top of page
  • Mariane Bunn

Generative AI in healthcare

A scene with some lab and medical symbols is formed. These symbols are surrounded by doctors dressing white, in a very small proportion to the image.

Generative AI, a technology capable of creating and analyzing various forms of data including images, text, and videos, is increasingly being integrated into the healthcare sector by both major tech companies and startups. Google Cloud is partnering with Highmark Health to develop AI tools for a personalized patient intake process, while Amazon's AWS is exploring ways to use AI for analyzing medical databases. Microsoft Azure is collaborating with Providence healthcare network to automate the triaging of patient messages.

Several startups, such as Ambience Healthcare, Nabla, and Abridge, are also making strides in healthcare-focused generative AI, attracting significant venture capital investment. Despite this growing interest, opinions on the readiness of generative AI for healthcare are divided among professionals and patients. Concerns include the technology's current limitations, such as its inability to handle complex medical queries effectively, leading to potential misdiagnoses or inappropriate treatments.

Studies have highlighted these issues, with AI systems like OpenAI's ChatGPT making errors in diagnosing diseases or failing in administrative tasks. Moreover, there's worry that generative AI could perpetuate stereotypes, as seen in instances where AI provided biased medical advice. Despite these challenges, some experts believe generative AI can still be beneficial in areas like medical imaging and administrative tasks, provided it's used under close supervision by healthcare professionals.

The deployment of generative AI in healthcare faces hurdles related to privacy, security, and regulatory compliance. The World Health Organization has called for rigorous science, human oversight, and independent audits to ensure the safe and effective use of AI in healthcare. Until these concerns are adequately addressed, the widespread implementation of generative AI in healthcare remains a cautious endeavor.

Source: TechCrunch


bottom of page