Emma Pierson is an artificial intelligence researcher who teaches machine learning within the renowned computer science program at the University of California, Berkeley. Outside of her academic work, she lives with a genetic mutation that elevates her risk of developing ovarian or breast cancer; recently, she underwent preventive surgery to have her ovaries removed, lowering her chance of developing the life-threatening disease.
Pierson does not argue that AI will never contribute to curing cancer. Instead, she points out that while the massive generalist AI systems developed by leading labs including Anthropic, OpenAI, and Google may one day help defeat deadly illness, they also pose immediate, large-scale societal risks that cannot be overlooked: these risks include mass job displacement, growing systemic inequality, expanded surveillance power for governments and corporations, and accelerated development of AI-powered weapons. “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 wrote.
Pierson’s essay quickly drew attention, and then fierce backlash, from thousands of AI accelerationists on X. Her argument directly challenged one of the movement’s most cherished core claims: that any slowdown in the push to build ever more powerful AI models is inhumane, because it withholds potential life-saving cures from millions of people living with cancer and other terminal illnesses. In his 2023 widely circulated tech manifesto, Marc Andreessen put it bluntly: “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.” When Andreessen commented on Pierson’s piece on X, he snarked: “Did cancer write this?” The dismissive post earned more than 15,000 likes and nearly 1,000 retweets.
Leaders of AI companies frequently highlight AI’s potential to speed up scientific research, particularly the search for cures for deadly disease. But Pierson counters that today’s large generalist models are not purpose-built to cure illness, and they are still far from delivering significant, tangible improvements to patient outcomes.
Why Emma Pierson’s essay is causing such a stir
