Blog · Book Review · Last reviewed July 2, 2026

The Undersea Network and the Ocean Floor of the Internet

Nicole Starosielski's The Undersea Network is a book about the part of the internet that refuses to become metaphor. The cloud is not in the air. Wireless life is carried by fiber, beaches, cable stations, ships, permits, repair regimes, island histories, military routes, finance, and ocean ecologies. Its AI-era lesson is direct: every model call travels through infrastructure that has owners, chokepoints, jurisdictions, maintenance labor, environmental conditions, and political histories.

The Book

The Undersea Network was published by Duke University Press in March 2015 in the Sign, Storage, Transmission series. Duke lists the book at 312 pages, with 55 illustrations, and gives the paper ISBN as 978-0-8223-5755-1, the hardcover ISBN as 978-0-8223-5740-7, and the electronic ISBN as 978-0-8223-7622-4. Google Books gives the same publisher, 2015 date, and 312-page length.

The book follows submarine cable systems from deep ocean routes to landing zones and cable stations, especially across the South Pacific. Starosielski's method is not only technical history. It is media archaeology, infrastructure studies, fieldwork, and environmental attention joined together. The book asks readers to stop imagining communication as pure flow and start looking at the places that make flow possible.

Duke also points to Surfacing, the interactive companion project by Nicole Starosielski, Erik Loyer, and Shane Brennan, with additional writing by Jessica Feldman and Anne Pasek. That companion matters because the book is not only about hidden cables. It is about a method for making hidden infrastructure narratable without flattening it into a single global map.

Against Flow

The book's first major intervention is conceptual. The internet is usually described through movement words: flow, stream, traffic, cloud, feed, link, route. Those words can be useful, but they can also make infrastructure feel weightless. Starosielski pushes in the other direction. A cable route is not a line on an abstract graph. It is a negotiated path through ocean space, coastal property, regulation, repair capacity, corporate investment, military history, and local conflict.

That shift from topology to topography is the book's core discipline. Topology asks how nodes connect. Topography asks where the connection runs, what it crosses, what it avoids, who maintains it, what histories it reuses, and what happens when it lands. The difference matters because politics often appears at the landing point, not in the network diagram.

Read this way, the cable is neither a neutral pipe nor a romantic relic. It is a working arrangement. Its path embodies old routes, new incentives, technical constraints, environmental permissions, institutional risk calculations, and public invisibility. The internet becomes less like a placeless cloud and more like a set of maintained corridors through the world.

Landing Stations

Starosielski is especially good at the shore. Cable systems spend much of their public life unseen, but they have to come ashore somewhere. A landing station is where the planetary network becomes local infrastructure: a building, a beach, a fence, a permit, a security practice, a neighbor, a labor process, and a vulnerability.

This is where the book is useful for AI infrastructure. Model systems are often discussed at the level of benchmark, parameter count, product feature, or policy document. But every service also has landing points: data centers, cloud regions, fiber routes, exchange points, power substations, water systems, workforces, content-moderation queues, and customer institutions. The political question is not only what the model can do. It is where the system touches the world and who lives with that touch.

The landing point also breaks the fantasy that resilience is only a cybersecurity problem. Cable resilience involves geography, maritime activity, repair ships, permitting, route diversity, physical security, spare parts, cross-border coordination, and the less glamorous work of maintenance. The same lesson applies to AI: reliability is not achieved by model evaluation alone. It depends on the material and institutional system around the model.

The Pacific Network

The Undersea Network keeps returning to Pacific sites because submarine cables do not only connect powerful centers. They also pass through islands, colonial histories, military routes, tourism economies, environmental zones, and communities whose relationship to the network cannot be summarized by the word "node."

That distinction matters. A node is a point in a system. A place is lived, governed, contested, remembered, repaired, and exposed. Technical maps often need nodes because systems require abstraction. Starosielski's warning is that abstraction becomes politically dangerous when the node replaces the place in public memory.

This is one reason the book belongs near AI governance. AI systems also convert places and people into nodes: users, accounts, workers, edge devices, datasets, regions, tenants, assets, and risk objects. Those abstractions are administratively useful. They become harmful when the abstraction is allowed to stand in for the full social, environmental, and historical reality it compresses.

The AI Infrastructure Reading

As of July 2, 2026, Starosielski's book reads less like media-history recovery and more like an AI-infrastructure manual. The International Telecommunication Union's submarine-cable backgrounder, last updated in April 2026, says submarine cables carry approximately 99% of the world's Internet traffic and enable critical services including financial transactions, cloud computing, and government communications. ITU's 2026 Porto Summit release described about 500 cables extending more than 1.7 million kilometers, and its 2025 Global Connectivity Report chapter said hyperscale technology companies now play a leading role in financing new submarine-cable infrastructure.

The Federal Communications Commission made the AI connection explicit in its August 7, 2025 statement on submarine cable buildout and security, saying that cable systems carry roughly 99% of global internet traffic and are key to AI and next-generation technologies. That framing matters because it moves submarine cables from telecom background to AI governance foreground.

A prompt sent to a hosted model is not just a string entering a model. It is a packet path through devices, access networks, exchange points, terrestrial fiber, submarine systems, landing stations, cloud regions, GPUs, storage, logging systems, policy filters, and return routes. The visible interface may be conversational. The operating reality is infrastructural.

This changes the meaning of "cloud dependence." An institution using AI through a remote API is also depending on route diversity, cable repair capacity, coastal regulation, data-center siting, vendor contracts, grid load, water use, jurisdictional control, and the business decisions of companies that own or lease capacity. The system is not only a software subscription. It is a geography of dependency.

Governance and Resilience

The governance lesson is practical: maintain an infrastructure dependency register before the dependency becomes invisible.

For AI systems, that register should include model and vendor, hosting region, data-center dependencies, network routes where known, cable exposure for cross-border services, fallback paths, outage behavior, data-residency claims, logging locations, incident contacts, repair assumptions, exit plans, and the public services that would fail if connectivity degraded. This is not an argument for making every route public in a way that weakens security. It is an argument that responsible institutions should know what they depend on.

Starosielski also complicates resilience language. Resilience is not just redundancy for rich centers. It can involve underserved regions, island geographies, repair delays, permitting bottlenecks, and the uneven capacity to recover from disruption. ITU's 2026 Porto Summit guidance emphasized repair times, regulatory procedures, geographic diversity, redundancy, and risk mitigation. Those are governance topics, not background engineering details.

The AI version is clear. If schools, hospitals, emergency services, courts, government offices, or workplaces build everyday operations around cloud AI systems, they need manual fallbacks, local continuity plans, vendor-exit rights, incident procedures, and public accountability for outages and degraded modes. A resilient AI institution is not one that assumes the model will always answer. It is one that can keep serving people when the network, vendor, model, or policy layer does not.

Where the Book Needs Friction

The Undersea Network is not a contemporary AI book. It predates the current foundation-model boom, hyperscaler cable strategies at today's scale, agentic AI products, and the 2025-2026 regulatory fight over submarine cable security. Its strength is method, not direct policy prescription.

The book also has a focused geography. Its South Pacific emphasis is a virtue because it prevents the network from becoming abstract, but it means readers still need other work on the Atlantic, Arctic routes, African connectivity, cable ownership, national-security review, repair-ship availability, terrestrial backhaul, exchange points, and data-center geography.

There is also a tension in making hidden infrastructure visible. Public understanding supports accountability, but full visibility can create security concerns. The answer is not secrecy as a default or exposure as a reflex. It is layered accountability: enough public knowledge for democratic governance, enough operational confidentiality for security, and enough institutional documentation that affected communities are not asked to trust a system nobody will describe.

What This Changes

The practical lesson is to stop treating AI as an interface floating above infrastructure.

Every serious AI deployment should ask: where does the signal travel, who owns or controls the path, what happens at the landing points, what jurisdictions touch the route, who can repair it, who can interrupt it, what communities host the supporting infrastructure, what energy and water systems are implicated, and what institutional service fails if the path fails?

That is not anti-cloud nostalgia. It is source discipline applied to infrastructure. The more institutions outsource cognition, administration, search, writing, triage, education, and public interaction to remote model systems, the more they need to understand the physical network underneath that outsourcing.

Starosielski's enduring value is that she gives the internet a floor. Once the network has a floor, AI has a geography. Once AI has a geography, governance can ask material questions before the system hides inside convenience.

Source Discipline

This review separates three source layers. Book metadata and publication context come from Duke University Press and Google Books. The companion-project description comes from Duke and Surfacing. Current submarine-cable and AI-infrastructure context comes from ITU's April 2026 backgrounder, ITU's 2026 Porto Summit release, ITU's 2025 Global Connectivity Report chapter, and the FCC's August 7, 2025 submarine-cable statement.

The analogy is limited. Starosielski did not write about foundation models, agent platforms, or cloud AI procurement. The narrower claim here is that her infrastructure method makes those systems legible: AI depends on physical routes, coastal sites, operators, jurisdictions, repair regimes, and places that should not disappear behind the language of cloud service.

Sources

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