This simmering discontent boiled over recently when 20-year-old Daniel Moreno-Gama was charged with attempted murder and arson after allegedly throwing a Molotov cocktail at the San Francisco residence of OpenAI CEO Sam Altman, a property he shares with his husband and one-year-old child. Authorities reported that after the alleged explosive attack, the Texas man proceeded to OpenAI’s offices, where he reportedly threw a chair at the building’s glass doors, threatening to ignite the premises and harm anyone inside. He was subsequently arrested while in possession of a jug of kerosene. Court documents reveal Moreno-Gama’s writings expressed concerns about AI’s existential risk to humanity, referencing an “impending extinction,” and a document found on him reportedly listed other AI companies as potential targets. His attorney has since indicated that Moreno-Gama was experiencing a mental health crisis during these events.
A Wave of Incidents and Reactions
The attack on Altman’s home was not an isolated incident but rather part of a disturbing pattern. Just two days later, two additional suspects were apprehended after allegedly discharging a firearm near the CEO’s property. Earlier in the month, a separate incident saw 13 shots fired at the front door of an Indiana councilman’s home, with a note left behind explicitly stating, “No Data Centers.” These acts underscore a growing, and increasingly aggressive, public sentiment against the rapid, largely unregulated expansion of AI technology and its associated infrastructure.
Reactions to these events have been sharply divided. Prominent critics of Altman and the broader AI industry have unequivocally condemned the violence. Alex Bores, a former Palantir employee now campaigning for Congress on a pro-AI regulation platform, described the Molotov attack as “unwarranted and unacceptable.” He stated, “Sam and I may disagree on many things, but we are all human and we cannot allow ourselves to lose the humanity at the heart of the debate over the future of AI safety.” This sentiment reflects a desire to maintain civil discourse even amidst profound technological disagreements.
However, the response on social media platforms presented a stark contrast, revealing a disturbing undercurrent of celebration and even encouragement for the attacks. Commenters inquired about contributing to Moreno-Gama’s bail fund, while others made light of the Molotov cocktail itself. One X user declared, “I care about Sam Altman’s humanity as much as he cares about mine,” directly challenging the notion of shared empathy. Another user lauded the acts, asserting, “Trying to stop the AI apocalypse is a heroic action, not a criminal one. The criminals are the AI CEOs who want to kill humanity & replace us with robots.” This rhetoric highlights a radicalized segment of the public that perceives AI developers not as innovators, but as existential threats, justifying extreme measures. The unsettling similarity to reactions following the 2024 murder of United HealthCare CEO Brian Thompson, where social media users joked about providing false alibis for the prime suspect, Luigi Mangione, was noted by Suresh Venkatasubramanian, director of the Center for Tech Responsibility at Brown University. Reports from the Wall Street Journal further linked Moreno-Gama to online discussions months prior where he mentioned Mangione and the United HealthCare CEO shooting, underscoring a potential influence or shared extremist ideology. This parallel prompted OpenAI’s offices to reportedly issue a directive advising employees to conceal their badges when leaving, a policy reminiscent of those adopted by United HealthCare.
The Deepening Chasm of Public Mistrust
The celebratory response to these violent acts serves as a stark indicator of the public’s escalating anger and resentment towards AI companies, the burgeoning data center industry, and the tech billionaires who helm them. AI experts, who have consistently voiced concerns within the tech community about the dangers of developing AI without adequate guardrails, view these public reactions as an alarming intensification of mistrust that has been steadily building for years.
Data from Stanford’s 2026 AI Index Report paints a clear picture of this widespread anxiety. The report found that a significant 64 percent of U.S. adults believe AI will inevitably lead to job losses. More than half, 52 percent, expressed nervousness about products and services utilizing AI, while a commanding 79 percent believe that companies should be mandated to disclose the use of AI in their offerings. These figures underscore a pervasive sense of unease and a demand for transparency and accountability that the industry has largely failed to meet.
Safiya Noble, a digital media professor and author of Algorithms of Oppression, characterizes the current climate as firmly within the “techlash”—a widespread backlash against the tech sector and its billionaire leaders, whom she describes as “obsessed and preoccupied with their sci-fi fantasies of the future.” This "techlash" is not merely about fear of the unknown; it’s rooted in tangible societal and economic anxieties.
Alondra Nelson, who previously directed the Biden administration’s Office of Science and Technology Policy, elaborates on the evolution of this negative sentiment. She notes that while public concern around AI has grown steadily, what has changed is that “the public has developed both the vocabulary and the lived experience to name what’s bothering them.” These grievances encompass a range of issues: the exorbitant energy costs associated with AI infrastructure, the looming threat of job displacement, instances of algorithmic discrimination, the dangerous concentration of power within a select few corporations, and the perceived harm to young people through AI-driven content. Crucially, Nelson highlights a “profound sense of a lack of agency and empowerment in the face of all of this,” suggesting that people feel their concerns are being ignored by both industry and government.
The Tangible Manifestation: Data Centers as Flashpoints
As AI companies have expanded their operations, so too have their plans for constructing massive data centers across the country. These facilities, which are essential for powering AI models, consume enormous quantities of water and electricity. Their construction has often led to the displacement of residents, particularly in the Southern U.S. where much of this development has been concentrated. Consequently, data centers have become increasingly unpopular and a literal flashpoint for public anger. Maine recently enacted the first statewide ban on such facilities, and prominent progressive lawmakers like Bernie Sanders and Alexandria Ocasio-Cortez have introduced federal legislation aimed at halting data center construction until more robust regulations are in place.
Nelson succinctly captures why these facilities have become such potent symbols of discontent: “Data centers are the physical manifestation of AI infrastructure, and they’ve become a flashpoint precisely because they’re tractable. They exist in specific places, they consume specific resources, they can be seen and pointed to.” Unlike the abstract concept of AI, data centers represent a concrete, visible, and often disruptive impact on local communities and the environment.
Beyond the Concrete: Abstract Fears and Societal Harms
While data centers embody the tangible ways AI is altering lives, more abstract and ambiguous fears are also reaching a critical point. Suresh Venkatasubramanian, from Brown University’s Center for Tech Responsibility, points to a “growing concern, broadly.” He cites “the horrible events last summer with teenagers getting sucked into AI-fueled psychosis and committing suicide,” highlighting the severe, even fatal, mental health impacts that unregulated AI interactions can have. This, combined with the pervasive rhetoric from tech companies about the “cost savings” that will result from replacing human labor with machines, is “creating a lot of fear in every sector of society.”
Noble further emphasizes the industry leaders’ explicit declarations about AI eliminating jobs as a significant catalyst for public backlash. She argues that these companies have “stolen all the works of humanity—the books, the art, everything we’ve ever put on Reddit,” then sought to “monetize and sell it back to us and defund education, libraries, public health institutions.” This perception of exploitation and intellectual property theft, coupled with the threat to livelihoods and public services, fuels a deep sense of injustice. “People are not stupid,” Noble asserts, predicting a continued growth in backlash as communities increasingly experience the destabilizing effects of faulty tech products on their institutions.
Historical Parallels: The Luddite Legacy Revisited
The current wave of resistance to AI is not without historical precedent, as economist Carl Benedikt Frey, author of The Technology Trap, points out. His work traces the history of technological progress from the Industrial Revolution to the advent of AI, revealing a consistent pattern of public reaction to disruptive innovations.
“If a technology threatens people’s jobs and skills, which is essentially what most people derive their income from, they’re quite likely to resist it, and rightly so,” Frey explains. He references the Luddites, the 19th-century British textile workers who famously destroyed automated looms, often portrayed as irrational enemies of progress. Frey argues this portrayal is simplistic: “they were not the ones who stood to benefit from mechanized factories and so their opposition made sense.” Economists often emphasize the long-term benefits of technology, such as increased availability and affordability of goods, but Frey notes that people “live in the present.” If they perceive an immediate threat to their livelihoods, resistance and skepticism are natural and rational responses.
A distinguishing factor in the current era, relative to previous episodes of technological change, is that “even the makers of the technology are actively warning about this risk,” Frey observes. He points to Dario Amodei, CEO of Anthropic, who has publicly warned that AI could displace half of all entry-level white-collar jobs and, in a worst-case scenario, even “destroy all life on Earth.” When the creators themselves voice such dire predictions, it inevitably amplifies public anxiety and legitimizes fears that might otherwise be dismissed as irrational.
Frey also notes that societal resistance to automation tends to intensify during periods of economic downturns, citing examples like the Great Depression and recessions in the 1960s. The current geopolitical landscape, marked by conflicts like the war in Iran, coupled with higher interest rates and an unstable job market, creates a potent cocktail for heightened public anxiety. Furthermore, communities become frustrated when their views are not reflected in policy decisions. “If people feel that, showing up at the ballot box, they’re not getting their voice heard, they may use other means to try to get the voice heard,” Frey states, while not condoning violence. He concludes, “One shouldn’t be surprised that if people feel that they are not likely to benefit from a technology, they are going to resist it. And if they feel that the political system is not delivering or responding to their concerns, then you’re more likely to see activism, which should preferably be nonviolent.”
The Path Forward: Trust, Guardrails, and Shared Power
For AI safety experts like Venkatasubramanian, the imperative is clear: tech companies must actively work to rebuild public trust. “Everyone, collectively, is feeling this sense of the world is shifting around us,” he says. “We don’t know how it’s going to play out, but the people we look to, whether it’s [national] politicians or tech leaders seem to have no answers or don’t care.” This perceived indifference from those in power exacerbates public frustration and fuels the growing mistrust.
AI ethicists have long advocated for the implementation of guardrails and protections around AI tools, likening them to the necessity of seatbelts in cars or lanes on highways. Such regulations, they argue, do not stifle progress but rather enable faster, safer advancement. “You don’t get to a place of trust by just convincing people to trust companies and others, you get to it by acting,” Venkatasubramanian asserts. He laments the lack of decisive action at the national level, noting that while states have attempted to legislate, their efforts are often hampered by the very tech companies that parachute in to block regulations aimed at building trust and establishing guardrails for AI.
Nelson emphasizes that beyond regulating energy consumption, pollution, and environmental impact, there must be genuine corporate accountability. She calls for “actual governance structures with teeth,” moving beyond mere messaging or public relations efforts. For Nelson, “The path forward is not better messaging. It’s sharing power.” This sentiment encapsulates the core demand of a public feeling disenfranchised and threatened by a technology that is rapidly reshaping their world, without their consent or adequate protection. The recent surge in violent acts, while condemned by many, serves as a grim warning of the profound societal unrest that can erupt when trust erodes and concerns are left unaddressed.
