Recap of Changing the Face of Health Care through Artificial Intelligence: Emerging Ethical and Legal Debates

On February 3rd 2018, the McGill Journal of Law and Health held its 10th annual colloquium entitled Changing the Face of Health Care through Artificial Intelligence: Emerging Ethical and Legal Debates. This year’s edition was particularly topical considering Montreal’s growing presence on the international artificial intelligence (AI) scene. A variety of lawyers, physicians, computer scientists, as well as law and medical students attended the event. The event’s program included two expert panel discussions: one meant to give an overview of the development of artificial intelligence technologies, and one meant to provide an idea of the road towards a regulatory framework on artificial intelligence, particularly in the field of the right to health in Canada.

Panel 1: An Overview of the Development of Artificial Intelligence Technologies

Contributed by Catherine Labasi-Sammartino

The first panel was composed of Dr. Jonathan Kanevsky, a final year resident in Plastic and Reconstructive Surgery at McGill who has developed several medical devices to improve therapy for skin cancer and scaring; Christelle Papineau, a PhD candidate in the international thesis program established between Paris University Panthéon-Sorbonne and the University of Montreal who’s research focuses on the interactions between law and artificial intelligence with a comparative perspective between Europe and North America; and Me. Antoine Guilman, a current lawyer at Fasken and member of the national group of Information and privacy protection who holds a PhD in Information Technology law from the University of Montreal and the Paris University Panthéon-Sorbonne.

Image1 Panel 1 speakers, from left to right: Dr. Jonathan Kanevsky, Christelle Papineau, and Me. Antoine Guilman 

Dr. Kanevsky started the panel off with a discussion on the potential of AI in health care, which he demonstrated by sharing examples of AI excelling in pattern recognition tasks, such as tumour detection in human biopsies. To create advancement in health care, it is important to recognize that some skills, such as pattern recognition, are not only human skills. This shift is similar to the one that took place when the recognition that the human mind could not possibly retain all the required information to treat patients put forward the idea that doctors should be using a data base to keep medical records. Dr. Kanevsky provided his audience with several insights about what AI can do in health care. These included classification (i.e., identify cancer types), prediction (i.e., make predictions based on physical appearance), and diagnosis (i.e., detect cancer cells).

Dr. Kanevsky also addressed the ethical challenges raised by the use of AI. Is AI good or bad? All three speakers jumped in to answer this question. Christelle Papineau brought up current studies on an algorithm’s potential (e.g., the Compass and LSI-R algorithm) to determine the appropriate sentence in criminal offence cases to illustrate AI’s potential role on our legal system and its associated risks. She stressed the value of human involvement in legal decision-making and the social responsibility AI innovators had to not delegate an irresponsible part of the cognitive processing required in legal settings to AI. Dr. Kanevsky echoed these concerns and left the audience with a rhetorical question regarding AI’s role in removing a scientist’s thought process.

Me. Guilman brought up issues surrounding the anonymization of personal information, such as doubts regarding its effectiveness and reliability. Furthermore, he explained the current trend of increasing the amount of data collected, without discriminating according to data type, and how it has created a series of challenges for the lawyers and business owners working according to the current Canadian laws on data protection. These laws are widely recognized as being out of touch with recent technological changes and have left the legal community with a variety of wide interpretations.

Overall, the first panel succeeded in bringing the audience to reflect on what AI to the legal and health care fields, while stressing the need for a continued responsible attitude towards its implementation. For all of the speakers, this responsibility translated itself in always having the possibility to include human interaction in when relying on AI decision-making. The importance of sensitising and sharing information with the general population regarding AI’s growing presence, in events such as the MJLH colloquium, were acknowledged as being effective tools to promote the responsible use of AI.

Panel 2: Road Towards a Regulatory Framework for Artificial Intelligence

Contributed by Handi Xu

Nicole Mardis is a Project Officer for the CIHR Institute of Health Services and Policy Research and a PhD Candidate at McGill University with specializations in medical sociology and industrial relations. Mardis began her talk by explaining that artificial intelligence signifies new patterns of human-computer interaction at the programming level that are expected to: expand the scope of activity that can be augmented by technology, accelerate algorithm development, and generate more independent machines. While traditional programming involves step by step problem-solving based on hard coded rules, AI consists of machines learning from data and examples, which puts less burden on programmers to embed all relevant context and meaning in the instructions that they write for computers.

While the productive potential of AI is still not fully understood, comparisons are often made to the Industrial Revolution. It is important to note that the mechanization and centralization of production that occurred during the Industrial Revolution gave rise to major productivity gains, but these gains were distributed in such a fashion that large segments of the population saw their material well-being and quality of life initially decrease.

Image2 Panel 2 speakers, from left to right: Christelle Papineau (moderator), Nicole Mardis, Dr. Frank Rudzicz, and Me. Marie Hirtle 

The Digital Revolution appears to be following a different pattern: information technology has diffused widely and costs have fallen, but productivity gains are hard to locate. Will the AI Revolution change this? What we do know is that more R&D is needed to make AI mainstream, and we should be particularly mindful of what data/examples are used to drive this activity. Health care providers (e.g., hospitals, clinics, and governments) now house very rich sources of population-based clinical and social data that could be used for AI. In partnership with these entities, research funders such as the Canadian Institutes of Health Research are investing in platforms and services to make this data available to university and hospital-based researchers. Yet, because AI cuts across many different fields of research and is driven in large part by industry, governments and other research funders will have to think more strategically about how public data assets are used to shape the trajectory of AI, as well as how they structure partnerships to maximize social and economic benefits for citizens.

Dr. Frank Rudzicz is a scientist at the Toronto Rehabilitation Institute (University Health Network), an assistant professor of Computer Science at the University of Toronto, co-founder and President of WinterLight Labs Inc., faculty member at the Vector Institute, and President of the international joint ACL/ISCA special interest group on Speech and Language Processing for Assistive Technologies. Dr. Rudzicz talked about the importance of using AI and software tools for medical diagnosis in the health care system in an ethical manner.

Current trends in AI research involve deep neural networks, big (interlinked) data, recurrent neural networks for temporal/dynamic data, reinforcement learning, active learning, telehealth and remote monitoring as well as causal/explainable models. Reinforcement learning consists of systems learning ‘online’ by taking imperfect observations, inferring the unseen state, then taking an action. This type of learning necessitates some exploration, where rewards and costs are usually supplied by humans. Active learning, which involves doctors using AI to determine a person’s disease, is efficient, but also risks putting doctors in a feedback loop and creating a blind reliance on AI. Neural networks learn to associate input features with output categories, but there is no abstract logic or interpretable reasoning to those associations; correlation is not causation, meaning that one usually cannot tell why or how a neural network made a decision, which is problematic when it comes to assigning responsibility.

Humans are notoriously bad with information: patients misread or miscommunicate their symptoms while doctors make diagnostic errors. A study by Bennett and Hauser (2013), which compared patient outcomes between doctors and sequential decision-making algorithms, concluded that AI technology was not only less costly, but also led to 50% better outcomes. Clinical doctors prescribe medication after informing patients of its benefits and side-effects. However, the AI doctor prescribes medication, partially, as an experiment, which allows it to directly and continuously learn from the outcomes, making it difficult to determine which set of ethics apply. Current regulatory frameworks will face ethical challenges, and will certainty need to adapt to the rise of AI, but most importantly, they need to continue to respect individual rights.

Marie Hirtle is a lawyer with a background in ethics and specialization in health issues ranging from community-based health and social services, to tertiary and quaternary care, biomedical research, and public health. She is currently Manager of the Centre for Applied Ethics at the McGill University Health Centre (MUHC), where she leads a team of professional ethicists who provide clinical, organizational, and research ethics services to the MUHC community. Using the example of the artificial pancreas, Face2Gene and Big Data, Me. Hirtle discussed regulatory issues raised by different applications of AI in health care settings. The artificial pancreas uses an insulin pump, a continuous glucose sensor, and a control algorithm to help patients with diabetes, but the dosing algorithm is self-learning, which is difficult to regulate. Face2Gene is an application which collects personal health information, such as photographs of faces of babies, to facilitate the detection of facial dysmorphic features and recognizable patterns of human malformations, while referencing comprehensive and up-to-date genetic information. It uses advanced technologies including computer vision, deep learning, and other AI algorithms to analyze patient symptoms, features, and genomic data. Face2Gene allows labs to interpret genetic information more accurately, thus helping clinicians diagnose rare diseases earlier on.

Me. Hirtle also discussed the legal issues associated with Big Data. Currently, Big Data is being collected, stored, used and disclosed, either when individuals consent or when the law explicitly allows it. Although obtaining individual consent is desirable, it can be impracticable. Individuals often click on “I agree” without reading the terms and conditions, therefore not knowing what they are consenting to. Furthermore, even though the law allows the use of non-identifiable data, the re-identification of these data is technically possible, which could potentially infringe on the right to privacy.

Overall, the second panel of the event drew the audience’s attention to the uncertain future of AI and the need to develop appropriate legal and regulatory frameworks to ensure that the benefits of AI can be harnessed while tempering the risks.

Changing the Face of Health Care through Artificial Intelligence: Emerging Ethical and Legal Debates

The McGill Journal of Law and Health is pleased to invite you to attend its 10th annual Colloquium: Changing the Face of Health Care through Artificial Intelligence: Emerging Ethical and Legal Debates. The aim of this bilingual and student-based initiative is to foster interdisciplinary dialogue on issues that lie at the intersection of health and law. It is our hope that such dialogue will have a positive influence on health and social policy-making in Canada.

La discussion sera divisée en deux tables rondes. La première table ronde donnera un aperçu du développement des technologies d’intelligence artificielle et discutera des défis éthiques que posent les nouvelles possibilités de soins de santé. La seconde portera plus particulièrement sur le chemin vers un cadre réglementaire de l’intelligence artificielle dans le domaine du droit de la santé au Canada.

*Un dîner et des collations seront servis*

This year’s event will feature some big names in the artificial intelligence field including: Christelle Papineau, Daniel Weinstock, Frank Rudzicz, Nicole Mardis, Antoine Guilmain, and Jonathan Kanevsky.

The event is wheelchair/stroller-accessible and the MJLH is happy to welcome all those with children! If you have any dietary restrictions, or any particular arrangements need to be made, please feel free to contact manager.mjlh@mail.mcgill.ca.

Please RSVP to the event HERE.
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Recap of Speaker Series 2017: Ethical and Legal Ramifications of Stem Cell Research

Posted by Handi Xu

Our first Speaker Series event of the 2017-2018 academic year consisted of a discussion on the ethical and legal ramifications of stem cell research. This event presented diverse perspectives on research involving the development, use, and destruction of human embryos, as well as its many potential benefits and its complexities and regulations.

Dr. Michel L. Tremblay, a leading researcher from McGill University’s Biochemistry Department, discussed the evolution of stem cell use and its current clinical applications. Notably, stem cells are capable of reproducing themselves and are also able to differentiate into other cell types. Since stem cells are difficult to isolate in humans, experiments involving embryo stem cells are usually performed using animals. These experiments aim to create stem cell mutations in order to understand normal gene function as well as their association to various human diseases such as cancer and obesity.

IMG_2747 Dr. Tremblay spoke about the current clinical applications of stem cells 

In 2006, Dr. Shinya Yamanaka, a Japanese stem cell researcher, discovered through the fusion of stem cells and tumor cells that some genes responsible for stem cell properties were dominant over other gene expressed in non-stem cells. Therefore, the fusion of these stem cells and cancer cells led the majority of the fused cells to be stem cell like.  He then discovered that only four dominant genes in stem cells were necessary to transform a normal cell into a stem cell (Induced Pluripotent Stem cells or IPS cells). He shared the 2012 Nobel Prize in Physiology and Medicine with Sir John B. Gurdon for showing that mature cells can be reprogrammed into pluripotent stem cells. This line of work proved that it was possible to use cells other than those from the embryo to generate stem cells, hence removing one of the major ethical issues of using human embryos to obtain stem cells. Nowadays, novel technologies of genetic engineering, such as CRISPR-Cas9-technology, allow the generation of specific manipulations of genomes in any human stem cell and in other cell types.

Dr. William Stanford, an influential stem cell researcher from the Ottawa Research Institute, detailed the history of stem cells discoveries. He further discussed the use of stem cells in clinical trials to treat a great number of diseases such as diabetes, blindness, and heart disease. They are also starting to be used in the development and assessment of new therapeutic drugs. However, the remarkable potential of stem cells to improve all spheres of biomedical research and treatment has spawn great competition due to the lucrative potential of these technologies. Since the cost and ethical regulations of stem research and therapies differ among many countries, other issues such as stem cell therapeutic “tourism”, fake treatments, and non-ethical research programs in non-clinically certified centres, have resulted in harm to patients in many countries lacking regulation. There is a continuous need for maintaining a legal framework for their applications as well as constant effort to inform the public on the advances and limitations of stem cells activities.

IMG_2749 Dr. Stanford spoke about ethical complications with stem cell therapies in countries lacking proper regulation 

Finally, Me. William Brock, a partner at Davies and a leukemia survivor that underwent bone marrow stem cell transplant, expressed his opinion on stem cell research from a patient’s perspective. Not only did his treatment allow him to realize how fragile and important life is, but it also led him to acknowledge the power of science.

IMG_2753 Me. Brock spoke about his personal experience receiving stem cell therapy 

Indeed, scientific progress has permitted the 100% mortality rate of leukemia fifty years ago to drop to 10% for children and 50% for adults today. Me. Brock also explained that ethics is differently defined for everyone; while one person might find stem cell research unethical, another person’s life or death could rely on stem cells. He believes that society cannot decide for a patient whether they should be allowed to receive a stem cell treatment or not.

Event: Ethical and Legal Ramifications of Stem Cell Research

We have provided a recording of the event below:


For our first Speaker Series event of the 2017-2018 academic year we are excited to present a stimulating discussion on the legal and ethical ramifications of stem cell research. This event will present diverse perspectives on research involving the development, use and destruction of human embryos, as well as its many potential benefits and its complexities and regulations.

Speakers include:

Dr. William Stanford, Ottawa Research Institute:
Dr. Stanford is a leading stem cell researcher focusing on understanding and manipulating human embryonic stem cells for development of novel therapeutics for many human diseases including cancer.

Me. William Brock:
A partner at Davies who is also a leukemia survivor that underwent stem cell treatment. Me. Brock will give us his legal and personal perspective on the technology.

Dr. Michel L. Tremblay:
Dr. Tremblay is a leading researcher in the Biochemistry Department at McGill University. Dr. Tremblay will discuss techniques for modifying stem cells using CRSPR-Technology in the lab as well as the current use of stem cells in the clinic. Dr. Tremblay will also discuss pertinent ethical issues such as who owns stem cells, stem cell “tourism”, and the future of stem cells including drug development, use of stem cells for tissue/organ replacement and stem cells versus robotics-cybog.

The event will take place at the Thompson House Restaurant (3650 Mc Tavish, Montreal) on November 1st 2017 from 4:45 PM until 6:00 PM. No tickets required. Please arrive 10 minutes in advance to secure a seat.