To Make a Real Difference in Health Care, AI Will Need to Learn Like We Do

Millions of people, many of whom have never thought much about computer science, are experimenting with generative AI models such as the eminently conversational ChatGPT and creative image generator DALL-E. While these products reflect less of a technological breakthrough than AI’s emergence into the public consciousness, the traction they have found is guiding massive investment streams—investment shaping how this technology will be applied for years to come. For those of us who have long been bullish on AI’s potential to transform society, especially in key areas such as health and medicine, recent months have felt very much like science fiction has come to life. [time-brightcove not-tgx=”true”] However, as delightful as it is to explore these capabilities—GPT-4 for example exceeded the passing score by 20 points on the U.S. medical licensing exam—the results of doing so mainly serve to highlight their shortcomings. The ability to read, retain and regurgitate all such data on demand makes today’s AI good at everything—but great at nothing. There’s no question that AI is poised to irrevocably change how we look to prevent and treat illness. Doctors will cede documentation to AI scribes; primary care providers will lean on chatbots for triage; near-endless libraries of predicted protein structures will supercharge drug development. However, to truly transform these fields, we should invest in creating an ecosystem of...
Source: TIME: Health - Category: Consumer Health News Authors: Tags: Uncategorized Innovation Technology TIME 2030 Source Type: news