Ethicara for Responsible AI in Healthcare: A System for Bias Detection and AI Risk Management.

Area of Science:

• Health Informatics
• Artificial Intelligence
• Biotechnology

Background:

• Health AI innovations promise patient-centered care but face adoption challenges due to risks and health equity concerns.
• Current health AI development lacks robust risk controls, hindering responsible implementation.

Purpose of the Study:

• To introduce Ethicara, a system for health AI risk assessment.
• To enable responsible AI model development by detecting and mitigating bias and increasing transparency.
• To operationalize risk management frameworks and comply with emerging AI regulations.

Main Methods:

• Ethicara orchestrates self-analytics services for bias detection and mitigation.
• It utilizes harmonized data models to enhance model transparency.
• The system integrates analytics results into healthcare applications via plug-ins.

Main Results:

• Ethicara provides repeatable and measurable controls for AI risk management.
• It facilitates the operationalization of voluntary risk management frameworks (e.g., NIST RMF, FDA GMLP).
• The system supports compliance with upcoming AI regulations (e.g., EU AI Act, US Blueprint for an AI Bill of Rights).

Conclusions:

• Ethicara enhances responsible AI use in healthcare and life sciences.
• It offers a framework for managing AI risks, ensuring fairness and transparency.
• The system demonstrates practical AI risk controls for industry applications.