Artificial intelligence is up to the challenge of reducing human suffering, experts say. Are we? (20 March 2025)

Summary

When Adam Rodman was a second-year medical student in the 2000s, he visited the library for a patient whose illness had left doctors stumped. Rodman searched the catalog, copied research papers, and shared them with the team.

“It made a big difference in that patient’s care,” Rodman said. “Everyone said, ‘This is so great. This is evidence-based medicine.’ But it took two hours. I can do that today in 15 seconds.”

Rodman, now an assistant professor at Harvard Medical School and a doctor at Beth Israel Deaconess Medical Center, these days carries a medical library in his pocket — a smartphone app created after the release of the large language model ChatGPT in 2022. OpenEvidence — developed in part by Medical School faculty — allows him to query specific diseases and symptoms. It searches the medical literature, drafts a summary of findings, and lists the most important sources for further reading, providing answers while Rodman is still face-to-face with his patient.

Experts predict that the adoption of large language models will reshape medicine. Some compare the potential impact with the decoding of the human genome, even the rise of the internet. The impact is expected to show up in doctor-patient interactions, physicians’ paperwork load, hospital and physician practice administration, medical research, and medical education.

But there are serious concerns, too.

Current data sets too often reflect societal biases that reinforce gaps in access and quality of care for disadvantaged groups. Without correction, these data have the potential to cement existing biases into ever-more-powerful AI that will increasingly influence how healthcare operates.