New Fellowship Develops Human-Centred Leaders in AI for Health
March 29, 2023
Artificial intelligence promises to have a huge impact on Canadian health care — and faculty at the University of Toronto’s Dalla Lana School of Public Health are working now to train leaders who can realize its benefits.
In partnership with AMS Healthcare, DLSPH has launched The AMS-Fitzgerald Fellowship in AI and Human-Centred Leadership – the first of its kind in Canada – to help emerging health systems leaders enhance their capacity to implement human-centred uses of AI into healthcare. The fellowship will create a community of practice to support its graduates as they instill AI in their organizations.
“Right now people are sorting out how AI is going to change health care,” says Prof. Jennifer Gibson, director of the DLSPH’s Joint Centre for Bioethics (JCB), who is leading the development of the fellowship along with a group of DLSPH faculty. “We have a major opportunity to think through the vision we are going to apply to this technology. It’s now or never.”
The Fellowship aims to equip leaders to implement human-centred approaches to AI in health care. This involves a holistic focus on people and communities and a commitment to promoting compassion and equity in an age of AI. For the fellowship, ‘human-centred’ means training systems leaders to navigate complexities with a strong degree of moral confidence — and an innovation mindset to ensure the technology is improving human health.
AMS Healthcare focuses on bringing compassion into modern, technology-driven care and already supports innovation and education in bioethics for AI at the School. Its CEO, Helen Angus, recognizes this as a pivotal moment to incorporate AI into health systems.
“This is an exciting time in health care, and we need to train leaders to have the knowledge, skills, and judgement to implement the new capabilities that AI brings to the healthcare system,” says Angus. “As we embed technology into the healthcare team, leaders will face a new series of challenges, and we want to ensure they are fully equipped to handle the transformation.”
Says Gibson: “The fellowship grew out of a longstanding partnership between JCB and AMS,. They aren’t just funders. They’re partners, and together we are turning our attention to leadership in AI.”
Use of AI has grown consistently in the healthcare community over the past few years. But the emergence of Large Language Models (i.e. next-generation chatbots) adds a level of complexity in innovation, creating new questions that need to be answered by those leading AI-based changes in health care.
The program is designed to be flexible for emerging leaders, who are working full-time in the health field in areas such as clinical leadership, policy development, and digital innovation.
The typical fellow might be responsible for digital health implementation at a hospital, or they may lead a laboratory focussing on the development of AI applications. The fellowship would be well suited to a clinician-leader contemplating the use of AI with the population they serve, or an executive interested in developing policies around AI use. All fellows will be highly promising health systems leaders who will carry human-centered AI innovation forward in health care.
Each cohort will meet for two or three full days at a time, then return to their workplaces and continue to engage with readings and discussions online. The curriculum for the fellowship will focus on four aspects of optimizing AI in the healthcare environment: human factors, ethics and governance, technical acumen in selecting and deploying AI, and embedding innovation in organizations.
Inevitably, participants will guide each other on practical aspects of integrating AI into their health systems as they learn from faculty.
“Human-centred AI relies as much on people as technology,” says Angus. “The AMS-Fitzgerald Fellowship will build a community of leaders that is essential for the healthcare system of today and tomorrow.”
Taken from the Dalla Lana School of Public Health March 29, 2023