One of the fundamental principles of ethical AI is transparency – in other words, being able to see how and why the AI has come to its conclusions. Healthcare providers should make it a priority to understand how AI algorithms make decisions and predictions. AI systems should prioritise transparency,, enabling healthcare professionals to trust the recommendations provided.
5 Ways to Ensure AI in Medicine is Being Used Ethically
Apr 15, 2024 | 3 Min Read
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As artificial intelligence (AI) continues to revolutionise the industries around the world, its impact on healthcare is unprecedented.
AI has huge potential to enhance patient care, diagnostics, and hospital processes. However, the ethical implications of AI in medicine are a serious concern for patients and healthcare professional alike.
Ensuring that AI is used ethically is essential to great patient care - maintaining trust, protecting privacy, and upholding principles. If you’re a healthcare professional, or concerned about how AI might impact your healthcare in future, here are five key factors to keep in mind.
1. Transparency
2. Data privacy and security
Protecting patient data is crucial in healthcare, and this will extend to AI as it is used more in future. Ensuring that AI systems adhere to strict data privacy and security standards, including compliance with regulations such as GDPR and HIPAA, will be a priority for healthcare providers in the next few years. Healthcare IT teams should pay attention to robust encryption protocols, access controls, and data anonymization techniques to safeguard sensitive patient information.
3. Bias mitigation
Just like humans, AI algorithms are also susceptible to inherent biases. This is because the data used for training AI platforms is informed by humans, which can be reflected in biases in AI predictions. Biases in healthcare is already an established issue - one study found that Black patients were 40% less likely to receive pain medication in U.S. emergency departments as compared to white patients.
To ensure fairness and equity in healthcare, healthcare teams can mitigate biases by diversifying training data; regularly auditing algorithms for bias; and implementing bias detection and correction mechanisms.
4. Human oversight and intervention
AI is not a perfect system and requires oversight like any other process. While AI can augment decision-making in medicine, it's essential to have human teams oversee and intervene when any issues arise. Doctors and other staff still have ultimate responsibility for patient care and treatment decisions, and patients should always be aware of this. There should always be processes in place for human review and validation of AI-generated recommendations, allowing clinicians to exercise their judgment and intervene when necessary.
5. Continuous monitoring and evaluation
Ethical AI in medicine is an ongoing phenomenon, and requires continuous monitoring and evaluation to remain safe for the future. Healthcare teams should regularly assess the performance, accuracy and impact of AI systems on patient outcomes. It’s also important to get regular feedback from patients to identify areas for improvement.
Allianz – committed to global health
As AI continues to transform healthcare, it's imperative that we prioritise ethics and responsibility in its development and deployment. At Allianz Partners, we embrace forward-thinking medicine, and prioritise the protection of our customers’ well-being. Check out our options for personal and business international health insurance.
