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.

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).

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