Generative artificial intelligence has taken off in recent months after OpenAI's ChatGPT wowed the public with its achievements. But healthcare is a space that remains highly skeptical, according to a new GE HealthCare (GEHC) survey.

At least 55% of medical professionals say AI is not ready for medical use, the international GE survey revealed. Of those asked, 42% globally — and only 26% in the US — think AI can be trusted. The survey included 7,500 clinicians, such as doctors, physician assistants, and public health medics, as well as patients and patient advocates in eight countries.

GE HealthCare's chief technology officer Dr. Taha Kass-Hout, who has been an advocate of AI and technology's use in health care, said he understands the apprehension found in the study, which was also reflected in recent work by BMJ, a medical journal. ("The risks associated with medicine and healthcare include the potential for AI errors to cause patient harm (and) issues with data privacy and security," said BMJ.)

...the experience sucks. Getting data out [is] really, really hardDr. Taha Kass-Hout, GE HealthCare's CTO

Kass-Hout said it is important to start addressing the needs and pain points of clinicians, who have often had to deal with technology that is not intuitive or easy to use for the work they do. Electronic health records, also known as electronic medical records (EMRs), are a prime example.

"Right now, you have techies designing the systems. EMR is the system of record for the data, and aggregating all that information. But every clinician has to go there and, I mean, the experience sucks. Getting data out (is) really, really hard," Kass-Hout said.

Bringing clinicians into the fold as systems are designed is also key, especially since 42% of those surveyed said they are actively looking to leave the industry.

The departures are a result of significant burnout from the pandemic and a general shift in overall job satisfaction. AI implementation could push many workers, especially older ones, over the edge.

But, he pointed out, there are already many areas where AI is being used successfully, including medical imaging and collecting and analyzing health data.

Kass-Hout noted that radiologists, for example, can spend several hours dissecting layers and angles of images in order to help target the exact location of cancer. AI could cut the search down to 15-20 minutes.

"You can imagine now, that time will go back to the radiologists. So we're really....working on heavy lifts and problems that we are solving in this clinical workflow," he said.