A hybrid subject of entangled human–machine capacities that foregrounds distributed agency, boundary blurring, and the material–semiotic making of writerly life.
Cyborg refers to the hybrid entity that emerges from the intimate entanglement of human and machine, blurring the boundaries between organic and technological, natural and artificial. In postqualitative and new materialist research, the cyborg is not merely a science fiction figure but a conceptual tool for thinking about the distributed, relational, and more-than-human constitution of subjectivity and agency. Within the context of GenAI in higher education writing instruction, the cyborg metaphor illuminates how instructors and students become technologically augmented beings, co-producing knowledge and text in collaboration with algorithmic systems. This perspective challenges the purity of human authorship and the autonomy of the educational subject, foregrounding instead the ongoing processes of cyborgification that shape pedagogical practice, creativity, and identity. The cyborg thus becomes a figure for exploring the ethical, affective, and epistemological complexities of teaching and learning in an era of pervasive digital mediation.
The cyborg, articulated by Haraway in the 1980s, is a conceptual figure for thinking with technoscience as lived, material, and political. It disrupts tidy splits between human and machine, nature and culture, body and tool by showing how identities and capacities emerge through attachments with devices, infrastructures, and discourses. In education, this is a way to notice how keyboards, platforms, databases, algorithms, policies, and bodies become mutually enabling. The cyborg foregrounds situatedness and accountability: no view from nowhere, only partial perspectives entangled with power. It also emphasizes coalition across difference, crafting “affinity” rather than assuming natural unity. In plain terms, the cyborg invites attention to who and what gets included (e.g. in learning,) how boundaries are drawn around legitimate composing, and how technical systems redistribute authority and labor.
In conversation with new materialist and postqualitative work, the cyborg travels alongside concepts like intra-action (from Barad), assemblage (from Deleuze & Guattari), and vibrant matter (from Bennett). Where assemblage maps multiplicity and linkage, the cyborg emphasizes how those linkages are historically charged and politically consequential. Where intra-action highlights that entities emerge through relations, the cyborg attunes to how those relations are technologized, gendered, racialized, and classed. Read this way, the cyborg is both a diagnostic and a design heuristic: it helps describe the world as already technoculturally entangled and invites the crafting of more just configurations of people and machines in everyday practice.
For postqualitative inquiry, the cyborg helps treat research apparatuses, data practices, and analytic tools as participants in knowledge-making rather than neutral carriers. It supports methodological commitments to tracing material-discursive practices, attending to distributed agency, and designing inquiry as an intervention in the phenomenon under study. In practical terms, it encourages researchers to document the specific entanglements that make the research possible: the platforms used, the prompts crafted, the sensors or logs gathered, the policies shaping what can be recorded, and the affective atmospheres that make certain questions urgent. It also offers an ethical vocabulary for making accountabilities explicit: whose bodies bear the costs of particular techno-pedagogical choices, and who gains voice or loses it through these couplings.
In AI-entangled writing instruction, the cyborg names the everyday composition of instructor, student, and machine across interfaces, prompts, datasets, and institutional rules. It helps analyze lived and affective experiences by asking how feelings like vigilance, relief, or creative momentum arise from specific human–machine couplings: typing together with a suggestion engine, reading with an inline explain feature, co-revising with a paraphrase tool. It clarifies the redistribution of authorship and labor across people and systems, showing how citation, style, and originality are enacted through platform affordances, model biases, feedback workflows, and classroom norms. It also orients attention to the pedagogical assemblage: prompts, rubrics, LMS integrations, privacy settings, licensing terms, and trace logs that collectively shape what writing can be and who is recognized as its author. Instructors experimenting with “cyborg writing” practices might, for example, stage assignments where model outputs are annotated with rationale and lineage, or where students design and justify their own human–AI workflows, making the attachments explicit rather than hidden.