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Overview
Led by renowned Harvard University faculty and AI ethics experts, this Responsible AI for Health Care - Concepts and Applications program focuses on ethical principles, regulatory frameworks, fairness, transparency, and implementation science. Participants will examine real-world case studies—both successes and failures—to explore how to apply responsible AI in high-stakes environments while avoiding unintended harms.
Through interactive lectures, group discussion, and applied learning, participants will engage with timely questions at the intersection of innovation, safety, and health equity. The program also fosters a strong peer network, designed to support continued learning and collaboration well beyond the course.
Program Highlights
- Led by Harvard faculty with deep expertise in AI, ethics, regulation, and healthcare implementation
- Explore real-world case studies of both successful and flawed AI implementations
- Engage with ethical and regulatory frameworks shaping AI in healthcare globally
- Gain tools to evaluate and monitor AI systems, including bias detection, transparency practices, and risk assessments
- Participate in interactive learning through group discussion, applied exercises, and optional Q&A
- Develop strategies for responsible AI implementation aligned with clinical, regulatory, and organizational realities
- Join a global network of healthcare professionals committed to safe, equitable, and effective AI
Programme Structure
What you will learn:- Identify sources of algorithmic bias stemming from data, design, or deployment, and evaluate their impact on health equity
- Apply leading ethical frameworks to assess fairness, transparency, accountability, and safety in healthcare AI
- Compare and contrast U.S. and global regulatory approaches to healthcare AI, and assess implications for compliance and innovation
- Evaluate the trade-offs between explainability and model complexity, and explain the role of transparency in building trust in clinical AI
- Assess post-deployment risks and accountability mechanisms, including model drift, adverse event reporting, and human oversight
- Analyze real-world AI successes and failures to identify lessons learned and implementation challenges
- Develop strategies for responsible AI implementation aligned with ethical standards, clinical workflows, and organizational readiness
Key information
Duration
- Part-time
- 9 days
Start dates & application deadlines
- StartingApply anytime.
Language
English
Delivered
Online
Campus Location
- Cambridge, United States
Disciplines
Public Health Artificial Intelligence View 125 other Short Courses in Artificial Intelligence in United StatesWhat students do after studying Computer Science & IT
This information is based on LinkedIn alumni data for graduates from 2018 to 2024 and may not fully represent all career outcomes
Total alumni
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
- This online program is designed for senior managers and executives who are responsible for developing and implementing AI strategy in their organizations and are looking to understand AI, its current state of the art, and future.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
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International Applies to you
Applies to youNon-residents2600 USD / full≈ 2600 USD / full - Out-of-State2600 USD / full≈ 2600 USD / full
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Domestic
Applies to youIn-State2600 USD / full≈ 2600 USD / full
Funding
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