The idea behind AI labs – where enormous language models and other AI technologies can be simulated and tested – is that they can improve the effectiveness and fairness of predictive analytics, disease detection, decision support and other healthcare AI tools.
The role of AI Assurance labs in frameworks such as the Health IT Certification Authority announced by US Health and Human Services to establish the AI Trust and AI Healthcare transparency has been a government and industry focus for the coming year.
Several groups and federal agencies are working to operationalize artificial intelligence to ensure patient safety and reliability under the executive order for the protected, secure and trustworthy development and operate of artificial intelligence – now canceled President Donald Trump – including the AI Healthcare Coalition. Some lawmakers raised concerns about Chai, but Federal Health AI Leads said their work with the group was complete and they left Chai’s roles in July.
In this week’s HIMSSSCast, Brigham Hyde, CEO of Atropos Health and member of the Generative AI Work Group, said the lack of standards for AI testing and evaluation could prevent providers from implementing advanced disease and risk models. He explained why he believes partnerships to assess the quality of machine learning algorithms from the outset are very vital, what the benefits are and where AI Healthcare innovation is heading.
“I think the onus should be on companies like mine and others, is to show what the expected performance and benefit is,” he said.
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Talking points:
- Why developing standards is so vital.
- The role AI Assurance labs play in providing health equity.
- How ML platform implementation providers can benefit from AI Assurance processes.
- Taste innovation and how it can benefit larger companies.
- Controlling Agency Workflows and Healthcare AI Trajectories in 2025
- Balancing the costs of testing data quality and model portability.
More about this episode:
Chai launches open source Healthcare AI Nutrition Label Card
Republicans want changes from HHS to AI Assurance Labs
Explainer: thinking through the protected operate of artificial intelligence
MITER, UMASS LOATH Health Ai Assurance Lab
Looking ahead to emerging AI regulations and more
Can government and industry solve racial bias in artificial intelligence?