Deploying artificial intelligence within healthcare introduces critical ethical considerations, notably regarding patient data privacy, informed consent, algorithmic bias, and accountability for automated diagnostic decisions. Because health tech systems ingest massive quantities of sensitive patient records, maintaining rigorous cybersecurity safeguards and data anonymization protocols is paramount to prevent unauthorized breaches. Furthermore, developers must actively mitigate historical systemic biases embedded within medical training datasets to ensure that predictive risk algorithms deliver equitable diagnostic accuracy across diverse demographic populations, socioeconomic groups, and marginalized communities.