Ethical Considerations in AI-driven Cancer Research

Developing AI models for cancer research introduces important ethical considerations:

• Bias in Data Representation: Ensuring diverse representation in the dataset is essential to prevent AI models from inheriting biases that could impact underrepresented groups.
• Transparency and Explainability: AI models should be transparent and interpretable, allowing clinicians to understand the basis of AI-driven recommendations.
• Informed Consent: Patients’ consent for the use of their medical images in research must be clearly defined, especially when sharing data across institutions.
• Accountability in Decision-Making: AI models used in clinical settings must have clear accountability guidelines to manage potential errors and adverse outcomes.
• Equitable Access to AI Innovations: The benefits of AI-driven advancements should be accessible across various healthcare settings, including those with limited resources.