Beyond Individual Privacy: A Layered Diagnostic Model for Analyzing Genetic Data Governance

Area of Science:

• Genomics
• Bioethics
• Data Governance

Background:

• Human genetic data presents unique challenges due to its personal, familial, and strategic value.
• Existing privacy frameworks inadequately address the complexities of genetic data governance.
• Recent events, like the 23andMe bankruptcy, have amplified concerns regarding genetic data security and national security risks.

Purpose of the Study:

• To propose a comprehensive, three-layer diagnostic model for analyzing and managing genetic data governance.
• To integrate individual privacy, relational/group interests, and national strategic value into a cohesive framework.
• To provide a practical approach for navigating the complex governance landscape of human genetic information.

Main Methods:

• Development of a three-layer diagnostic model: individual, relational/group, and state/strategic.
• Comparative examination of genetic data governance in select jurisdictions.
• Critical review of existing scholarship on genetic data privacy and security.

Main Results:

• The proposed model categorizes genetic data governance into three distinct but interconnected layers.
• It highlights the inadequacy of individual-centric privacy models for comprehensive genetic data management.
• The framework provides a structured approach for diverse stakeholders.

Conclusions:

• A multi-layered governance model is essential for effectively managing human genetic data.
• Integrating individual, relational, and state perspectives is crucial for addressing privacy and security concerns.
• This framework offers a practical pathway for researchers, policymakers, and industry stakeholders.