Gwynne Dyer HandoutArticle content‘Artificial intelligence’ based on Large Language Models is shaping up to be the most efficient destroyer of value since the South Sea Bubble.THIS CONTENT IS RESERVED FOR SUBSCRIBERS ONLY.Subscribe now to access this story and more:Unlimited access to the website and appExclusive access to premium content, newsletters and podcastsFull access to the e-Edition app, an electronic replica of the print edition that you can share, download and comment onEnjoy insights and behind-the-scenes analysis from our award-winning journalistsSupport local journalists and the next generation of journalistsSUBSCRIBE TO UNLOCK MORE ARTICLES.Subscribe or sign in to your account to continue your reading experience.Unlimited access to the website and appExclusive access to premium content, newsletters and podcastsFull access to the e-Edition app, an electronic replica of the print edition that you can share, download and comment onEnjoy insights and behind-the-scenes analysis from our award-winning journalistsSupport local journalists and the next generation of journalistsRegister to unlock more articles.Create an account or sign in to continue your reading experience.Access additional stories every monthShare your thoughts and join the conversation in our commenting communityGet email updates from your favourite authorsSign In or Create an AccountorArticle contentAfter the Crash, some specific functions of AI will eventually turn out to be genuinely revenue-generating, and a lot of jobs will duly disappear.Article contentArticle contentBut the biggest winner (and potentially biggest loser) is medical science.Article contentArticle contentHow AI designed virusesArticle contentDr. Brian Hie, a chemical engineer at Stanford University in California, has just revealed that his team has made the first viruses designed by artificial intelligence. They are ‘bacteriophages’, viruses that only infect bacteria and are widely used to treat people with infections that resist other treatments.Article contentHowever, natural bacteriophages sometimes fail, so Dr. Hie used generative AI to design new ones that might do the job.Article contentAI generated thousands of designs for new genomes that more or less fit the bill, and he chose around 300 of them to build in the lab. It’s hard work, not magic, but he ended up with sixteen ‘novel’ bacteriophages that might work.Article contentHe applied them to petri dishes containing two harmful strains of E. coli, a common bacteria that lives in the human gut, and they killed the bacteria off. It’s still early days, but if it is truly becoming possible to tailor-make bacteriophages that target specific bacteria, then we may be getting a major new weapon in the struggle against antibiotic resistance.Article contentArticle contentThat problem is growing rapidly, as the overuse of antibiotic medicines gives bacteria endless opportunities to evolve into new, more antibiotic-resistant forms. The Institute for Health Metrics and Evaluation estimates that 1.34 million Americans will be dying each year from antibiotic-resistant diseases by 2050 (up from half a million now).Article contentWhy is this a problem?Article contentThe ability to design genomes for unique bacteriophages that target specific diseases is indisputably a good thing for health care, but it is not necessarily a great thing for the world at large.Article content“Although this is promising for life sciences application,” wrote Prof. Tom Inglesby of Johns Hopkins University, “it also raises urgent biosafety and biosecurity questions.”Article content“The ability to compose viral genomes now exists; the governance to safely steer it does not….Such genomes might encode new pathogens that cannot be contained by existing countermeasures.”Article contentProbably nothing as bad as the Black Plague or even COVID, but who knows?
GWYNNE DYER: Why medical science is both the biggest winner and loser in the AI boom
