Course Overview
This 8-week course offers an in-depth examination of the ethical, legal, and governance issues surrounding the use of artificial intelligence in healthcare. It is designed to equip healthcare professionals, policymakers, and technologists with the knowledge and skills needed to ensure that AI technologies are developed, deployed, and governed ethically and responsibly within healthcare settings.
Course Goals
The course aims to empower participants with the expertise to ensure the ethical and responsible deployment of AI in healthcare. By offering a comprehensive understanding of AI ethics and governance, the course prepares healthcare professionals, policymakers, and technologists to lead in the creation and implementation of ethical AI practices.
Program Objectives
- Understand Ethical Challenges: Grasp the ethical challenges in AI healthcare applications.
- Address Biases and Ensure Fairness: Learn how to identify and mitigate biases in AI algorithms to ensure fairness and equity.
- Navigate Legal Frameworks: Understand and comply with legal regulations such as HIPAA and GDPR.
- Design Governance Structures: Develop effective governance frameworks for AI deployment in healthcare organizations.
- Analyze Real-World Cases: Study and extract best practices from real-world examples of AI in healthcare.
- Develop Governance Frameworks: Create and present AI governance frameworks tailored for healthcare settings.
Program Structure
- MODULE 1: Introduction to AI Ethics and Governance
- Fundamentals of ethics in AI
- The importance of governance in AI applications
- Overview of ethical theories and principles applicable to AI in healthcare
- MODULE 2: Ethical Considerations in AI Deployment
- Identifying and addressing biases in AI algorithms
- Ensuring fairness and equity in AI outcomes
- Privacy and confidentiality issues in AI applications
- MODULE 3: Legal Frameworks and Compliance
- Overview of legal frameworks governing AI in healthcare (HIPAA, GDPR, etc.)
- Compliance challenges and strategies for AI technologies
- Intellectual property rights and data ownership issues in AI
- MODULE 4: Governance of AI in Healthcare Organizations
- Developing effective governance structures for AI use
- Role of leadership in ethical AI implementation
- Strategies for stakeholder engagement and public trust
- MODULE 5: Case Studies and Best Practices
- Examination of real-world cases of AI in healthcare
- Discussion of successful governance models
- Lessons learned and best practices in ethical AI deployment
- MODULE 6: Capstone Project
- Design an AI governance framework for a healthcare organization
- Address ethical, legal, and operational considerations
- Presentation and critique of the governance framework
Eligibility
- Graduates and Professionals: Ideal for those looking to pursue roles such as AI Ethics Officer, Healthcare Compliance Officer, AI Governance Specialist, and other positions focused on policy and regulation within the healthcare sector.
Learning Outcomes
- Ethical Understanding: Gain a deep understanding of the ethical principles and challenges associated with AI in healthcare.
- Legal and Compliance Knowledge: Learn about legal frameworks and compliance requirements affecting AI applications.
- Bias Mitigation Skills: Develop the ability to identify and mitigate biases in AI algorithms, ensuring fairness and equity.
- Governance Framework Design: Acquire the skills to design and implement governance frameworks for AI use in healthcare organizations.
- Leadership in Ethical AI: Be prepared to lead discussions and initiatives on ethical AI deployment, fostering trust and transparency in healthcare.