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Is the AI medical revolution at risk? Find out the shocking truth revealed by GE Healthcare report.

Is the AI medical revolution at risk? Find out the shocking truth revealed by GE Healthcare report.


GE Healthcare Survey Finds Distrust and Skepticism Around AI in Medical Settings

A recent survey conducted by GE Healthcare has revealed that while the majority of clinicians agree that AI has the potential to transform healthcare, they express concern over the technology’s readiness and the biases that may be present. This report comes at a time when several healthcare giants are experimenting with AI models to improve patient experiences and outcomes, automate tasks, and increase productivity in the industry.

AI is Here But Concerns Remain

Around the world, AI has been touted as a significant force for driving change and disrupting the healthcare industry. According to the survey, clinicians aren’t alone in believing that AI can help with decision-making, enable faster intervention, and improve operational efficiencies. The study revealed that 61% of clinicians believe that AI can help with decision-making, 54% think that it can enable faster health interventions, and 55% believe that it can improve operational efficiencies. However, despite these claims, 55% of all survey participants stated that AI technology is currently unfit for medical use, with many highlighting the issue of data trust, particularly among clinicians with more than 16 years of experience, 67% of which feel anxious about AI implementation.

Concerns about AI in the Medical Setting

One of the significant concerns expressed by respondents is the potential for AI to produce unfairly discriminatory outcomes. This can be attributed to several factors, such as flawed algorithms, incomplete training data, or inadequate evaluation processes. Up to 44% of respondents stated that AI was subject to built-in biases. Additionally, the study found that only 55% of clinicians surveyed feel that they are provided with enough training on how to use medical technology effectively.

How to Build Confidence?

To build confidence among clinicians, GE Healthcare CTO Taha Kass-Hout emphasizes the importance of a data-driven, thoughtful approach where companies can ensure data quality, transparency, and address concerns around bias. He recommends training programs that orient clinicians about AI technology and its applications in healthcare, and suggests that breaking the black box of AI will help clinicians gain a better understanding of AI models’ data inputs, which can lead to an improvement in trust levels.

Massive Potential

As healthcare systems around the world experience intense pressure, clinicians burn out and consider leaving the industry. The WHO predicts that by 2030, there could be a shortage of 10 million health workers, with 1.4 billion people being 60 or over at that time. This is where AI-driven systems could help eliminate repetitive low-level tasks so that healthcare workers could focus on patient care primarily. Kass-Hout points to GE HealthCare’s Command Center as an excellent example of an AI-driven platform that helps hospitals use real-time data to allocate resources better and help reduce clinician burnout. Another example is Hyro, which uses conversational AI assistants to automate tasks like patient registration, routing, scheduling, IT helpdesk ticketing, and prescription refills.


In conclusion, while it may be true that AI technology has the potential to revolutionize healthcare, distrust and skepticism persist among respondents. However, with adequate training, data quality, and transparency being key factors in building trust, the healthcare industry can unlock the benefits of AI and reduce the burden on clinicians.


What did the GE Healthcare survey reveal?

The survey revealed that the majority of clinicians believe that AI technology can transform healthcare by improving decision-making, enabling faster intervention, and improving operational efficiencies. However, concerns remain about the technology’s readiness, data trust, and built-in biases.

Why do clinicians express concern over AI technology?

Clinicians express concern over AI technology because of concerns such as built-in biases, flawed algorithms, incomplete training data, or inadequate evaluation processes. Additionally, lack of training on how to use medical technology effectively is yet another concern.

How to build confidence in AI technology?

To build confidence in AI technology, a data-driven, thoughtful approach that involves adequate training for clinicians on AI technology, addressing concerns around bias, and ensuring data quality and transparency is essential.


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