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Why Emma Pierson’s essay is causing such a stir
Emma Pierson’s recent essay in The Atlantic, “I’d Rather Risk Cancer Than See AI Move This Fast,” has naturally stirred up strong opinions in the artificial intelligence community this week. The accelerationists on X, in particular, seemed triggered by it.
Pierson is an AI researcher who teaches machine learning in the vaunted computer science program at the University of California, Berkeley. She also carries a gene mutation that can increase the risk of ovarian or breast cancer. In fact, she recently had her ovaries removed to reduce her chances of developing the disease.
Her argument isn’t that AI will never help cure cancer. It’s that the huge generalist AI systems being developed at labs like Anthropic, OpenAI, and Google may one day help defeat disease, but they also carry more immediate societal risks, including mass unemployment, inequality, surveillance, and weapons development. “[I] will wait a little longer for a cure—even if it means losing my fertility and living under the shadow of risk—if it lets us approach this new world more carefully,” she writes.
Pierson’s piece quickly caught the attention, and then the fury, of thousands of AI accelerationists on X. After all, she was challenging one of their most prized arguments, which is that anything less than driving hard toward powerful AI models is inhumane because it could deny millions of people suffering from cancer and other diseases a chance at a cure. In his 2023 manifesto, Marc Andreessen wrote: “We believe any deceleration of AI will cost lives. Deaths that were preventable by the AI that was prevented from existing is a form of murder.”
Andreessen had this to say about Pierson’s article on X: “Did cancer write this?” The post got 15,000 likes and almost a thousand retweets.
AI company leaders often say they are most excited about AI’s potential to accelerate scientific research, including the search for cures. But Pierson argues that the huge, generalist models aren’t specifically designed to cure disease, and still seem far from delivering major improvements in patient outcomes.
She explains why. AI labs are showing impressive progress in areas like coding and math, where training data is abundant and “ground truth” answers are available. Cancer is different. “Cancer data are finite and come from biological experiments and clinical trials that cannot run at silicon speeds,” Pierson writes. “And cancer data only imperfectly illuminate the complex processes by which our own cells betray us. There are, in short, many barriers to curing cancer beyond a lack of intelligence.”
Beyond the practical question of whether generalist AI models can cure disease, Pierson is making a broader argument. Humans have been the most intelligent beings on the planet for roughly 300,000 years. Now they are building synthetic intelligence that could become many times smarter than they are. If that happens, there is a real danger that humans will outsource much of their mental labor to machines and, in doing so, lose touch with the very human pursuit of knowledge.
Pierson seems to suggest that such outsourcing carries a cost, even when human lives are at stake. “For my own part, I would neither spend months struggling with a research problem I knew AI could solve instantly nor find as much pleasure in the answers it provided,” she writes. “I do not want to be merely a spectator to the universe, whatever wonders AI may reveal.”
“Incredible reason to not want to save millions of lives,” scoffed Justine Moore, a partner at the Andreessen Horowitz venture capital firm, on X. But I think Pierson was making a broader point. She doesn’t doubt that AI could play a major role in defeating cancer. She is arguing that if we are on the cusp of artificial superintelligence, now is the moment to make thoughtful decisions about which tasks should remain human, rather than delegating every damn thing to machines because it’s convenient for users and highly profitable for model makers and their investors.
Alex Bores, who AI industry forces both opposed and backed, loses bid for Congress
Alex Bores, whose primary campaign became a flashpoint in the fight over AI regulation, lost his bid Tuesday night to succeed Rep. Jerry Nadler, Democrat from New York.
Bores became a prominent figure in that debate after a political action committee (PAC) backed by AI leaders spent millions to defeat him. As a New York State Assembly member, he spearheaded an influential AI safety bill. Before entering office in 2022, he worked as a data scientist at the shadowy AI firm Palantir.
“Though we’ve come up short tonight, the example set here tonight was not the one the AI oligarchs intended,” Bores said in a concession statement Tuesday night. “They set out to make people afraid to stand up to them. Instead they learned just how ready people are to push back.”
By Wednesday, nearly every side of the AI debate was claiming some version of victory. Think Big, a group affiliated with Leading the Future, a PAC backed by leaders at OpenAI and Andreessen Horowitz, spent $8 million on ads and direct mail attacking Bores. Leading the Future says it wants a uniform federal framework for regulating AI models.
Another group, Jobs and Democracy PAC, which is tied to Public First Action, a super PAC network linked to Anthropic, spent more than $11 million supporting Bores. Jobs and Democracy PAC says it aims to elect Democrats who will “stand up to Big Tech companies trying to buy their way out of sensible AI regulation.”
Bores had hoped to turn that attention, and growing public concern about AI, into a win in New York’s Twelfth Congressional District, which covers parts of Manhattan. But AI wasn’t the only force shaping the race. Michael Bloomberg, the former New York City mayor, gave $10 million to a super PAC supporting Micah Lasher, his former aide, who won the primary.
It’s hard to say whether the race will have a lasting effect on national AI policy. Public opinion on AI is already fairly entrenched, and millions of dollars in attack ads can only do so much to move it.
In one sense, Leading the Future with its opposition to Bores may have gotten a worse result than a Bores victory. Dean Ball, an AI policy analyst, noted that Bores was relatively centrist on AI, while Lasher supports a moratorium on AI data centers, the crucial infrastructure behind the spread of AI. “LTF’s ‘victory’ here is that a guy who supports a data-center moratorium won, and the guy who supports frontier transparency and auditing (which LTF now supports!) lost,” Ball tweeted Wednesday. “Is that really a win?”
Still, the race offered an early look at how AI money may shape congressional contests around the country.
In the U.S. at least, ChatGPT is maintaining its lead among chatbots
New Pew Research survey data shows that Americans are far more aware of, and more handy with, AI chatbots—especially ChatGPT—than they were just a couple of years ago.
Here are some selected nuggets:
- Usage: 36% of Americans say they interact with AI at least several times a day.
- Chatbot share: Americans (44%) report using ChatGPT far more than other chatbots, followed by Google’s Gemini (24%), Microsoft’s Copilot (17%), Meta AI (14%), xAI’s Grok (8%), and Anthropic’s Claude (6%).
- More good news for OpenAI: The percentage of Americans who say they use ChatGPT more than doubled from 2023 (18%) to 2026 (44%).
- Chatbot uses: The top three uses for chatbots in 2026 are search and information retrieval (42%), tasks at work (38%), and fun and entertainment (25%). One in 10 people say they use chatbots for emotional support.
- AI in search: A majority of Americans (60%) say they read AI summaries at the top of search results.
- AI advancement: Roughly two-thirds of Americans (63%) say AI is advancing too quickly, while only 2% say it’s advancing too slowly.
- Regulation and governance: Two-thirds of Americans (67%) have “little to no confidence” in the government to regulate AI effectively. About six in 10 adults are “not confident” in U.S. companies to develop and use these tools responsibly.
More AI coverage from Fast Company:
- One fake web page can be enough to trick AI shopping recommendations
- Daters say AI dependence gives them the ick
- Can we trust scientific images in the era of AI?
- Satya Nadella is asking the right AI question
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