The use of AI in healthcare is governed by several ethical principles, which are often derived from bioethics. Here are the key principles:

1. Autonomy: This principle respects the decision-making capacities of autonomous persons, and it requires that individuals should be allowed to make their own decisions regarding their healthcare. In the context of AI, this means that patients should have the ability to make informed decisions about the use of AI technologies in their care.

2. Beneficence: This principle refers to the act of 'doing good', to improve the health and wellbeing of others. AI technologies should be designed and used in ways that improve patient outcomes and the quality of care.

3. Non-Maleficence: This principle means 'do no harm'. AI should not harm patients or healthcare providers, and should not compromise patient safety.

4. Justice: This principle refers to the fair distribution of benefits, risks, costs and resources. The use of AI in healthcare should not lead to inequalities or unfair outcomes.

5. Privacy and Confidentiality: AI systems should respect and protect patient privacy and confidentiality.

6. Transparency and Explainability: AI systems should be transparent in their operations and decisions, and healthcare providers should be able to explain AI decisions to patients.

These principles are not exhaustive and may vary depending on the specific context and jurisdiction. It's also important to note that these principles often need to be balanced against each other, as they can sometimes conflict.

Question

The use of AI in healthcare is governed by several ethical principles, which are often derived from bioethics. Here are the key principles:

1. Autonomy: This principle respects the decision-making capacities of autonomous persons, and it requires that individuals should be allowed to make their own decisions regarding their healthcare. In the context of AI, this means that patients should have the ability to make informed decisions about the use of AI technologies in their care.

2. Beneficence: This principle refers to the act of 'doing good', to improve the health and wellbeing of others. AI technologies should be designed and used in ways that improve patient outcomes and the quality of care.

3. Non-Maleficence: This principle means 'do no harm'. AI should not harm patients or healthcare providers, and should not compromise patient safety.

4. Justice: This principle refers to the fair distribution of benefits, risks, costs and resources. The use of AI in healthcare should not lead to inequalities or unfair outcomes.

5. Privacy and Confidentiality: AI systems should respect and protect patient privacy and confidentiality.

6. Transparency and Explainability: AI systems should be transparent in their operations and decisions, and healthcare providers should be able to explain AI decisions to patients.

These principles are not exhaustive and may vary depending on the specific context and jurisdiction. It's also important to note that these principles often need to be balanced against each other, as they can sometimes conflict.

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