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
About the Program
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 health care, emphasizing ethical considerations and safety measures.
Program Fees
- Standard Price $2,600.00
Program Overview
AI is reshaping industries, with Large Language Models and Generative AI poised to revolutionize health care. Responsible AI for Health Care: Concepts and Applications introduces these technologies’ core principles, emphasizing responsible AI use, ethical considerations, and safety measures under the tutelage of distinguished Harvard faculty. It transitions health care professionals from traditional to data-driven AI-augmented practices using a “zero-to-AI” strategy, providing foundational concepts tailored for health care applications.
Participants will engage in a dynamic learning experience through group discussions, active learning, case studies, and master classes that explore AI’s origins and implementation challenges. The course examines viable business models for AI in health care and forecasts future developments over the next five years. It also fosters a networking environment for collaboration among participants, serving as a lasting resource beyond the program.
Upcoming Program Details
- Understand the first principles of AI ethics and safety in health care
Grasp the core ethical principles and safety measures essential for AI in health care. - Discuss how large language models can and have been applied ethically in health care
Explore real-world applications of LLMs in health care, emphasizing ethical use cases, patient privacy, and mitigation of biases. - Understand prompt engineering, tuning, and optimizing large language models with ethical considerations
Learn techniques for improving the performance of AI through effective prompt engineering and model tuning. - Describe the process of implementing AI projects in large health care organizations
Outline the steps for integrating AI into health care settings, focusing on ethical deployment, stakeholder engagement, and compliance with regulatory frameworks. - Identify future challenges and opportunities in AI with a focus on ethics and safety
Anticipate emerging issues and potential advancements in AI, with a focus on ensuring ethical practices and addressing societal impacts.
All Times are Eastern Time (ET).
| Tuesday, February 4, 2025 | ||
|---|---|---|
| 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 | Interactive Session |
| 12:30–1:00 pm | Office Hours (Q&A) | Wednesday, February 5, 2025 |
| 9:00–10:00 am | Romero-Brufau | Implementing AI in Healthcare Organizations |
| 10:00–10:15 am | Break | |
| 10:15–11:15 am | Mattie | Algorithmic Bias and Data Ethics |
| 11:15–11:30 am | Break | |
| 11:30 am–12:30 pm | Mauro | Interactive Session |
| 12:30–1:00 pm | Office Hours (Q&A) | Thursday, February 6, 2025 |
| 9:00–10:00 am | Safety and Regulation I | |
| 10:00–10:15 am | Break | |
| 10:15–11:15 am | Safety and Regulation II | |
| 11:15–11:30 am | Break | |
| 11:30 am–12:30 pm | Mauro | Interactive Session |
| 12:30–1:00 pm | Office Hours (Q&A) | Friday, February 7, 2025 |
| 9:00–10:00 am | Lindemer | Evaluating and Scaling AI in Healthcare |
| 10:00–10:15 am | Break | |
| 10:15–11:15 am | Brownstein | AI and Intrapreneurship |
| 11:15–11:30 am | Break | |
| 11:30 am–12:30 pm | Mauro | Interactive Session and Closing |
| 12:30–1:00 pm | Office Hours (Q&A) |
This agenda is subject to change.
Current faculty, subject to change
John Brownstein
Chief Innovation Officer
Adebona Account
Professor of Pediatrics
Harvard Medical School
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
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
Credits & Logistics
All participants will receive a Certificate of Participation upon completion of the program.
This program also contributes to the Business Applications for AI in Health Care Certificate of Specialization. Click here for more information.
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.