Course Overview
This 8-week course provides an in-depth look at ethical, legal, and governance challenges when deploying AI in healthcare. Participants learn to develop governance structures, navigate regulations like HIPAA and GDPR, mitigate bias, and uphold accountability in clinical AI systems.
Course Goals
Equip healthcare professionals, technologists, and policymakers with the expertise to lead ethical AI initiatives, ensuring AI solutions in healthcare are fair, transparent, compliant, and patient-centric.
Program Objectives
- Understand ethical challenges in AI healthcare applications.
- Identify and mitigate biases to ensure fairness.
- Navigate legal frameworks (HIPAA, GDPR) for AI systems.
- Design governance structures for AI deployment.
- Analyze real-world case studies to extract best practices.
Program Structure
Module 1: Introduction to AI Ethics and Governance
- Fundamentals of AI ethics
- Governance principles and their importance
- Ethical theories applied to healthcare AI
Module 2: Ethical Considerations in AI Deployment
- Bias identification and mitigation techniques
- Ensuring equity and fairness in AI outcomes
- Privacy and confidentiality in healthcare AI
Module 3: Legal Frameworks and Compliance
- HIPAA, GDPR, and other healthcare regulations
- Compliance strategies for AI technologies
- Data ownership and intellectual property in AI
Module 4: Governance of AI in Healthcare Organizations
- Developing governance frameworks
- Leadership roles in ethical AI implementation
- Stakeholder engagement and building trust
Module 5: Case Studies and Best Practices
- Analysis of real-world healthcare AI deployments
- Successful governance models
- Lessons learned from ethical failures
Module 6: Capstone Project
- Design an AI governance framework for a healthcare organization
- Address ethical, legal, and operational considerations
- Present and critique governance proposal
Participant Eligibility
Ideal for healthcare professionals, AI technologists, policymakers, ethics officers, and compliance managers aiming to guide responsible AI deployment in clinical settings.
Learning Outcomes
- Master ethical principles and governance strategies for healthcare AI.
- Apply legal and privacy frameworks to AI systems.
- Mitigate bias and ensure equity in AI decisions.
- Lead governance initiatives and stakeholder engagement.
- Develop and present robust AI governance frameworks.
