Protecting Informational Self-Determination in AI-driven Precision Oncology: Privacy, Ethics, and Governance...

Area of Science:

• Oncology
• Bioinformatics
• Medical Ethics

Background:

• Artificial intelligence (AI) is revolutionizing cancer care, impacting diagnosis, risk prediction, treatment planning, and drug discovery.
• The integration of genomic, imaging, and clinical data for AI in oncology raises significant privacy and ethical challenges.
• Patients express concerns regarding secondary data use, commercialization, and security breaches, despite supporting AI's clinical potential.

Purpose of the Study:

• To examine the emerging privacy and ethical challenges in AI-driven precision oncology.
• To explore strategies for safeguarding patients' informational self-determination in the context of AI data utilization.
• To analyze current regulatory frameworks and identify gaps in protecting sensitive health information.

Main Methods:

• Narrative ethical and policy analysis.
• Informed by recent empirical and technical research on AI and data privacy.
• Examination of existing regulatory frameworks like GDPR and HIPAA.

Main Results:

• De-identified data, including molecular and imaging profiles, can be vulnerable to re-identification and inference of sensitive attributes via machine learning.
• Current regulations primarily address explicit identifiers, failing to mitigate risks from AI's inferential analytics.
• Privacy violations can undermine patient autonomy, confidentiality, trust, and exacerbate health inequities.

Conclusions:

• Multilayered governance is essential to address AI-driven privacy risks in oncology.
• Strategies include privacy-preserving technologies, dynamic consent, data minimization, and transparency.
• Strengthened legal safeguards and robust governance are crucial for maintaining public trust in AI for cancer care.