With the demand for healthcare outpacing the workforce, healthcare organizations need help from AI tools and automation. At the same time, the deployment of AI technologies is rarely plug and play.
The list below aggregates the most common roadblocks and concerns many organizations have encountered, along with a few ideas on how to help work through — or around — them.
1. Lack of trust:
One promising initiative to improve trust in AI for healthcare organizations is the Coalition for Health AI (CHAI™). The coalition is a key leader in the drive to establish standards for the responsible use of AI in healthcare and a valuable source of guidance for healthcare systems of all sizes
2. Concerns about accuracy:
Whether you're using AI to provide information, generate content, make recommendations or take action of some kind, human oversight and continuous monitoring should be in place to ensure accurate responses and continued trust among stakeholders.
3. Staff training:
Just like reading the instruction manual for a new car before operating it, teams expected to use AI should be trained on proper usage. Policies and guidelines to govern AI's use should be created after gathering input from stakeholders across the organization.
4. Protection of intellectual property:
In general, content created by AI tools should be seen as providing helpful first drafts to be reviewed and modified by the user. This also helps avoid replicating anyone's existing work.
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