AI’s Hype, Dangers, and Resistance: Monthly Review’s Part III Turns Toward Media, Labor, and Power
AI’s Hype, Dangers, and Resistance: Monthly Review’s Part III Turns Toward Media, Labor, and Power
The third installment of Monthly Review’s series “Artificial Intelligence: the hype, the dangers, and the resistance” was republished on August 15, 2026, after first appearing through Report from the Economic Front on August 13, 2026. The article is part of an ongoing structural critique of artificial intelligence, examining how the technology is promoted, who benefits, what harms it creates, and where organized pushback is emerging.
The series title itself provides the analytical frame. “Hype” refers to the industry claims that often accompany AI adoption; “dangers” points to the social and economic harms linked to rapid deployment; and “resistance” signals collective responses by labor, civil society, creators, educators, and public-interest policy actors.
A Political-Economic Critique of AI
Monthly Review has long positioned itself within a left-leaning tradition of political economy, and the AI series follows that approach. The Part III installment continues the focus on ownership and control of AI systems, the concentration of profit, and the shifting of costs onto workers, users, and broader society. In that framing, the central questions are structural: who owns the systems, who captures the gains, and who absorbs the risks.
The article also sits at an intersection with the internet and media ecosystem. The context highlights journalism, content production, information quality, and platform power as areas of concern. That means the analysis reaches beyond automation in factories or offices and into the machinery of news distribution, search, recommendation systems, and the economics of digital publishing.
Media, Information Quality, and Platform Power
For newsrooms and media workers, AI tools are increasingly embedded in workflows: generating summaries, transcribing interviews, optimizing headlines, and, in some cases, producing synthetic content. The series’ focus on hype and harm creates space to ask whether those tools improve news quality or intensify problems such as misinformation, copyright disputes, and dependence on a small number of platform companies.
The internet and media angle also raises questions about who gets to define truthful information when AI systems are trained on large datasets and operated by dominant platforms. In that context, journalists, publishers, and content creators are not neutral observers; they are among the groups whose labor and output are directly affected by AI deployment.
What Resistance Looks Like
The “resistance” element suggests that Part III is not solely a catalog of risks. It points to unions, regulators, creators, educators, and community advocates challenging AI deployment through bargaining, policy proposals, legal action, or public campaigns.
Labor organizations have raised concerns about job displacement, surveillance, and the use of AI in management decisions. Civil society groups have questioned algorithmic bias and transparency. Publishers and creators have pushed back on the unlicensed use of copyrighted material in training data. Educators and researchers have debated whether AI systems should be subject to independent audits and public accountability. The series, by foregrounding these responses, treats resistance as part of the AI story rather than an afterthought.
The three-part lens of “hype, dangers, and resistance” frames AI not as an inevitable force, but as a contested set of technologies shaped by ownership, policy, and collective action.
For readers tracking the regulatory and policy side of that contest, several public-interest frameworks offer detailed guidance. The U.S. National Institute of Standards and Technology maintains an AI Risk Management Framework that outlines ways to identify and manage AI risks. UNESCO publishes a Recommendation on the Ethics of Artificial Intelligence, and the OECD hosts an AI Policy Observatory tracking national approaches.
Because Monthly Review readers expect a structural critique, the Part III installment connects these concerns to larger questions of economic power rather than treating AI as a standalone technology problem. The article’s publication history, moving from Report from the Economic Front to Monthly Review, signals a readership already engaged with political economy, labor, and media analysis.
The series does not present itself as a neutral technical explainer. Instead, by pairing the word “hype” with “dangers” and “resistance,” it foregrounds a debate about who controls AI and how societies can respond to harms that are already being distributed unevenly.
