This article proposes a multi-layered governance model for health data in AI applications, suggesting accountability and transparency are vital in addressing algorithmic bias.
Key Points
To explore the need for updated health data governance frameworks in light of advancements in machine learning and artificial intelligence.
Identified key governance issues related to health data utilization.
Explored the limitations of current HIPAA regulations.
Proposed a multi-layered governance model based on key principles.
Highlighted challenges such as algorithmic bias and dynamic consent.
Emphasized the importance of data provenance and transparency.
Suggested incorporating accountability and co-regulation in health data governance.