Darius Tahir reports for KFF Health News that artificial intelligence (AI) in healthcare, which is supposed to save money, requires a lot of expensive humans. “Artificial intelligence systems require consistent monitoring and staffing to put in place and to keep them working well.”
“Government officials worry hospitals lack the resources to put these technologies through their paces. ‘I have looked far and wide,’ FDA Commissioner Robert Califf said at a recent agency panel on AI. ‘I do not believe there’s a single health system, in the United States, that’s capable of validating an AI algorithm that’s put into place in a clinical care system,’” Tahir writes.
The technology will become universal and profitable, tech experts predict. “The investment firm Bessemer Venture Partners has identified some 20 health-focused AI startups on track to make $10 million in revenue each in a year.”
However, Tahir notes that evaluating whether these products work and continue to work is rather challenging. “It’s not easy for hospitals and providers to select the best algorithms for their needs. The average doctor doesn’t have a supercomputer sitting around, and there is no Consumer Reports for AI.”
Minor errors due to AI can be damaging in healthcare. “A team at Stanford University tried using large language models (LLM)…to summarize patients’ medical history. They compared the results with what a physician would write. ‘Even in the best case, the models had a 35 percent error rate,’ said Stanford’s Shah,” Tahir remarks.
“Experts interviewed by KFF Health News floated the idea of artificial intelligence monitoring artificial intelligence, with some (human) data whiz monitoring both. All acknowledged that would require organizations to spend even more money — a tough ask given the realities of hospital budgets and the limited supply of AI tech specialists.”
