The arrival of ChatGPT has sparked global conversations about the future of higher education. From headlines proclaiming the “death of the essay” to policy debates about academic integrity, the tool has become a lightning rod for public imagination. Media outlets across continents have alternately hailed ChatGPT as an educational revolution and condemned it as a threat to intellectual standards. This discursive turbulence offers a unique lens into how societies project their hopes, fears, and values onto emerging technologies.
Rather than treating ChatGPT merely as a neutral instrument, this article examines it as a symbolic object embedded in sociotechnical imaginaries—collective visions of desirable or undesirable futures shaped through public discourse. By tracing the evolution of media narratives, this study highlights not only how higher education is represented in relation to AI, but also how media discourses actively shape institutional responses, cultural anxieties, and policy frameworks. In doing so, it reveals the mutual entanglement of technology, culture, and education.
The concept of sociotechnical imaginaries emerged within the interdisciplinary field of Science and Technology Studies (STS), particularly through the work of Sheila Jasanoff and colleagues. It refers to collectively held visions of desirable futures that are animated by shared understandings of science and technology. Unlike purely technical forecasts, sociotechnical imaginaries intertwine cultural values, political agendas, and institutional priorities. They are not neutral projections but normative blueprints: they tell societies not only what is possible but also what is preferable.
Historically, imaginaries have shaped national projects such as the U.S. space program or South Korea’s investment in biotechnology. These examples highlight how imaginaries transcend technical feasibility, becoming frameworks through which policymakers, scientists, and citizens coordinate their expectations and justify actions. In this sense, imaginaries are performative: they do not merely describe futures but mobilize resources, institutions, and people toward specific trajectories.
In educational contexts, imaginaries often function as promises of democratization, personalization, or efficiency. The idea that technology can eliminate inequalities or revolutionize teaching is itself an imaginary that circulates through policy papers, commercial advertisements, and journalistic accounts. Thus, when ChatGPT enters public discourse, it does so already entangled in longstanding imaginaries of automation, progress, and disruption. To analyze these narratives, one must recognize imaginaries as cultural resources that frame debates about legitimacy, risks, and opportunities in higher education.
Media play a pivotal role in materializing sociotechnical imaginaries. Newspapers, television, digital platforms, and social media channels are not passive reflectors of technological change but active arenas where competing visions are articulated. Through metaphors, headlines, and visual imagery, media frame new technologies in ways that resonate with collective hopes and fears.
For instance, coverage of early computing technologies often emphasized metaphors of the “electronic brain,” simultaneously generating awe and anxiety. Similarly, media portrayals of ChatGPT frequently oscillate between utopian and dystopian poles: it is either a “super-assistant” capable of democratizing knowledge or a “plagiarism machine” undermining academic integrity. These discursive framings shape how the public perceives both the tool and the broader institution of higher education.
The performative power of media discourse lies in its capacity to stabilize imaginaries. By repeating certain narratives—such as the inevitability of AI-driven education—media solidify cultural expectations that may influence universities’ strategies and students’ self-understandings. Conversely, sensationalized warnings about “the end of learning” may prompt regulatory interventions or trigger resistance from faculty. Media imaginaries thus serve as intermediaries between technological innovation and social governance, translating complex possibilities into accessible and emotionally resonant stories.
Applying the imaginary framework to education reveals that each wave of technological innovation—printing presses, radio, television, computers, MOOCs—was accompanied by narratives of transformation. These narratives often promised to make education more accessible, efficient, or egalitarian. Yet historical evidence demonstrates a recurring pattern: initial hype, institutional experimentation, partial adoption, and eventual normalization within existing structures.
For example, the introduction of MOOCs in the early 2010s was accompanied by media imaginaries of a “global classroom” that would democratize elite education. While MOOCs did expand access, they did not displace universities or eliminate educational inequality. Instead, they became supplementary tools integrated into established systems. The imaginary of disruption gave way to the reality of institutional adaptation.
In this regard, ChatGPT can be situated within a lineage of educational imaginaries. It carries forward utopian narratives of personalized learning and democratized access, while also intensifying fears of automation and loss of human judgment. Unlike earlier technologies, however, ChatGPT interacts with students’ cognitive and linguistic capacities in real time, making its imaginaries more intimate and immediate. The promise of “enhancing creativity” and the fear of “eroding originality” coexist within media discourses, illustrating the ambivalent cultural position of generative AI in higher education.
The sociotechnical imaginary of ChatGPT is not just about tools but about possible futures of education itself. Universities, educators, and policymakers project different visions depending on their institutional missions and cultural contexts. Some imagine AI as a partner that augments pedagogy, fostering personalized tutoring and reducing administrative burdens. Others frame it as a threat to academic integrity, critical thinking, and the value of human scholarship.
These imaginaries intersect with broader debates about labor, authority, and the commodification of knowledge. If ChatGPT can draft essays, summarize research, or simulate conversations, what becomes of the traditional markers of intellectual achievement? Media discourses amplify these questions, offering scenarios in which universities either evolve into AI-enhanced hubs of innovation or collapse under the weight of automation and distrust.
Moreover, the imaginary of ChatGPT is global but uneven. In technologically advanced economies, narratives may emphasize innovation and competitiveness. In contexts with fragile educational infrastructures, imaginaries may highlight both hope (bridging teacher shortages) and fear (deepening dependence on foreign tech companies). The multiplicity of imaginaries underscores their cultural contingency: they are never universal, but always negotiated across local and transnational settings.
In sum, the theoretical framework of sociotechnical imaginaries provides a powerful lens to examine how media discourses about ChatGPT are not simply descriptive but constitutive of higher education futures. These imaginaries reveal the cultural negotiations through which societies grapple with the promises and perils of AI in education, setting the stage for analyzing the evolving trajectories of media discourse in subsequent sections.
This section traces how media stories about ChatGPT in higher education have shifted over time: from spectacle and hype, to crisis-oriented integrity frames, to institutional policy debates, and finally toward more normalized, professionalized discussion. I divide the trajectory into six interlocking subsections so that each discursive phase can be examined in detail and in relation to broader cultural currents.
The first wave of media attention around large language models cast them as spectacle—novel, attention-grabbing technologies that promised to alter everyday life. Journalistic accounts foregrounded striking demonstrations (coherent essays, passing standardised tests in pilot reports, or generating creative fiction) and leaned into vivid metaphors: “robot writers,” “AI tutors,” or even apocalyptic catchphrases such as “the end of the essay.” Such framings served two rhetorical functions. First, they simplified complex machine-learning phenomena for mass audiences by converting algorithmic processes into culturally resonant images. Second, they performed a promissory function: the future was not just described but valorized as nearer and more transformative than many institutions were prepared for.
These early narratives amplified affect—wonder, curiosity, and fear—making ChatGPT an object of mass fascination. Tech sections, weekend features, and celebrity op-eds circulated a limited palette of imaginaries: automation-as-efficiency and automation-as-threat. Importantly, the spectacle phase was not merely celebratory; the same attention that lauded potential efficiency gains also produced the raw material for later anxiety-driven frames. In short, early hype established the terms of public imagination—what the technology could mean in principle—so that subsequent debates would argue over its social desirability and governance.
Following the spectacle came a reflexive backlash centered on academic integrity. Media narratives coalesced around stories of students using AI to draft essays, complete assignments, or game assessment systems—stories that were readily dramatized and, in many outlets, cast as evidence of a broader moral crisis. The integrity frame relies on a set of culturally potent logics: authorship as a moral good, the essay as a rite of passage, and the university as a guardian of intellectual virtue. When generative AI appeared to circumvent those norms, journalists and commentators framed the issue in stark moral terms.
This frame performs several functions. It personalises systemic anxieties—turning questions about assessment design and labor conditions into stories about “cheating students” and “betrayed faculty.” It also foregrounds epistemic trust: if the public cannot trust student work, what does that mean for credentialing and the social value of degrees? Media treatments often recycled legalistic and moral vocabularies—plagiarism, fraud, misconduct—thereby setting the stage for punitive institutional responses.
The rhetoric of moral panic has its own generative effects. Universities, responding to highly visible incidents and public scrutiny, adopted short-term containment strategies: bans on AI tools in exams, emergency policy memos, or heavy-handed honor code enforcement. These responses were themselves newsworthy and contributed to a feedback loop in which media coverage prompted institutional action, which then became new fodder for media attention. Crucially, the integrity frame occluded alternative interpretations—such as opportunities for redesigning assessment to foreground process over product—by focusing attention on discrete acts of misuse rather than on systemic pedagogical adaptation.
As the integrity debate matured, coverage shifted toward institutional policy and governance. Media outlets began to chronicle how universities, accreditation bodies, and education ministries were grappling with operational questions: Should AI be banned in certain assessments? How should faculty be trained to detect machine-generated prose? How should academic conduct codes be revised? These stories moved beyond anecdote into structural analysis, reporting on task forces, policy memos, pilot programs, and contracting with third-party detection vendors or ed-tech providers.
Two competing policy imaginaries emerged in the coverage. The first—regulatory containment—emphasised prohibition, surveillance, and enforcement. Headlines in this vein foregrounded “bans,” “detection,” and “sanctions,” reflecting a preventive posture. The second—integrative governance—emphasised adaptation: redesigning assessments, embedding AI literacy into curricula, and piloting AI-augmented pedagogies. Media narratives that adopted the integrative posture often featured educators experimenting with ChatGPT as a tool for feedback, iterative drafting, or differentiated instruction.
News reporting frequently highlighted the influence of commercial actors (both AI platform vendors and ed-tech firms) and the tension this created: universities were simultaneously users, customers, and critics of platforms whose incentives did not always align with public education. Such coverage expanded the debate from student behaviour to procurement, vendor governance, data privacy, and the public authority of higher education—thereby politicising what had initially appeared as individual acts of misuse.
Over time, a gradual normalization occurred in some media sectors. Specialist education and higher-education trade press began publishing more measured, evidence-based coverage: empirical studies of learning gains, case studies of pedagogical redesign, and interviews with educational researchers. The tone of reporting in these outlets shifted from sensational headlines to professionalised analyses: which instructional models worked, which assessment designs were robust, and what faculty development resources were necessary.
This professionalized discourse broadened the public imaginary by relocating the question from moral panic to pedagogical pragmatics. Rather than asking “Is ChatGPT cheating?” these stories asked “Under what conditions does AI support learning?” and “How should assessment measure higher-order thinking in an age of generative tools?” Such framing invites iterative, research-driven responses rather than emergency prohibitions. It also opened space for hybrid narratives that acknowledge both risks and affordances—an important discursive correction after the extremes of hype and panic.
Parallel to legacy media, platformed publics—Twitter/X threads, Reddit communities, TikTok tutorials, and YouTube explainers—played a decisive role in shaping the everyday discourse. These channels amplified performative demonstrations (how to prompt ChatGPT to pass a particular assignment), circulated memes that trivialised or normalised use, and offered peer-to-peer pedagogical hacks. The tone and temporality of social media produced distinct discursive effects: rapid viral cycles, polarized reactions, and affect-laden storytelling that could both popularise and caricature academic debates.
Influencers—popular educators, student creators, and tech commentators—often reframed academic concerns for broader audiences, sometimes translating nuance into rapid takeaways that fed back into mainstream reporting. Algorithmic amplification meant that particularly sensational or affective posts could reach broad publics quickly, shaping the headlines that legacy media then picked up. This cross-pollination highlights how media ecosystems, not single outlets, generate and sustain the imaginaries that structure institutional and public responses.
Finally, the evolution of media discourses is uneven across national and cultural contexts. In some countries coverage emphasised innovation, national competitiveness, and economic opportunity; in others it focused on regulatory risk, foreign influence, or digital sovereignty. Local educational histories and institutional capacities shaped which frames resonated: contexts with acute teacher shortages might foreground pedagogical promise, while contexts with high-stakes credentialing systems might emphasise integrity and distrust.
Language, political economy, and media systems therefore mediate imaginaries: global narratives about AI circulate, but they are remade locally. Comparative reporting exposes the contingency of discursive trajectories and underscores that media evolution is not monolithic but plural—shaped by distinct publics, institutions, and policy terrains.
Across these phases, media discourse moved from affective spectacle to crisis framing, onto policy contestation, and—within specialist spaces—toward deliberative nuance. Yet these phases are not strictly sequential: they overlap, re-emerge, and coexist in the media ecology. The next section will examine the social effects of these discursive shifts—how media imaginaries have shaped institutional practice, student identity, faculty labor, and broader public trust in higher education.
Media coverage has exerted a powerful influence on how universities craft and communicate policy. As newspapers and online outlets highlighted stories of “AI-fueled cheating” or “universities in crisis,” institutions felt pressured to respond swiftly, often in highly visible ways. Emergency bans on ChatGPT in exams, revised honor codes, and public statements about academic standards were as much about managing reputational risk as about solving pedagogical problems. The performativity of media discourse here is striking: it created a climate in which institutional inaction risked being read as negligence.
Beyond bans, however, some universities embraced experimental policies. Media attention to positive case studies—faculty using ChatGPT to scaffold feedback, or departments piloting AI literacy modules—legitimized integrative approaches. This interplay underscores how discourse can open as well as close institutional possibilities. While punitive narratives narrowed the horizon to integrity enforcement, constructive coverage expanded it toward curricular innovation. In both cases, universities internalized media framings, treating them as proxies for public expectation. Thus, institutions did not simply adapt to a technology; they adapted to the imaginaries of technology circulating through media ecologies.
For students, media narratives shaped both self-understanding and everyday practices. Stories about rampant “AI cheating” cast students as potential violators, producing a climate of suspicion that could alter how they engaged with coursework. In some cases, students internalized stigma, hesitating to experiment with AI tools for legitimate learning purposes. In others, the visibility of AI’s controversial status heightened its allure: media representations of ChatGPT as a subversive shortcut incentivized exploration precisely because it was framed as forbidden.
At the same time, narratives that portrayed ChatGPT as a learning aid, a personalized tutor, or a democratizing tool encouraged students to imagine themselves as empowered learners leveraging new resources. These discourses invited them to reconceive learning as co-produced with AI, blurring traditional boundaries of authorship and agency. In both directions—stigmatization and empowerment—media discourse structured the symbolic conditions under which students negotiated identity: as cheaters, innovators, collaborators, or resisters. Such identity work is consequential, shaping not only immediate behaviors but also long-term orientations toward knowledge, integrity, and creativity in higher education.
Faculty members experienced their roles reconfigured under the weight of media narratives. Coverage emphasizing AI’s potential to “replace professors” or “automate grading” challenged professional authority, fostering anxiety about redundancy and diminished expertise. In turn, stories of faculty resistance—professors catching students with AI-generated essays, educators denouncing ChatGPT’s errors—reinforced the image of faculty as guardians of tradition.
Yet media discourse also created opportunities for faculty to redefine their roles. Reports highlighting innovative teaching practices—courses redesigned to foreground process writing, critical AI literacy workshops, or collaborative projects where students and AI co-produced texts—framed faculty not as defenders against technology but as architects of its meaningful integration. In this sense, discourse shaped professional identity: whether faculty were positioned as obstructive gatekeepers or visionary innovators often depended on media framing.
Additionally, labor implications surfaced. The expectation that faculty detect AI misuse added to workloads, while narratives about AI “efficiency” sometimes obscured the invisible labor of rethinking pedagogy, redesigning syllabi, and learning new tools. Media imaginaries therefore both constrained and expanded faculty possibilities, making visible the contested reconfiguration of pedagogical authority in the age of generative AI.
Perhaps the most far-reaching effect of media discourse lies in its influence on public trust in higher education. Reports suggesting that “AI can pass exams” or “students can outsource essays” risk undermining the perceived legitimacy of academic credentials. If a bachelor’s degree is presumed to certify original intellectual work, then the specter of widespread AI use destabilizes that value proposition in the public eye.
Conversely, media narratives that highlight adaptation—universities incorporating AI literacy, embedding critical thinking assessments, and reasserting human judgment—work to restore confidence. Trust is therefore not only a function of institutional policy but also of discursive framing: the public’s faith in higher education is mediated through what they read in newspapers, blogs, and social media feeds. Employers, too, may recalibrate expectations, scrutinizing the reliability of credentials and demanding new forms of skill verification.
Thus, media discourse exerts systemic pressure: it does not merely describe risks but amplifies them in ways that affect the reputational economy of higher education. Trust, once eroded, is difficult to rebuild, underscoring the high stakes of discursive dynamics in shaping not just perceptions but the very social contract between universities and society.
Finally, the social effects of media discourse are inseparable from commercial and global contexts. Stories framing ChatGPT as a must-have educational tool have spurred ed-tech markets, pushing schools and universities toward rapid procurement of detection software, tutoring platforms, and AI literacy modules. Media coverage thus fuels commercialization: vendors position themselves as solutions to the very crises that media narratives amplify. The cycle of hype, panic, and solutionism underscores the political economy of discourse.
Inequalities are also exacerbated. Elite institutions with resources to experiment with AI integration are often portrayed positively in the media, reinforcing reputational advantages. Meanwhile, underfunded institutions, particularly in the Global South, appear as passive recipients of technology or as spaces of risk, their struggles framed more in terms of vulnerability than innovation. This discursive imbalance risks entrenching global asymmetries in educational futures.
Moreover, the circulation of narratives across borders means that imaginaries created in Anglophone media often set the agenda elsewhere. Local media adapt or contest these frames, but the global dominance of English-language reporting grants disproportionate visibility to certain perspectives. Thus, media discourse not only influences domestic institutions but also mediates transnational power relations in education.
Taken together, these social effects demonstrate that media discourse does not merely reflect higher education’s encounter with ChatGPT; it actively shapes it. Institutions recalibrate policy, students renegotiate identity, faculty reimagine authority, and the public reassesses trust—all under the influence of mediated imaginaries. Moreover, the commercial and global dimensions remind us that discourse is bound up with markets and inequalities, not just ideas.
This prepares the ground for the final section, which looks forward: how media imaginaries might continue to evolve, and what trajectories of governance, pedagogy, and cultural meaning could emerge in the years ahead.
Looking forward, the discourses surrounding ChatGPT in higher education will likely evolve along three major axes: normalization, contestation, and hybridization. Normalization refers to the gradual incorporation of ChatGPT into everyday academic practices, where media narratives may shift from sensationalized reporting toward depictions of mundane utility. Contestation will persist, however, as concerns about authorship, integrity, and inequality remain unresolved. Meanwhile, hybridization suggests that narratives will increasingly reflect a blending of optimism and caution, portraying ChatGPT as both a practical tool and a cultural symbol of technological disruption. These trajectories will shape how the public perceives not only AI itself but also the broader meaning of higher education in a digital age.
Governance will be central in mediating future media narratives. Policies around academic integrity, intellectual property, and AI literacy are poised to gain greater prominence. Media representations will likely track the development of regulatory frameworks, framing them alternately as safeguards against misuse or as constraints on academic freedom. For instance, if universities adopt AI-inclusive assessment models, narratives may emphasize innovation and adaptation. Conversely, if regulatory approaches are punitive, stories of surveillance and restriction may dominate. Thus, governance choices will not merely respond to media narratives but actively co-construct them, reinforcing the dynamic interplay between discourse and institutional practice.
From an educational standpoint, media discourses will influence whether ChatGPT is imagined as a catalyst for pedagogical renewal or as a threat to traditional modes of knowledge transmission. If coverage highlights stories of students using ChatGPT to enhance critical thinking or broaden access to learning, the discourse will support its institutional legitimacy. On the other hand, if narratives fixate on plagiarism scandals or diminished human creativity, public trust in AI-mediated education may erode. Importantly, the trajectory of discourse will affect resource allocation, shaping whether universities invest in AI literacy training, teacher professional development, or new digital infrastructures. Thus, media stories are not passive reflections but active forces shaping educational futures.
On a cultural level, ChatGPT’s media imaginaries will continue to intersect with broader narratives about automation, labor, and the value of human creativity. In some societies, ChatGPT may be framed as a democratizing tool that levels access to elite knowledge, while in others it may be depicted as deepening social divides. These cultural framings will resonate with longstanding societal anxieties about technology—automation replacing workers, machines supplanting human judgment, and digital tools reshaping cultural identity. Media narratives will thus function as a barometer of collective hopes and fears, mediating the cultural legitimacy of AI in higher education.
A critical challenge for the future is fostering reflexive and inclusive discourses. Reflexivity involves acknowledging the ways media narratives themselves shape educational practices, while inclusivity requires amplifying diverse voices—students from marginalized backgrounds, educators across different contexts, and communities outside the Global North. Without such reflexivity and inclusivity, the discourse risks reproducing inequities or perpetuating techno-solutionist myths. Moving forward, media outlets, universities, and policy actors will need to cultivate dialogical spaces where multiple perspectives are represented. Such efforts may help mitigate polarization and support more nuanced, responsible imaginaries of ChatGPT.
In examining the evolving media discourses on ChatGPT in higher education, this article has highlighted how sociotechnical imaginaries shape both public perception and institutional practices. From theoretical frameworks of sociotechnical imaginaries to the historical trajectories of media narratives, the discussion underscores that representations of ChatGPT are never neutral; they actively configure how education is imagined, governed, and practiced. The social effects of these narratives—ranging from concerns about integrity to opportunities for democratization—reveal both tensions and possibilities. Looking forward, future discourses will be characterized by normalization, contestation, and hybridization, deeply intertwined with governance, cultural values, and pedagogical priorities. The challenge ahead is to cultivate reflexive and inclusive narratives that recognize diverse experiences and avoid techno-solutionist simplifications. Ultimately, the way media frames ChatGPT will profoundly influence how societies envision the future of education and the role of artificial intelligence within it.
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