Rethinking education in AI age: Cyborg theory faces new challenges in modern classrooms

A new study is reigniting debate over one of the most influential ideas in modern critical theory, arguing that Donna Haraway's "cyborg" concept must be fundamentally rethought in the age of artificial intelligence, platform capitalism, and data-driven education systems. The paper warns that AI is not simply reshaping classrooms but redefining power, identity, and knowledge itself.

The study, titled "Haraway's cyborg manifesto in education: after AI" and published in AI & Society, revisits Haraway's 1985 "Cyborg Manifesto" four decades later, assessing both its predictive power and its limitations in today's AI-dominated world.

From cyborg promise to platform control

Haraway's original manifesto framed the "cyborg" as a hybrid of human and machine, a metaphor meant to break down rigid boundaries such as human versus technology, nature versus culture, and mind versus body. This hybrid identity was seen as politically liberating, offering new ways to challenge entrenched systems of power and inequality.

The author claims that this vision was remarkably prescient. The study highlights how Haraway anticipated the deep integration of technology into everyday life, including education, and warned of emerging "informatics of domination" that would reshape social systems.

In education, those predictions have materialized in striking ways. Schools and universities are now deeply entangled with digital infrastructures that track performance, manage data, and shape learning environments. The paper notes that education systems have become increasingly dependent on platforms that enable surveillance, algorithmic decision-making, and monetization of student data.

This shift has brought profound consequences. Educational institutions are losing autonomy as they adopt proprietary technologies, while students and teachers face growing constraints tied to data-driven governance. Privacy erosion, platform lock-in, and the commercialization of learning are no longer peripheral concerns but central features of modern education systems.

The study also explains how AI intensifies these dynamics. Rather than simply enhancing learning, AI introduces new layers of opacity and control. Decision-making processes become less transparent, and educational practices are increasingly shaped by predictive analytics and automated systems.

This reality challenges one of Haraway's core assumptions: that humans can meaningfully control or shape the boundaries between themselves and machines. In today's context, those boundaries are largely governed by a small group of powerful technology firms.

Data power, inequality, and the limits of the cyborg vision

Haraway's optimistic framing of human-machine hybridity no longer holds in an era defined by what some scholars call "technofeudalism" or "datafeudalism." In this system, vast amounts of personal data are extracted, processed, and monetized by a handful of corporations, creating new forms of inequality and dependence.

The study points out that global tech companies now wield unprecedented influence over communication, knowledge production, and political processes. These platforms shape not only how people learn but also how they understand truth, form relationships, and engage with society.

In this environment, the idea that "the machine is us" becomes deeply contested. While individuals are increasingly integrated with digital systems, they have little control over how those systems operate or how their data is used. The paper argues that this asymmetry undermines the emancipatory potential of the cyborg concept.

Education, as a key site of social reproduction and transformation, reflects these tensions. The study highlights several trends that illustrate the growing influence of technology on education, including the expansion of AI-driven learning tools, the rise of global edtech markets, and the persistence of inequalities in access to STEM fields.

The paper also notes that Haraway's predictions about education have proven strikingly accurate. She foresaw the increasing alignment between education and corporate interests, the erosion of democratic structures in schooling, and the emergence of knowledge systems shaped by technological and economic forces.

However, the manifesto underestimated the extent to which these forces would consolidate power rather than disrupt it. Instead of dissolving boundaries and hierarchies, contemporary technologies often reinforce them, embedding existing inequalities into digital systems.

The study also raises concerns about the broader societal implications of AI in education. These include the spread of misinformation, the decline of critical thinking skills, and the growing influence of algorithmic systems on public discourse. In this context, education is not just adapting to technological change but actively participating in its consequences.

Rethinking education beyond critique and resistance

The author suggests that contemporary research has focused heavily on critique, exposing the risks and harms associated with digital technologies. While this work is essential, it often overlooks the potential for alternative ways of thinking about education and technology.

The study proposes several directions for rethinking education in light of these challenges. One approach involves engaging with the "alien logic" of AI systems, exploring how they might generate new forms of knowledge and understanding rather than simply replicating existing patterns. This perspective treats AI not only as a tool of control but also as a potential source of disruption and innovation.

Another direction focuses on the concept of desire and utopia. The paper argues that education should not be limited to preparing individuals for existing economic systems but should instead cultivate the capacity to imagine and create alternative futures. This involves rethinking the purpose of education itself, moving beyond narrow definitions of efficiency and productivity.

A third approach emphasizes the idea of education as an emergent, aesthetic process rather than a purely instrumental one. Drawing on theoretical work that compares education to art or music, the study suggests that learning can be understood as a dynamic and creative activity that cannot be fully controlled or predicted.

These perspectives reflect an effort to move beyond binary thinking, such as human versus machine or technology versus society. Instead, the paper calls for a more nuanced understanding of the complex relationships between humans, machines, and environments.

Importantly, the study also engages with newer theoretical developments that build on or critique Haraway's work. Concepts such as "technosymbiosis" and "cybork" are presented as attempts to rethink human-machine relations in ways that account for contemporary realities, including the role of labor, knowledge, and collective intelligence.

However, the author notes that many of these frameworks still struggle to address the underlying issues of power and ownership that shape technological systems. Without confronting these dynamics, efforts to reimagine human-machine relationships risk remaining abstract or limited in impact.

The paper calls for a renewed focus on the political and economic dimensions of technology in education, urging researchers and policymakers to consider not only how AI is used but also who controls it and for what purposes.