Anthropic CEO Dario Amodei says the best way to win over AI skeptics is to deliver on the hype. In a rare post on X on Saturday, Anthropic's CEO acknowledged the public's mistrust of AI and said the industry can only change that by delivering tangible scientific breakthroughs.
"At this point, saying that AI will cure cancer is more a cliché than it is inspiring, and most people think it is deceptive," Amodei wrote. "The most accurate criticism of AI companies, including Anthropic, is that we haven't yet delivered on our big promises to benefit the world."
"The thing that will work is actually curing cancer," he added.
The AI industry is facing a growing public backlash as it builds huge data centers in communities across the country, scrapes often copyrighted online data to train its models, and upends the workforce for many industries. A recent Pew Research Center study found that about half of Americans felt the increased prevalence of AI in their daily lives made them feel "more concerned than excited."
Amodei, meanwhile, has repeatedly warned on podcasts, in essays, and in Anthropic blog posts, about the dangers posed by AI's rapid development. In a June essay, Amodei wrote that the company's new Mythos models present "very real risks" to cybersecurity, the financial sector, critical infrastructure, and national security. Last year, he warned that AI would cause half of all entry-level jobs to vanish.
Some other AI leaders have criticized the kind of rhetoric for which Amodei, who left OpenAI in 2020 over concerns about the company's attention to safety, has become famous. Google DeepMind's Demis Hassabis said earlier this year that his peers had been "way too certain" about their dire predictions and encouraged them to dial it back.
As OpenAI and Anthropic gear up for expected IPOs, they have followed that advice, pivoting from doomerism to boomerism. Amodei, however, said in his Saturday X post that he doesn't think his warnings are the cause of the public's distrust of AI.
"I do not agree that my messaging has been disproportionately negative," he wrote.
"I wrote Machines of Loving Grace because I didn't feel the AI industry was painting an inspiring enough picture of how the technology could radically transform the world for the better," he added, referring to a lengthy 2024 blog post in which he laid out how he thought AI could make the world a better place.
Instead, Amodei said that the public's distrust of AI companies reflects broader skepticism among Americans toward corporations overall. "The causes of this go back decades and AI is just the latest iteration of it," he wrote.
Anthropic's decision not to open-source any of its frontier models, which it says is out of caution, has contributed, at least in part, to the public's wariness. Anthropic drew ire last month for being the only major AI developer not to sign a letter advocating for open-weight AI as Washington considered restrictions on some Chinese models.
Yann LeCun, the former chief AI scientist at Meta, has long argued that keeping frontier AI technology closed-source, as Anthropic does, contributes to public distrust about AI more than anything else.
In an X post responding to Amodei, LeCun wrote that the "only way forward" is for AI to be "widely available, shared, and open."
"We need diverse AIs for the same reason we need a diverse press," he wrote.
As for Amodei's argument that a major scientific breakthrough could turn the tide of public opinion, not everyone agreed with that either.
Angel Brodin, an applied AI architect at OpenAI, wrote in a response to Amodei's post that despite routinely delivering advancements in public health, the pharmaceutical industry is "still one of the least trusted industries."
"People also won't judge AI companies solely by their breakthroughs," she wrote. "They'll judge them by pricing, access, lobbying, opacity, how the economic gains are distributed, who gets to participate in its benefits, and who ultimately holds the power."
Amodei, for his part, said Anthropic is ramping up work in the biological and medical fields to test that theory.
"We hope to have incredible results in the coming years and some early glimmers in the coming months," he wrote. "When we've actually accomplished something real, the whole world will hear about it, as loudly as possible, you have my word on that."