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Today’s biggest artificial intelligence (AI) startups make no shortage of bold promises. Their technologies, some boast, will revolutionize software development, drug discovery, and scientific research.
Yet a new preprint posted on 16 July on bioRxiv suggests many of these firms barely participate in one of science’s most fundamental practices: publicly documenting discoveries in scientific literature so other researchers can evaluate and build on them. More than half of AI unicorns—private companies valued at more than $1 billion—have never played a leading role in publishing a scientific paper or preprint, according to the new analysis. Collectively, they accounted for just one in every 1000 AI papers published in 2025.
“For a field that is supposedly reshaping science and is so advanced in terms of scientific potential, not having any scientific documentation seems like a very weird paradox,” says paper co-author John Ioannidis, a metascientist at Stanford University. “How can you judge that what they say is real, validated, and reproducible?” The scarcity of publications, others say, also makes it harder to assess AI’s social impacts, including energy use and safety.
But University of Alberta AI ethicist Mohamed Abdalla says the findings reflect the incentives facing commercial AI developers, rather than solely a failure to uphold scientific norms. “It’s not the company’s job to advance science, right?” he says. “The company’s job is to advance money.”
Yet a new preprint posted on 16 July on bioRxiv suggests many of these firms barely participate in one of science’s most fundamental practices: publicly documenting discoveries in scientific literature so other researchers can evaluate and build on them. More than half of AI unicorns—private companies valued at more than $1 billion—have never played a leading role in publishing a scientific paper or preprint, according to the new analysis. Collectively, they accounted for just one in every 1000 AI papers published in 2025.
“For a field that is supposedly reshaping science and is so advanced in terms of scientific potential, not having any scientific documentation seems like a very weird paradox,” says paper co-author John Ioannidis, a metascientist at Stanford University. “How can you judge that what they say is real, validated, and reproducible?” The scarcity of publications, others say, also makes it harder to assess AI’s social impacts, including energy use and safety.
But University of Alberta AI ethicist Mohamed Abdalla says the findings reflect the incentives facing commercial AI developers, rather than solely a failure to uphold scientific norms. “It’s not the company’s job to advance science, right?” he says. “The company’s job is to advance money.”
