Rebecca Solnit

In the AI Story

Solnit's intellectual formation began not in universities but in landscapes. She grew up in California's suburbs and mountains, developing what would become a career-long practice of walking as a mode of thinking. Her early work combined art criticism, landscape history, and political reportage in ways that refused disciplinary boundaries. By the time Hope in the Dark appeared in 2004—written in the wake of the Iraq War invasion and the despair that had settled over the American left—she had established a distinctive voice: fiercely analytical, deeply read, and committed to the proposition that historical change happens through mechanisms more complex and more hopeful than the institutional discourse acknowledges.

The concept that defines Solnit's contribution to the AI discourse is the distinction between hope and optimism. Optimism is a disposition—the expectation that things will turn out well regardless of what one does. Hope is a practice—the recognition that the outcome is genuinely uncertain and that this uncertainty is precisely what makes human action meaningful. If the future were already written, there would be no point in showing up. It is because the future is unwritten that showing up matters. This distinction cuts against every instinct the contemporary mind has been trained to follow, particularly in technology discourse, where the triumphalist narrative assumes progress is inevitable and the catastrophist narrative assumes collapse is unavoidable.

Solnit's 2024 London Review of Books essay "In the Shadow of Silicon Valley" crystallized her critique of the technology industry through the observation that driverless cars are called autonomous vehicles, but driving is not an autonomous activity—it is a cooperative social activity conducted through eye contact, gesture, and the implicit agreements that allow millions of strangers to share roads. When the human is removed from the vehicle, the social negotiation does not become more efficient; it becomes impossible. The observation applies, as scholars immediately recognized, to essentially every domain where AI is being deployed as a replacement for human judgment. Teaching, diagnosing, managing—these are cooperative social activities, not information-processing tasks that can be optimized through automation.

Solnit's discovery in 2023 that approximately half her published books had been scraped into AI training datasets without consent placed her in the position of someone whose life's work—decades of carefully constructed arguments about power, memory, and who gets to tell the story—had been converted into raw material for systems designed to produce fluent text without understanding. She aligned herself with Artists Against Generative AI, not because she opposed technology in the abstract, but because she recognized a familiar pattern: the extraction of value from those who create it, by those who build the infrastructure to capture it, justified by a rhetoric of progress that obscures the distribution of gains. Her response was not the howl of a Luddite but the precise anger of someone who understands systems and recognizes when power is being exercised under the cover of inevitability.

Origin

Solnit's formation as a public intellectual occurred at the intersection of three traditions: the essay as a form of public thinking (Orwell, Baldwin, Didion), the history of social movements (Howard Zinn, E.P. Thompson), and the literature of place and landscape (Barry Lopez, Annie Dillard). Her work synthesizes these traditions into a distinctive analytical method that treats historical events not as predetermined outcomes but as contested processes whose trajectories were shaped by the participation—or silence—of ordinary people. The method is empirical, grounded in archival research and direct observation, but it refuses the positivist assumption that the accumulation of facts produces understanding without interpretation.

Her long residence in San Francisco—arriving in 1980, witnessing the city's transformation from bohemian cultural center to technology-industry bedroom community—gave her a front-row seat to the social consequences of the internet revolution and the platform economy. By the time AI became a mass phenomenon in the 2020s, she had spent decades documenting displacement, extraction, and the specific forms of violence that operate under the rhetoric of innovation and progress. Her 2026 interventions in the AI discourse drew on this embodied knowledge of how power moves through cities, institutions, and the everyday texture of working life.

Key Ideas

Hope as Practice. Hope is not a feeling or a prediction but a discipline—the commitment to act as though the outcome depends on what you do, even when you cannot prove that it does. This practice becomes essential in the AI transition, where both triumphalist certainty and catastrophist despair produce the same practical result: passivity.

Disaster Communities and Spontaneous Cooperation. Research across multiple catastrophes demonstrates that when institutional structures collapse, the default human response is cooperation rather than chaos—a finding that challenges the elite panic assumption that populations cannot be trusted with power and that applies directly to the institutional vacuum of the AI transition.

History Is Not Linear. The belief in inevitable progress produces dangerous passivity; the actual shape of history is irregular, reversible, full of dead ends and sudden openings. The most important changes are the ones no existing framework predicts, which means the significant consequences of AI are likely not the ones currently dominating the discourse.

The Distinction Between the Technology and Its Governance. The problem is not AI itself but the political economy that deploys it—the ownership structures, the absence of democratic governance, the ideology that treats technological deployment as a natural force rather than a political choice. This distinction determines where interventions should go.

Small Acts, Large Consequences. The disproportion between Rosa Parks sitting down and the civil rights movement illustrates a mechanism: small acts demonstrate possibilities, demonstrations change calculations, and changed calculations accumulate into movements. The most consequential AI interventions may be the local, invisible acts that prove alternatives exist.

Debates & Critiques

Solnit's framework is contested on multiple fronts. Technology industry figures dismiss her critique as anti-innovation Luddism that ignores the genuine capability expansion AI provides. Some academic critics argue her emphasis on uncertainty and open futures underestimates structural constraints—that the concentration of AI infrastructure, the network effects of platform economies, and the political power of the technology industry make alternatives less viable than her framework suggests. Disability rights advocates have noted that her critique of autonomous vehicles insufficiently engages with the mobility benefits for people who cannot drive. Her insistence that participation matters even when outcomes are uncertain is challenged by those who argue that individual and small-scale action is structurally inadequate to forces operating at the scale of global capital and algorithmic governance.