OpenAI and Anthropic CEOs are both so annoying! Doomsday theories and relative deprivation make American people dislike AI.

Silicon Valley’s “All-In Podcast” says American society is growing resentful toward AI, with data centers becoming the target for both anti-wealth sentiments and fears of unemployment.

When Silicon Valley’s well-known podcast “All-In Podcast” discussed the AI industry, it made a particularly sharp observation: America’s attitude toward AI is shifting in a negative direction, and the most concrete outlet for this sentiment is the data centers that AI companies are rushing to build across the United States. The source of this resentment could include AI doomsday theories, fears of job loss, or a deeper sense of dissatisfaction: the new wave of technological innovation seems once again to make only a few people extremely wealthy, while most people’s lives do not see any obvious improvement.

U.S. local governments have already overturned data center construction cases

Chamath Palihapitiya said on the show that the problems facing the AI industry are not only model competition, capital expenditure, or a shortage of computing power, but that “Americans as a whole are becoming increasingly resentful of AI.” He noted that the source of this resentment may include AI doomsday theories, fears of unemployment, or a deeper dissatisfaction: it seems that each new wave of technological innovation will again make a small number of people rich—“even creating a batch of trillion-dollar billionaires”—while most people’s lives still do not see clear improvements.

Chamath believes that once this kind of emotion accumulates to a certain level, the action most likely to be taken by local communities is to oppose data centers. He gave an example: in the U.S., some local governments originally approved a $6 billion data center construction project, but later, the election replaced the committee members who supported the project. The newly appointed officials then tried to overturn the original decision. He believes this shows that data centers have become more than infrastructure—they have turned into political symbols of the AI industry and tech billionaires.

Another host, David Friedberg, offered a more direct explanation. He believes many Americans are “really starting to hate the rich,” and data centers have become a concrete projection of that sentiment. He described data centers as one of the most obvious physical spaces where wealth is created in the U.S., as well as the machinery that, in the eyes of ordinary people, continues to widen the gap between tech elites, political connections, and billionaires.

Friedberg said that for ordinary people, the benefits of AI are not concrete enough. Many hear every day that AI will change the world, reshape businesses, and improve productivity, but in their own lives, the improvements they truly feel may only be things like using ChatGPT to get medical advice, writing letters, or looking up information. By contrast, what they feel more directly is anxiety about job displacement, concerns that electricity prices may rise, and the massive data centers that technology companies build to train models.

So Friedberg likened data centers to “the mansion tax target of this era.” If politicians used to attack the wealthy’s second homes, mansions, or private jets, then in the AI era, data centers are the new entry point for attacks. They represent the progress of tech billionaires, but also represent the progress that others have not felt.

From a policy and industry perspective, David Sacks added that why data centers have become unpopular across multiple states in the U.S. can be broken down into several categories. First, many local communities worry that data centers consume large amounts of electricity and thereby drive up electricity bills for typical households. Sacks said that in some cases, developers in the past did seek local government approvals even before there were clear solutions for power supply, which led to backlash from local communities.

Second is the combination of AI doomsday groups and the anti-data center movement. Sacks believes that some groups that argue AI could bring catastrophic risks gradually realized that it is not easy to directly convince the public that “AI will lead to terminators,” but if the pitch is instead about data centers consuming water and electricity and damaging communities, it becomes easier to mobilize local opposition. He therefore criticized that behind some anti-data center movements there is “packaged NIMBYism.”

David Sacks criticizes Anthropic AI doomsday theories

Sacks took aim at Anthropic. He believes that in the past, Anthropic politically allied with AI doomsday theories and NIMBY groups—perhaps because Anthropic did not plan to build large data centers itself, but instead relied on hyperscalers to provide computing power. As a result, opposing data center construction was essentially like “throwing sand in the path” of competitors such as OpenAI and xAI.

But as Anthropic’s own scale grows and its demand for computing power explodes, if it also needs to personally enter the data center construction race in the future, this strategy could end up hurting itself instead.

The show also mentioned that one of the biggest bottlenecks AI companies currently face is insufficient computing power. Chamath pointed out that the market’s reaction after Allbirds pivoted into the concept of an AI data center—sending its stock soaring—may seem absurd, but it actually reflects that capital markets have already realized “a severe shortage of computing power.” He said that the AI industry lacks not only GPUs, but also land, electricity, data center enclosures, and local government permits.

This puts AI companies in a paradoxical situation: on the one hand, companies like OpenAI, Anthropic, xAI, and Meta all need more data centers to support model development and revenue growth; on the other hand, society’s resentment toward data centers is growing stronger, and local governments and residents are increasingly likely to block these constructions.

Chamath warned that if leading AI companies cannot secure enough computing power, revenue growth may not slow down because their products are not good enough, but because of a problem similar to what Friendster faced years ago: demand clearly exists, but the infrastructure cannot support it, and the company is ultimately overtaken by competitors.

Sacks also believes that if data center construction in the U.S. faces too many restrictions, computing power may move elsewhere—for example, to regions with cheaper energy, more friendly policies, and even to the U.S.’s allied countries. He pointed out that if the U.S. limits domestic data centers while also opposing allies from using U.S. technology to build AI infrastructure, it will ultimately weaken America’s own advantage in the AI race.

Silicon Valley investors: Altman and Amodei are not suitable as industry spokespersons

But the most notable part of the show is still its assessment of the AI industry’s public relations crisis. Host Jason Calacanis said bluntly that one of the biggest problems in the AI industry right now is that the people representing the industry are simply too poor at it. He compared American society’s perceptions of AI with China’s highly positive attitude toward AI, and concluded that at present, the messaging of the U.S. AI industry almost all revolves around fear, unemployment, and elite monopoly.

Jason also specifically called out that the AI industry’s public image is related to the personalities representing it. He believes that Anthropic CEO Dario Amodei has long described AI in terms of disaster, cybersecurity risks, and large-scale unemployment, which makes outsiders’ fears even deeper. Meanwhile, OpenAI CEO Sam Altman, who has long been at the center of controversy, also struggles to take on the role of persuading the public. Jason said these two “cannot be the industry’s spokespersons.”

If the AI industry wants to improve its social image, it must have the narrative redefined by people who can better explain public benefits in areas such as healthcare, education, and housing.

He argues that the AI industry must pull the narrative back toward three directions that can truly improve everyday lives: healthcare, housing, and education. In other words, AI companies cannot just tell the market how many trillion-dollar valuations they can create, nor only tell corporate clients how many labor costs they can save. They must also make ordinary people see how AI makes getting medical care cheaper, education more efficient, and housing issues easier to solve.

• This article is reprinted with permission from: “Chain News”
• Original title: “Sam Altman, Dario Amodei Are Too Annoying! AI Doomsday Theories and Relative Deprivation Fuel U.S. Public Resentment Toward AI”
• Original author: Neo