Home / Executive and Continuing Education / Responsible AI for Health Care: Concepts and Applications / Responsible AI for Health Care: Concepts and Applications

Responsible AI for Health Care: Concepts and Applications

“I went in with close to zero knowledge regarding AI in health care and finished the course with a plethora of knowledge I hope to apply in my realm of practice. The future is here.”
—Deep Palikhel, Physician Assistant at Baylor Scott & White Hospital

Download Brochure

About the Program

February 2 – 10, 2026

This program aims to unveil the core principles of responsible AI, the capabilities of Large Language Models and Generative AI, and their profound implications for healthcare, emphasizing ethical considerations and safety measures.

Online

Artificial Intelligence and Technology

AI in Health Care Certificate of Specialization

Program Fees

Standard Price $2,600.00

Program Overview

AI is Transforming Industries—Understand its Role in Healthcare’s Future

Large Language Models (LLMs), machine learning, and other forms of artificial intelligence (AI) are reshaping how healthcare is delivered, managed, and regulated. But with this promise comes complexity and risk. Responsible AI for Health Care: Concepts and Applications is a four-day, intensive live online program that equips healthcare professionals with the knowledge and tools to critically assess, implement, and govern AI technologies in clinical, operational, and public health settings.

Led by renowned Harvard faculty and AI ethics experts, this 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.

More About the Program & Curriculum

Upcoming Program Details

Define foundational AI concepts and differentiate types of AI tools relevant to clinical, operational, and population health use cases
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

All Times are Eastern Time (ET).

Monday, February 2, 2026
9:00–10:00 am	Panch	Introduction to AI I
10:00–10:15 am		Break
10:15–11:15 am	Panch	Introduction to AI II
11:15–11:30 am		Break
11:30 am–12:30 pm	Panch, Mattie, Mauro	Interactive Session
12:30–1:00 pm		Office Hours (Q&A)
Tuesday, February 3, 2026
9:00–10:00 am	Campbell	Safety and Regulation I
10:00–10:15 am		Break
10:15–11:15 am	Campbell	Safety and Regulation II
11:15–11:30 am		Break
11:30 am–12:30 pm	Panch, Mattie, Mauro	Interactive Session
12:30–1:00 pm		Office Hours (Q&A)
Monday, February 9, 2026
9:00–10:00 am	Mattie	Algorithmic Bias
10:00–10:15 am		Break
10:15–11:15 am	Panch, Mattie	Interactive Session
11:15–11:30 am		Break
11:30 am–12:30 pm		Implementing Responsible AI
12:30–1:00 pm		Office Hours (Q&A)
Tuesday, February 10, 2026
9:00–10:00 am		AI Governance in Clinical/Healthcare
10:00–10:15 am		Break
10:15–11:15 am	Romero-Brufau	Implementing AI in Healthcare Organizations
11:15–11:30 am		Break
11:30 am–12:30 pm	Panch, Mattie, Mauro	Interactive Session and Closing
12:30–1:00 pm		Office Hours (Q&A)

This agenda is subject to change.

Trishan Panch, MD, MPH

Instructor, Harvard Chan School

Heather Mattie, PhD, SM, MS

Lecturer on Biostatistics, Co-Director, Health Data Science Master’s Program, Director of EDIB Programs | Harvard Chan School

Current faculty, subject to change

Ray Campbell

President
FAIR Health

Heather Mattie

Lecturer on Biostatistics, Co-Director, Health Data Science Master’s Program, Director of EDIB Programs
Department of Biostatistics
Harvard T.H. Chan School of Public Health

Gianluca Mauro

CEO
AI Academy

Trishan Panch

Instructor
Harvard T.H. Chan School of Public Health

Santiago Romero-Brufau

Director of AI and Systems Engineering
Department of Otolaryngology — Head and Neck Surgery
Mayo Clinic

Adjunct Assistant Professor
Department of Biostatistics
Harvard T.H. Chan School of Public Health

In the video below, you can hear directly from course faculty on how AI is reshaping health care operations and patient care. This discussion offers a preview of the key concepts and case studies you’ll explore more deeply in this program.

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.

Participants will come from a range of organizational functions including health care delivery, health care technology, primary care systems, payers, and governments. Some titles represented in the program will include:

Chief Executive Officer
Chief Information Officer
Chief Innovation Officer
Chief Medical Informatics Officer
Chief Medical Officer
Clinician
Data Scientist
Director
Engineer
Innovation Specialist
Finance Professional
Product Manager
Project Manager
Venture Capital Investor

Frequently Asked Questions

Responsible AI for Health Care: Concepts and Applications is a live online program from Harvard T.H. Chan School of Public Health Executive and Continuing Education designed for healthcare professionals who want to understand and apply artificial intelligence responsibly in their organizations.

Over four days, you will explore AI fundamentals, ethical frameworks, regulatory guidance, and real-world case studies to evaluate and implement AI solutions in clinical, operational, and public health settings. The course emphasizes interactive discussion and applied learning so participants can immediately apply insights to their organizations.

This online program is designed for senior managers, clinicians, and executives from sectors such as healthcare delivery, healthcare technology, primary care systems, payers, and governments. Healthcare professionals across the U.S. and internationally have found the program immensely valuable.

This program is right for you if you are responsible for decisions around innovation, data, or technology in healthcare organizations, or want to be responsible for such decisions.

You will gain practical tools to:

Understand foundational AI concepts tailored to healthcare settings
Implement responsible AI strategies in clinical and public health contexts
Identify and reduce algorithmic bias
Apply ethical and regulatory frameworks
Evaluate AI risks, transparency, and compliance

The full agenda is available here.

No. The program is accessible to professionals from clinical, policy, and administrative roles. The focus is on ethical implementation, decision-making, and leadership, tailored to healthcare and public health settings—not programming.

Becoming an AI leader in healthcare requires a blend of ethical, technical, and strategic skills. You can build this expertise by gaining a solid understanding of artificial intelligence and studying frameworks for fairness, governance, and regulatory compliance. Programs like Harvard T.H. Chan School of Public Health’s Responsible AI for Health Care program can help you move from awareness to leadership—equipping you with the confidence and knowledge to guide AI strategy, oversight, and innovation across health systems.

While on-the-job experience with AI is very valuable, it often lacks the structured frameworks, ethical grounding, and cross-sector perspectives needed to lead AI responsibly in healthcare. The Responsible AI for Health Care program from Harvard T.H. Chan School of Public Health Executive Education offers structured learning guided by Harvard faculty and enriched by peers from diverse disciplines. Through interactive discussions and real-world case studies, you’ll explore what has worked (and what hasn’t) in different organizations. This shared learning helps you return to your own workplace with proven strategies, practical insights, and a stronger foundation for responsible AI implementation.

You’ll learn from Harvard faculty, healthcare leaders, and industry experts, including:

Program Director: Trishan Panch – CEO, LUNRStudio; Executive Chair and Chief Strategy Officer, Lumin Health; Co-founder, Wellframe

Program Director: Heather Mattie – Lecturer on Biostatistics, Co-Director of the Health Data Science Master’s Program, Director of EDIB Programs at Harvard Chan School

Ray Campbell – President, FAIR Health

Gianluca Mauro – CEO, AI Academy

Santiago Romero-Brufau – Director of AI and Systems Engineering, Department of Otolaryngology — Head and Neck Surgery, Mayo Clinic

Note: This list may not include all faculty and is subject to change.

This course is part of the Harvard T. H. Chan School of Public Health’s Executive Education AI in Health Care Certificate of Specialization. Completing this and two other AI courses (Innovation with AI in Health Care and Implementing Health Care AI in Clinical Practice) earns the certificate, showing advanced skills in healthcare AI leadership.

All individual Harvard Chan Executive Education programs also award a Certificate of Participation upon completion.

Note: If you have previously completed a healthcare AI course at Harvard Chan School, or enroll in Responsible AI for Healthcare in February 2026, you will be eligible to earn the Certificate of Specialization with 2 courses, per the prior criteria.

Yes, we offer customized programs for organizations that can be adapted from open-enrollment courses like Responsible AI for Health Care or designed as a new, bespoke program.

Teams of 4–20: We can offer a discounted cohort of an existing open enrollment program to accommodate your group.

Teams of 21+ : We recommend a fully customized design—either a modified version of an existing course or a new program built around your goals.

We’d be happy to have an informal conversation about how we can help you to customize your organizational training needs. Please contact Priya Ponnappan for more information at Priya_ponnappan@hsph.harvard.edu

Credits & Logistics

Harvard T.H. Chan School of Public Health will grant 1.2 Continuing Education Units (CEUs) for this program, equivalent to 12 contact hours of education. Participants can apply these contact hours toward other professional education accrediting organizations.

All credits subject to final agenda.

All participants will receive a Certificate of Participation upon completion of the program.

This program also contributes to the AI in Health Care Certificate of Specialization. Click here for more information.

This image has an empty alt attribute; its file name is HPH-GPH-certificate-23-08-24-3-1024x791.webp

Advance Your Career at Harvard with Responsible AI for Health Care: Concepts and Applications