How does AI actually kill a billion people? Here is one of the many ways.
An MIT team led by Kevin Esvelt took the DNA of the 1918 influenza virus, split it into fragments, and ordered them from 38 synthesis providers. 36 shipped. No screening triggered. Pieces of a pandemic virus, arriving in the post.
That barrier was already lower than you think. AI lowers the rest.
AI does not build a pathogen end-to-end, at least not yet. But it considerably lowers the expertise you used to need. In August, a Stanford team used an AI model to design an entirely new virus from scratch. Out of nearly 300 synthetic genomes, 16 were viable. A mix of these AI-made viruses wiped out their bacterial target, which had already become immune to natural viruses.
Nature does not optimize viruses to kill us. Ebola, for example, kills about half the people it infects, but because it makes people visibly sick very fast, it is relatively easy to contain and quickly runs out of targets. An artificial pathogen has no such constraint. A synthetic virus could be optimized to combine extreme lethality with a long, hidden incubation period, a combination that rarely happens in nature. And an attacker does not have to stop at one. They could release a hundred at once.
Every year, if not every month, the hard part gets less hard.
I don't think what I just said is sufficient for extinction. Someone is always in a submarine, and some AI CEOs have allegedly invested in bunkers. But this could end in billions of casualties.
Every year, if not month, the hard part gets less hard. This is an emergency. We need to urgently scale up pandemic preparedness and implement basic measures like robust DNA synthesis screening, while also establishing strong governance for this technology.