Principles

Data Ethics

Building AI for healthcare requires more than technical excellence—it demands unwavering commitment to patient privacy, clinical safety, and ethical data use.

Our Core Principles

Patient Privacy First

All patient data is de-identified, encrypted at rest and in transit, and processed under strict HIPAA compliance. We never train models on identifiable patient information or share data across organizations.

Clinical Safety by Design

Our AI systems are decision-support tools, not autonomous decision-makers. Every prediction surfaces to clinicians with transparent reasoning and appropriate uncertainty quantification.

Bias Monitoring & Mitigation

We actively monitor model performance across demographic groups and clinical contexts, continuously testing for and mitigating algorithmic bias that could lead to disparities in care.

Human Oversight & Accountability

Clinical experts review model outputs, validate recommendations, and maintain ultimate decision authority. AI augments clinical judgment—it never replaces it.

Transparency & Explainability

Clinicians understand why AI makes specific recommendations. We provide feature importance, confidence intervals, and clear reasoning for all predictions.

Data Minimization

We collect and process only the minimum data necessary for clinical value. Retention policies ensure data is purged when no longer needed for product function or regulatory compliance.

Governance & Oversight

Our internal Data Ethics Review Board evaluates all new AI features, model updates, and data practices. The board includes clinical advisors, data scientists, legal counsel, and patient advocates.

We conduct quarterly audits of model performance, bias metrics, and data handling practices. Results are reviewed by executive leadership and inform product roadmaps.

Patient Rights

Patients have the right to:

  • •Understand how their de-identified data is used to improve care quality
  • •Request deletion of their data from our systems (subject to regulatory retention requirements)
  • •Know when AI tools are used in their care decisions
  • •Access transparent explanations of AI-generated recommendations affecting their treatment

Research & Academic Collaboration

We partner with academic medical centers and research institutions to advance healthcare AI responsibly. All research collaborations:

  • •Require IRB approval and informed consent where applicable
  • •Use de-identified or synthetic data wherever possible
  • •Include data use agreements with strict privacy protections
  • •Publish findings in peer-reviewed journals to contribute to scientific knowledge

Questions or Concerns?

We welcome questions about our data practices, ethical frameworks, and governance processes.

Contact Privacy Team