Attendees

No prior experience or legal training is required. The 2022 Summer Institute is for people interested in learning more about the legal ramifications of AI in health and healthcare. Students come from diverse professional backgrounds, but our program is designed to be most useful to professionals with a health background. Please note class size is limited, and we encourage you to apply promptly.

Format

The program runs full-time over five days and encompasses 20 hours of seminars and workshops and 10 hours of group discussion. You’ll join live lectures with breakout discussions, participate in Q&A, and have direct access to some of the leading experts in the field. You can expect interactive seminars designed to facilitate peer learning, interaction, as well as opportunities to network with fellow students. The sessions will be held through Zoom, supplemented with the Teachable platform.

Cost

The cost of the Institute is $1,500 (CAD), payable upon admission. Students completing the course will receive a Certificate in Health Law – Artificial Intelligence from the University of Ottawa Centre for Health Law, Policy and Ethics. A limited number of partial bursaries may be available to student applicants who show financial need.

FAQ

Who is the Institute for?

The Institute is for people interested in learning more about the legal ramifications of AI in health and healthcare. Selected participants will include both students and professionals. Please note the Institute may not be a good fit for you if you have already completed legal studies. If uncertain, don’t hesitate to contact us at healthlaw@uottawa.ca.

What do I need?

All sessions will be held through Zoom. As such, you will need a device with a microphone, camera, and internet connection. For system requirements for Zoom, please see here. The sessions will also be recorded and made available exclusively to you for 12 months on Teachable, which has similar requirements.

Do I need to attend the sessions in real time?

You do not. However, we strongly recommend that you do. We are purposely holding live sessions and keeping our cohort small to allow for rich direct interaction between instructors and students. So, while the sessions will be recorded and available to you asynchronously, you should attempt to attend them live.

What is the language of instruction?

All sessions will be in English.

Will I get University credits for participating in the Institute?

Upon completion of the Institute, you will receive a Certificate in Health Law – Artificial Intelligence from the University of Ottawa Centre for Health Law, Policy and Ethics (CHLPE). While CHLPE is an official Centre within the University, it is unable to grant University of Ottawa course credits directly. That said, if you are a student at the University of Ottawa, it may be possible to get credits with the completion of additional requirements (for example, a paper). This may also involve additional fees payable to the University of Ottawa. This is at the discretion of the University. Please don’t hesitate to contact us at healthlaw@uottawa.ca for more information.

Will there by opportunities outside the Institute?

In addition to its training aspect, we intend the Summer Institute to create and connect a community of people interested in health law, policy and ethics. We will provide opportunities to stay active and involved within this community after the Institute ends. As one example, we organize occasional evening sessions with leading experts and public health officials that are exclusive to Institute alumni.

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Sessions

Fundamentals of Health Law

Monday am

Professor Flood will set the stage with an introductory overview of some fundamental principles and rules of Canadian law and health systems and their relevance for AI governance. This introductory information will help you understand aspects of Canadian health law, its major players, and its implications for health-related AI. As part of her session, Professor Flood will also outline some international legal materials and comparisons with U.S. law to introduce the transnational regulatory context and options.

Fundamentals of Health Law

Monday am

Professor Flood will set the stage with an introductory overview of some fundamental principles and rules of Canadian law and health systems and their relevance for AI governance. This introductory information will help you understand aspects of Canadian health law, its major players, and its implications for health-related AI. As part of her session, Professor Flood will also outline some international legal materials and comparisons with U.S. law to introduce the transnational regulatory context and options.

Colleen Flood

Colleen M. Flood is Professor at the University of Ottawa and a University Research Chair in Health Law & Policy. She is also inaugural Director of the University of Ottawa Centre for Health Law, Policy and Ethics. From 2000–2015 she was a Professor and Canada Research Chair at the Faculty of Law, University of Toronto, with cross-appointments to the School of Public Policy and the Institute of Health Policy, Management and Evaluation. From 2006–2011 she served as Scientific Director at the Canadian Institute for Health Services and Policy Research (CIHR).


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CHLPE member picture

Human Rights and Health AI

Monday pm

In this afternoon session, Professor Okechukwu will speak on human rights and bias in artificial intelligence. He will discuss how algorithms can become biased, how they enter into systems, and the harmful effects of algorithmic bias for health care. Taking a human rights globalist approach, he will explore the legal and regulatory responses to bias in AI for health purposes.

Human Rights and Health AI

Monday pm

In this afternoon session, Professor Okechukwu will speak on human rights and bias in artificial intelligence. He will discuss how algorithms can become biased, how they enter into systems, and the harmful effects of algorithmic bias for health care. Taking a human rights globalist approach, he will explore the legal and regulatory responses to bias in AI for health purposes.

Jake Okechukwu Effoduh

Jake Okechukwu Effoduh is a Vanier Scholar and Ph.D. candidate at Osgoode Hall Law School, York University. He has been an international human rights Lawyer for 12 years. He holds two master’s degrees in law, one from the University of Oxford in the UK, and from York University.


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Bioethics and AI

Tuesday am

On the second day, Professor Cohen will lead a discussion on the ethics of building and implementing predictive analytics in healthcare. He will cover issues surrounding data acquisition, model building and validation, testing models in real world settings, and broad dissemination of technology.

Bioethics and AI

Tuesday am

On the second day, Professor Cohen will lead a discussion on the ethics of building and implementing predictive analytics in healthcare. He will cover issues surrounding data acquisition, model building and validation, testing models in real world settings, and broad dissemination of technology.

I. Glenn Cohen

Professor Cohen is a Deputy Dean and the James A. Attwood and Leslie Williams Professor of Law at Harvard Law School and the Faculty Director of the Petrie-Flom Center for Health Law Policy, Biotechnology & Bioethics. He is one of the world's leading experts at the intersection of bioethics and the law as well as health law. He is the author of more than 200 articles and book chapters and the author, co-author, editor, or co-editor of more than 18 books. His current projects relate to big data, medical AI, health information technologies, mobile health, reproduction/reproductive technology, research ethics, organ transplantation, rationing in law and medicine, health policy, FDA law, COVID-19, translational medicine, and medical tourism.

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CHLPE member picture

Privacy and Health AI

Tuesday pm

The Tuesday afternoon session will focus on privacy. AI algorithms often require access to large quantities of patient data and these data may need to be used in ways that were not contemplated nor agreed upon at the time of acquisition. Privacy laws have not kept up with new developments in health-related AI. In this session, Prof. Scassa will consider the state of existing laws in Canada. She will also explore reforms to privacy laws as well as the development of data governance regimes at the provincial and the federal levels to ensure the public is adequately protected from issues such as data breaches, reidentification and cyber attacks.

Privacy and Health AI

Tuesday pm

The Tuesday afternoon session will focus on privacy. AI algorithms often require access to large quantities of patient data and these data may need to be used in ways that were not contemplated nor agreed upon at the time of acquisition. Privacy laws have not kept up with new developments in health-related AI. In this session, Prof. Scassa will consider the state of existing laws in Canada. She will also explore reforms to privacy laws as well as the development of data governance regimes at the provincial and the federal levels to ensure the public is adequately protected from issues such as data breaches, reidentification and cyber attacks.

Teresa Scassa

Dr. Teresa Scassa is the Canada Research Chair in Information Law and Policy at the University of Ottawa Faculty of Law. She is a member of the Centre for Law, Technology and Society at the University of Ottawa, where she is part of the Scotiabank AI & Society Initiative. Teresa has served on a number national and provincial advisory panels on law- and technology-related issues. She has written widely in the area of privacy law, data governance, intellectual property law, law and technology, artificial intelligence, and smart cities. She is a co-editor of the books AI and the Law in Canada (2021), Law and the Sharing Economy (2017), and The Future of Open Data (2022). She is co-author of Digital Commerce in Canada (2020) and Canadian Intellectual Property Law (2013, 2018 and 2022).

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Health Canada Approach to AI and ML

Wednesday am

Health Canada is facing a host of challenges in its efforts to regulate AI tools as it attempts to strike the right balance between fostering innovation that will improve clinical outcomes and healthcare quality without sacrificing public safety. In this session, Professor Da Silva will look at the rules for AI-enabled tools in Canada and map out its efforts to develop new frameworks for pre-market authorization and post-market regulation.

Health Canada Approach to AI and ML

Wednesday am

Health Canada is facing a host of challenges in its efforts to regulate AI tools as it attempts to strike the right balance between fostering innovation that will improve clinical outcomes and healthcare quality without sacrificing public safety. In this session, Professor Da Silva will look at the rules for AI-enabled tools in Canada and map out its efforts to develop new frameworks for pre-market authorization and post-market regulation.

Michael Da Silva

Dr. Michael Da Silva is Permanent Lecturer (Assistant Professor) at the University of Southampton School of Law. He is a member of the New York bar. Dr. Da Silva was previously the Alex Trebek / CIHR Postdoctoral Fellow in AI and Health Care in the University of Ottawa Faculty of Law. His work at the University of Ottawa included collaborations on the Machine M.D. project. He also previously served as a CIHR Banting Postdoctoral Fellow in the McGill University Faculty of Law and Institute for Health and Social Policy. He remains affiliated with Ottawa’s Centre for Health Law, Policy and Ethics and Centre for Law, Technology, and Society. He is widely published in law, philosophy, and bioethics and recently served on a Health Canada External Reference Group on the development of regulatory requirements for adaptive machine learning-enabled medical devices.

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FDA approach to AI and ML

Wednesday pm

In this focused session, Professor Cortez will map out the current U.S. pre-market pathway for AI tools, as well as the U.S. Food and Drug Administration's (FDA) attempt to build a total product lifecycle-based regulatory framework for these technologies. The proposed framework would allow for device modifications while ensuring that the safety of the software and its effectiveness as a medical device are maintained.

FDA approach to AI and ML

Wednesday pm

In this focused session, Professor Cortez will map out the current U.S. pre-market pathway for AI tools, as well as the U.S. Food and Drug Administration's (FDA) attempt to build a total product lifecycle-based regulatory framework for these technologies. The proposed framework would allow for device modifications while ensuring that the safety of the software and its effectiveness as a medical device are maintained.

Nathan Cortez

Professor Cortez is the Callejo Endowed Chair of Law, a Gerald J. Ford Fellow, and a former Research Dean at the SMU Dedman School of Law in Dallas, Texas. He teaches and writes in the areas of health law, administrative law, and FDA law. His research focuses on emerging phenomena in health care and biotechnology, focusing on big data analytics, AI and machine learning, and other novel technologies in medicine. His work has appeared in leading medical and law journals, and has been a part of grant-funded projects in the United States and Canada. Prior to becoming a law professor, he practiced in the Health Care and Food and Drug groups at Arnold & Porter in Washington D.C.

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Liability and Health AI

Thursday am

In her session, Professor Khoury will address the uncertainty regarding the potential liability of using AI technology in healthcare. Who might be held liable for a mistaken diagnosis made while using AI as a tool for medical decisions? Can a hospital or physician be held liable for an omission to use AI as a tool for medical decisions? While liability may vary depending on the context in which the AI tool is used, malpractice claims may arise from making medical decisions with or from the omission of making medical decisions with such technology.

Liability and Health AI

Thursday am

In her session, Professor Khoury will address the uncertainty regarding the potential liability of using AI technology in healthcare. Who might be held liable for a mistaken diagnosis made while using AI as a tool for medical decisions? Can a hospital or physician be held liable for an omission to use AI as a tool for medical decisions? While liability may vary depending on the context in which the AI tool is used, malpractice claims may arise from making medical decisions with or from the omission of making medical decisions with such technology.

Lara Khoury

Professor Khoury is an Associate Professor at the McGill University Faculty of Law. She is also a member of McGill’s Institute of Comparative Law and a full member of the Paul-André Crépeau Centre for Private and Comparative Law. She leads, with Professor Alana Klein, the McGill Research Group on Health and Law. She teaches and conducts research in the fields of comparative medical, public health and environmental law, with a particular focus on liability issues.

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Development and Commercialization of Health AI

Thursday pm

This session will share best practices and insights about topics such as data use, integration with third parties, life cycle considerations and post-implementation activities. We will also cover topics such as product development and commercialization basics, typical contractual terms, licensing and ownership, and use rights.

Development and Commercialization of Health AI

Thursday pm

This session will share best practices and insights about topics such as data use, integration with third parties, life cycle considerations and post-implementation activities. We will also cover topics such as product development and commercialization basics, typical contractual terms, licensing and ownership, and use rights.

Ty Kayam

Ty Kayam is an attorney for health and life sciences and retail health businesses at Microsoft. She focuses on technology and commercial transactions and routinely advises on regulatory and policy matters related to digital health, AI, and other emerging health technology issues. Ty previously worked as counsel at a health information network and started her career in the health care practice group of a D.C. law firm. Ty has a Master’s in Public Health from Tufts University and received her law degree from Northeastern University School of Law.

Cameron Schuler

Cameron Schuler is the Chief Commercialization Officer & Vice President, Industry Innovation at the Vector Institute. He is the former Executive Director of Amii, where for eight years he led one of the top-ranked Machine Learning and AI groups in the world. Cameron’s career has covered finance, business and product development, consumer products, IT and general management from start-ups to mature companies. Roles have included COO, CFO, President and CEO. He has founded numerous start-up companies, including medical devices as well as computer software and hardware. Cameron has an MBA from Queen’s University.

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Health AI Case Studies

Friday am

Professors Goldenberg and Flood will workshop different health-related AI technologies such as the digital twin, surgical black-box supports, and a suicidal prediction app. Goldenberg is a leading AI innovator in the healthcare space and will explain the challenges that innovators face in developing health-related AI to work for patients. Flood will illuminate, in conversation with Goldenberg, whether our existing laws are up to the challenges posed (e.g. liability, privacy, informed consent, algorithmic bias).

Health AI Case Studies

Friday am

Professors Goldenberg and Flood will workshop different health-related AI technologies such as the digital twin, surgical black-box supports, and a suicidal prediction app. Goldenberg is a leading AI innovator in the healthcare space and will explain the challenges that innovators face in developing health-related AI to work for patients. Flood will illuminate, in conversation with Goldenberg, whether our existing laws are up to the challenges posed (e.g. liability, privacy, informed consent, algorithmic bias).

Anna Goldenberg

Dr. Anna Goldenberg is a Senior Scientist in Genetics and Genome Biology program at the SickKids Research Institute, and is also the first Varma Family Chair in Biomedical Informatics and Artificial Intelligence. She is an Associate Professor in the Department of Computer Science at the University of Toronto, faculty member and an Associate Research Director, Health at Vector Institute and a fellow at the Canadian Institute for Advanced Research (CIFAR), Child and Brain Development group. Goldenberg trained in machine learning at Carnegie Mellon University, with a postdoctoral focus in computational biology and medicine. The current focus of her lab is on developing machine learning methods that capture heterogeneity and identify disease mechanisms in complex human diseases, as well as developing risk prediction and early warning clinical systems.

Colleen Flood

Colleen M. Flood is Professor at the University of Ottawa and a University Research Chair in Health Law & Policy. She is also inaugural Director of the University of Ottawa Centre for Health Law, Policy and Ethics. From 2000–2015 she was a Professor and Canada Research Chair at the Faculty of Law, University of Toronto, with cross-appointments to the School of Public Policy and the Institute of Health Policy, Management and Evaluation. From 2006–2011 she served as Scientific Director at the Canadian Institute for Health Services and Policy Research (CIHR).

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Workshop on ML-Based Medical Directives to Expedite Care in Pediatric Emergency Medicine

Friday pm

In this workshop, Dr. Singh will present technology developed by his research group aimed at expediting care in pediatric emergencies using a machine learning system. With knowledge gained throughout the week's sessions, you will engage in dialogue and work through scenarios to explore the complexities surrounding the deployment of this technology in hospitals.

Workshop on ML-Based Medical Directives to Expedite Care in Pediatric Emergency Medicine

Friday pm

In this workshop, Dr. Singh will present technology developed by his research group aimed at expediting care in pediatric emergencies using a machine learning system. With knowledge gained throughout the week's sessions, you will engage in dialogue and work through scenarios to explore the complexities surrounding the deployment of this technology in hospitals.

Devin Singh

Dr. Devin Singh is a practicing Pediatric Emergency Medicine Doctor at SickKids (the Hospital for Sick Children) in Toronto, Canada. He is one of Canada's first physicians to specialize in clinical AI. He completed his undergraduate degree at the University of Western Ontario in medical sciences and went on to work for the Ontario Provincial Government. Afterward he attended medical school at the University of Sydney, Australia, followed by a pediatric residency and emergency medicine subspecialty training at SickKids Hospital. His fellowship in clinical AI was completed at SickKids. He also has graduate training in Computer Science from the University of Toronto, Canada.

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