Healthcare is one of AI's most promising and most ethically fraught domains — where errors can cost lives.

Promising Applications

• Medical image analysis (radiology, pathology)
• Drug discovery acceleration
• Clinical decision support
• Patient risk stratification

Documented Risks

• Racial bias in pulse oximeters — less accurate on darker skin
• Sepsis prediction algorithms with high false alarm rates causing alert fatigue
• Models that perform well on training data but fail on different hospital systems

Key Principle

AI in healthcare must augment clinician judgment — not replace it — until evidence of superiority is overwhelming.

Reference:

FDA on AI medical devices

https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices