The more the use of AI in healthcare and healthcare research becomes mainstream, the more the risks associated with AI-powered analysis evolve — and the greater the potential for breakdowns in consumer trust. The mature practices for incorporating AI technologies are essential, like using an LLM for a fact check or a point of exploration rather than relying on it to deliver an answer to complex care questions.
Here are three top considerations for leaders and researchers in protecting patient privacy, compliance and, ultimately, consumer trust as AI innovation accelerates:
1.Start with consumer trust in mind.
2.Establish a data governance committee for AI innovation.
3.Mitigate the risks associated with re-identification of sensitive patient information.
By addressing the risks associated with AI-powered data analysis, healthcare clinicians and researchers can more effectively leverage the data available to them — and secure consumer trust.
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