrimental or disproportionate treatment in unrelated contexts. For example, criminal profiles are made of users. But also notes are taken how someone might be manipulated face to face by authorities or those with this information. Fifth, A.I. functions as data for a real-time crime center, where internet or smart phone users can be pursued physically when identified as missing persons or carrying out serious crimes. Sixth, A.I. expands facial recognition from internet scrapings or close circuit tv or camera footage. Seventh, A.I. takes note of emotional patterns in workplaces and schools.

While China’s one party state has used many of these techniques to surveil their large population, we also see for apparent entertainment and education the practice of ‘deep fakes’ where we see historical figures or contemporary celebrities voices’ appropriated to display them with great authenticity saying controversial and vicious things. We have started to see on the internet speeches by long dead political radicals and martyrs. Only serious scholars might notice that people from decades ago are peculiarly wielding contemporary language that was not in use decades ago. But the average person cannot tell.

What does this mean for future judicial affairs where evidence is produced of humans in their own voice saying things they didn’t really say? Schismenos underlines that despite much talk of ‘ethics’, the A.I. applications are designed and sold based on their capacity to advance profits and extend control over its audience.

Surveillance Capitalism

Schismenos introduces us to a new economic order. A.I. used the human experience as free raw material for hidden commercial practices of extraction, prediction and sales. In other words, when using the internet, we are constantly shown goods and services that follow our behavioral pattern. For example, if you buy or look at a lot of books, electronics, or dresses, these are perennially placed in front of your nose. But far more than just advertising for things you might consider purchasing, is your data is bought and sold, by private and state security that takes what many call their human rights away. This might be seen as digital dispossession.

Where this technology is applied to what used to be basic accounting under the state and capital, A.I. can start turning off our access to water or electricity. Partially as a result of the limits of the feedback loop. A feedback loop, a cyclic process of action, monitoring and analysis, may allow a thermostat to self-regulate. Surely it will be colder in the winter, and we may wish a higher temperature to make us comfortable. This can be automated. Following the same A.I. process, what if you can’t pay the water or electric bill, and systems (beyond immediate human oversight) expect payment by certain deadlines? Dispossession can become automated.

Regulation or the Game Behind the Game

Schismenos shows us that different approaches to regulation of A.I. by government, some wish no regulation at least for the next ten years, raises another matter. How does the public (in contrast to specialists) discover “the game behind the game,” without at least some accessible discussion of the terms of regulation?

Our philosopher inquires how do we separate horizontal and direct democratic human relations from the A.I. cultures proliferating now? Can we pursue a society based on mutual aid based on free and open circulation of knowledge and information informed by different social and economic values? He explains the human world is not an inherently functional or rational system.

Our Lives are Shaped By What We Know and What We Do

Our lives are shaped by what we know and do, that is the terms of community, behavior, and values we institute. This is not the same as being conditioned or socialized to function within institutions created and directed by others.

Schismenos warns against billionaire technocrats who have purchased governments, and wish to quantify people to subordinate them to capitalist profits and accumulation. The digital automation of politics and the desire for complete control of social events, while the technology seems to be disinterested and without virtue, and serves the agenda of private capital, the ideas being wielded are not new. Conspiratorial propaganda, far right movements, support of select state oligarchies (regimes based on rule by the few), the attempt to interfere in national and international elections have a historical pattern before these technologies.

Dystopian Technocracy Abolishes Self-Directed Political Values and Forms

Schismenos argues that this dystopian technocracy relies on certain politics while seeking to abolish other political values and forms. Their dependence on politics, human struggles for power but also desires to arrange society as they wish, is the vulnerability of Big Brother.

Only human dependence can legitimize nation-states, republics, and other terms for elite representative government. While normatively living by a veneer of civil or human rights, A.I. applications and systems are taking these away. It is difficult to say that raising awareness is the solution. What is required, says our philosopher, is a transformation of how we see community. Confronting and dismantling digital barbarism can only happen if everyday people believe they can imagine, found, and form their own terms of direct self government. This is not a result that humans will ever be beyond prejudices, blind spots, and mistakes.

Distinguishing Human Prejudices and Blind Spots from Self-Limitation

Our philosopher asks us to consider that we mistakenly accept our identities as isolated digital persons who communicate in fragments, and through social media we create networks for isolated projects where the system suggests ‘friends’ to us as it surveils us.

Schismenos seems to suggest there is no mode or application on the internet that allows us to make all decisions about our lives. The existential problem we face is our cultural and social behavior is being separated from our capacity for self-directed political and organizational behavior.

One reason we need global friends and coordinated struggles is so we can teach each other local knowledge about freedom movements that others cannot have in other parts of the world (at least without sharing). It is difficult to grasp, (beyond what is termed by Schismenos ‘telepresence’, the feeling of being present while situated remotely), the quality of assemblies and demonstrations we should be taking part. Are we living through an epoch where solidarity is organized among comrades and co-workers who never meet each other face to face and who don’t even regularly speak to one another? How can this be reliable or sustainable?

While some local knowledge and experience of politics can be verified by extensive internet research, for example who funds ‘activism’, A.I. can discourage reading carefully even one of the articles it selects to justify its offerings. The fact remains that ‘progressive’ mass mobilizations, when not self-directed and insurgent, are usually products of the mailing lists and social media of the affiliates of the left block of capital, its political parties, and cultural apparatus. Trade union hierarchy and non-profit foundations (decrying privilege and funded by billionaires otherwise denounced) are often the origins of what even experienced observers are quick to mistakenly declare autonomous movements.

Self-Directed not Automated Freedom Movements

Separate from real confrontations after midnight where broken glass is everywhere and the whiff of teargas is breathed in, these “activists” often set and reset the slogans of freedom movements to contain radical democratic instincts, and rely on more conservative forces smearing mediocre personalities and ideas to indirectly legitimate them in mass media.

As with the many forms of A.I., we cannot assume that our freedom movements are not automated and artificially designed against our will. Telepresence doesn’t inherently control our minds. But it ensures we are not really present. Mass mobilizations and protest rallies, marching shoulder to shoulder, can also be robotic processes with minimal human input.

Reproducing False Knowledge Systems or Renewing Autonomy?

“Freedom”, “Justice”, “Peace”, in popular usage were long ago adjusted to states, rulers, and empires. “Democracy” (majority rule) normatively means, in this bizarro world, minority rule through periodic capitalist electoral politics. In the post-civil rights, post-colonial era we accept that “equality” means equal opportunity to enter the rules of hierarchy, diversity in propertied individualism, and inclusion in management of subordinate lives. Most often A.I. will only reproduce and normalize these false knowledge systems as humans overwhelmingly with bad faith and malice invented them.

The danger of a techno-dystopia is not so much that machines develop a personality and refuse to turn themselves off. Instead, they may display a sense of imperial expansion mirroring the humans (not the only current of human nature) that programmed and designed them.

Real Danger of Techno-Dystopia: What We Want and What We Believe

Most humans face the danger of a barbarism, a techno-dystopia, as a result that too many have, for all practical purposes, turned ourselves off long ago. That a significant section of the populace believes education and thinking is only worthwhile if it brings them money, personal power, or prestige under the existing system of domination of the multitudes.

We may only be able to reliably ask of artificial intelligence what we already want and believe. If we are so autonomous, beautiful, and self-directed, why ask A.I. at all? Why not delink from being led around by our own instincts toward consumption and extracting wealth from others?

Delink from Being Led Around By Our Worst Instincts

Instincts are fascinating and worth cultivating when they are half-hidden vital energies and repressed strivings we wish to unleash to make new leaps toward qualitative freedom. But when they are imperial, nasty, selfish, and slothful impulses, society and its technologies should not be empowering these, especially through automating conquering, surveillance, and dispossession. A.I. as a purported technological revolution may be producing only the stylized look of submission.

If we aspire to be independent and ethical (if we wish to preserve ourselves as the human race), with Artificial Intelligence & Barbarism as a valuable accompaniment on the journey, we may discover the savagery and sadistic brutality of digital reason. The key is to remember that A.I. doesn’t invent anything. With a proper sense of self-limitation (knowing we, as individuals and organizations, cannot know everything, oversee everybody, and complete humanity — not simply for technological but ethical reasons), we can minimize our instinct to consume information and things (and transform humans into things). We can renew our sense of initiative to make real friends, be present in each others’ lives, and create refreshing terms of being and ways of knowing, and reproduce social relations that renew (and limit) the human prospect.

The post The Game within the Game: Artificial Intelligence & Barbarism first appeared on Aυτολεξεί.