To secure AI deployment in healthcare, consider these key strategies. First, implement a private instance of AI tools, allowing clinicians to experiment without exposing sensitive data. Utilize big cloud providers’ privacy agreements, which ensure prompt data won’t be used for model retraining. Second, establish a robust action plan for potential data breaches, detailing necessary responses and frameworks for addressing new attack surfaces. Third, start AI implementation gradually; focus on specific problems, and avoid sharing extensive data with AI models. It’s crucial to use organization accounts, rather than personal emails, to prevent unauthorized data sharing. Additionally, create an oversight team to vet AI tools, ensuring transparency in AI usage across the organization. Lastly, conduct a complete risk assessment and audit to identify compliance risks, which forms the foundation of effective AI governance in healthcare. Prioritize trust and privacy for successful AI adoption in the industry.
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