International Journal of Communication 20(2026), Book Review Chang Sup Park

Katalin Feher, Generative AI, Media, and Society, New York, NY: Routledge, 2025, 187 pp., $57.99 (paperback).

Reviewed by

Chang Sup Park

The University of Oklahoma

Katalin Feher’s Generative AI, Media, and Society enters a crowded but rapidly evolving field of scholarship on artificial intelligence (AI), platformization, and digital society. Published at a moment when generative AI has become central to debates about journalism, governance, labor, creativity, and public trust, this book aims to synthesize technological, ethical, sociopolitical, and media-centered discussions into a single conceptual framework. Rather than approaching generative AI purely as a technical innovation, Feher frames it as a civilizational transformation that reconfigures knowledge production, human–machine relations, and sociotechnical infrastructures.

The book is organized into six substantive chapters—“Transformation,” “Generative AI,” “AI Media,” “Uncertainties,” “Ethics,” and “Policy”—followed by a glossary and extensive references. Pedagogically, each chapter systematically integrates internal components consisting of “impact projects,” “reflective art,” “scholarly debates,” and “strategic takeaways,” an organizational design explicitly structured to bridge academic inquiry, policy discussion, and applied industry concerns. Feher positions the monograph as an interdisciplinary resource accessible to audiences ranging from scholars and graduate students to policy makers, technology professionals, and media practitioners.

One of the book’s major strengths lies in its breadth. Feher successfully synthesizes an enormous range of literature spanning communication studies, sociology, AI ethics, philosophy of technology, political economy, infrastructure studies, and media theory. Her conceptual vocabulary is ambitious and expansive, linking generative AI to datafication, sociotechnical systems, mediatization, automation, computational propaganda, synthetic media, and platform governance. Particularly compelling is the book’s insistence that generative AI should not be treated merely as another stage in digital innovation but rather as a deeper epistemological and ontological shift. Feher argues that generative AI transforms how reality itself is encoded, interpreted, and circulated, likening the transition to the historical shift from oral to written communication.

This argument gives the book intellectual coherence. Across chapters, Feher repeatedly returns to the idea that synthetic systems increasingly mediate human perception, communication, and decision making. Her discussion of “synthetic realities,” “model collapse,” and the erosion of distinctions between human-generated and machine-generated knowledge captures anxieties now central to contemporary media scholarship. This book is especially effective when examining how generative AI complicates long-standing concerns about authenticity, authority, and trust in digital environments. The chapter on AI media is particularly strong in this regard, connecting robot journalism, recommendation systems, deepfakes, and computational manipulation into a broader critique of synthetic mediatization.

Feher also deserves credit for foregrounding governance and ethics throughout the book rather than isolating them into a single normative chapter. Questions of accountability, explainability, bias, and democratic legitimacy are integrated across discussions of technological infrastructures, media systems, and institutional power. This approach reflects a growing recognition in critical AI scholarship that technological systems cannot be separated from political economy and governance structures (Couldry & Mejias, 2019; Crawford, 2021). Feher’s emphasis on “human-centered governance” (p. 105) and “responsible-explainable AI” (p. 92) aligns the book with emerging international policy debates surrounding trustworthy AI and algorithmic accountability.

Another valuable contribution is the book’s sustained engagement with sociotechnical theory. Feher repeatedly emphasizes that AI systems are embedded within broader social, political, and infrastructural arrangements rather than functioning as autonomous technological agents. Her discussions of cognitive assemblages, infrastructural thinking, and sociotechnical coevolution effectively draw from traditions associated with Manuel Castells, N. Katherine Hayles, and mediatization research. This theoretical orientation helps the book avoid simplistic technological determinism, even when its rhetoric occasionally veers toward futurist speculation.

The speculative dimension is partly what makes the book intellectually engaging. Feher captures the uncertainty surrounding generative AI exceptionally well. Rather than presenting AI development as linear or predictable, she emphasizes ambiguity, instability, and unintended consequences. Her discussion of “black swan” events, AI winters and springs, and sociotechnical errors reflects an awareness that AI systems evolve within volatile political and economic environments. This focus on uncertainty distinguishes the book from more narrowly techno-solutionist accounts that frame generative AI primarily as an efficiency tool or market opportunity.

The book is also notable for its global orientation. Feher draws from experiences across North America, Europe, Africa, and Asia, and her institutional affiliations reflect extensive engagement with international policy and research networks. While the empirical material still leans heavily toward Western AI discourse, the book nevertheless attempts to situate generative AI within broader geopolitical and governance contexts. Discussions of AI colonialism, global inequalities, and power asymmetries point toward increasingly important conversations within communication and technology studies.

Stylistically, the book is accessible without becoming overly simplistic. Feher writes clearly and often effectively translates complex technical and theoretical concepts for interdisciplinary audiences. The glossary and structured chapter design make the text particularly suitable for graduate teaching. Instructors in media studies, communication technology, digital sociology, or AI ethics would likely find portions of the book useful for introducing students to foundational debates surrounding generative AI and synthetic media. The “scholarly debates” and “strategic takeaways” sections further reinforce its pedagogical utility.

Nevertheless, some readers may find the book’s conceptual expansiveness uneven. The sheer range of topics covered—spanning attention economies, quantum computing, misinformation, emotional intelligence, AI governance, creativity, and sustainability—means that certain sections inevitably remain underdeveloped. Scholars seeking deeply focused analyses of specific communication phenomena may therefore find the book more valuable as a synthetic overview than as a specialized theoretical intervention.

The chapter “Transformation” exemplifies both the strengths and limitations of the book. Feher maps digital transformation through discussions of AI waves, datafication, quantum computing, attention economies, and human–machine cognition. The chapter is conceptually rich and highly readable, particularly for readers seeking a broad introduction to contemporary AI discourse. However, the density of concepts sometimes comes at the expense of analytical depth. The book frequently introduces major theoretical frameworks or emerging technological developments in rapid succession without fully unpacking their empirical implications. Discussions of quantum computing, Xenobots, Web3, deep tech, and posthumanism occasionally read more like intellectual inventories than sustained analyses.

This tendency reflects one of the book’s central limitations: its preference for conceptual synthesis over empirical grounding. Although Feher references numerous contemporary debates and case studies, the book rarely develops detailed empirical analyses of specific media systems, industries, or institutional practices. The discussion of AI journalism, for example, identifies important issues surrounding automation, synthetic content, and disinformation but offers limited engagement with newsroom ethnographies, labor studies, or platform governance research that would strengthen its intervention within journalism studies specifically. Similarly, the treatment of generative AI’s labor implications remains relatively abstract despite the significance of labor exploitation, data annotation, and invisible platform work in AI infrastructures (Gray & Suri, 2019).

The book’s tone occasionally oscillates between critical analysis and speculative futurism. Feher adopts what she calls a “techno-neutralist” position, seeking to avoid both utopianism and technological pessimism. Yet the text sometimes relies on dramatic metaphors and sweeping claims about civilizational transformation that risk overstating the novelty or inevitability of generative AI. Some phrases describing synthetic realities “devouring” nonsynthetic ones or suggesting that AI may fundamentally redefine existence can feel rhetorically inflated relative to the empirical evidence provided. These moments occasionally blur the distinction between analytical scholarship and speculative forecasting.

Despite some limitations, Generative AI, Media, and Society succeeds as a timely and intellectually ambitious contribution to emerging scholarship on generative AI and media transformation. Its greatest contribution lies not in offering definitive empirical conclusions but in articulating a broad conceptual map for understanding how generative AI intersects with communication systems, governance structures, and sociotechnical life. Feher convincingly demonstrates that generative AI cannot be understood solely through computational or engineering perspectives; it must also be analyzed as a cultural, political, epistemological, and infrastructural phenomenon.

For readers of the International Journal of Communication, the book is especially relevant because it foregrounds communication itself as central to AI transformation. Feher treats generative AI not merely as a tool of automation but as a communicative actor embedded within media ecologies, institutional systems, and public discourse. In doing so, she reinforces a critical insight increasingly shaping communication scholarship: that the future of AI will be determined not only by technical capability but by struggles over legitimacy, governance, trust, labor, and democratic accountability.

References

Couldry, N., & Mejias, U. A. (2019). The costs of connection: How data is colonizing human life and appropriating it for capitalism. Stanford, CA: Stanford University Press.

Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. New Haven, CT: Yale University Press.

Gray, M. L., & Suri, S. (2019). Ghost work: How to stop Silicon Valley from building a new global underclass. New York, NY: Harper Business.