Co-creating Consent for Data Use - AI-Powered Ethics for Biomedical AI.

Area of Science:

• Biomedical AI
• Regulatory Science
• Bioethics

Background:

• Nations are developing regulatory frameworks for medical AI, facing challenges in oversight due to AI's complexity and rapid innovation.
• Existing regulatory institutions may be overwhelmed by the scale and pace of AI development, potentially eroding public trust.
• Protecting privacy while ensuring access to large, inclusive data is critical for safe, effective, and equitable medical AI.

Purpose of the Study:

• To explore the challenges of regulating medical AI, focusing on privacy protection and data access.
• To examine the limitations of traditional informed consent in large-scale data environments.
• To advocate for the development of AI-powered oversight mechanisms and evolved privacy standards.

Main Methods:

• Literature review and analysis of current regulatory challenges in medical AI.
• Exploration of the concept of informed consent in the context of big data and AI.
• Conceptualization of AI-driven solutions for regulatory and ethical oversight.

Main Results:

• Traditional informed consent models are insufficient for modern large-scale data use in medical AI.
• AI applications in biomedicine pose significant challenges to human regulators.
• There is an urgent need for AI-powered tools to assist human regulators and ethicists.

Conclusions:

• Informed consent must evolve to ensure privacy, equity, and trust in medical AI.
• AI-driven oversight processes are necessary to support human regulators and ethicists.
• Investment in AI tools for AI oversight is critical to prevent regulators from falling behind.
• Public engagement in co-creating privacy standards is essential for data contribution.