Responsible AI Track
Following the successful first edition of the Responsible AI event in 2022, we are excited that the event will be held again in 2023. We strongly believe in the importance and urgency of the Responsible and Ethical Development of Artificial Intelligence for the Social Good.
As outlined by the UNESCO Recommendation on the Ethics of Artificial Intelligence, AI technology may have unintended by-products that lead to discrimination, reinforce inequalities, infringe upon human rights, socially sort and disrupt democratic processes, limit access to services and intensify surveillance and unfair treatment of marginalized and minority groups. As such, we are committed to organizing a cohesive and dynamic program that embodies the paradigm of responsible development of AI so that AI researchers and practitioners can engage in critical analysis and integration of fairness, ethics, transparency, and algorithmic accountability in their work.
This year's program will consist of the following events and will be open to all participants of the Canadian AI conference:
- Six Invited Talks of 30 minutes each. The talks will consist of speakers with practical and theoretical expertise at the intersection of various domains and Responsible AI
- A keynote speaker by an international leader in Responsible AI
- A half-day hands-on tutorial that offers useful practical introductory training on the use of fairness-aware AI tools
The track will take place in the Strathcona Anatomy and Dentistry building.
Thursday: Room 2/36
Friday: Room M/1
Emily Denton Keynote Address
Emily Denton (they/them) is a Staff Research Scientist at Google, within the Technology, AI, Society, and Culture team, where they study the sociocultural impacts of AI technologies and conditions of AI development. Their recent research centers on emerging text- and image-based generative AI, with a focus on data considerations and representational harms. Prior to joining Google, Emily received their PhD in Computer Science from the Courant Institute of Mathematical Sciences at New York University, where they focused on unsupervised learning and generative modeling of images and video. Prior to that, they received their B.S. in Computer Science and Cognitive Science at the University of Toronto. Though trained formally as a computer scientist, Emily draws ideas and methods from multiple disciplines and is drawn towards highly interdisciplinary collaborations, in order to examine AI systems from a sociotechnical perspective. They've published in multiple top-tier venues spanning social science and computing disciplines, including Big Data & Society, CSCW, FAccT, and NeurIPS.
Student Posters Presentation
Allison Marchildon talk
AI developers and companies seem increasingly open to talking about ethics and adopting ethical principles. But their discourses on the matter also face growing criticism, as they don't always translate into actual responsible practices. And when they do, it is questionable the extent to which these practices correspond to what the actors impacted by them consider responsible.
The challenge then becomes fostering practices that are aligned with the values that are important not only for those who develop AI systems, but also - and above all – for the actors likely to be affected by these systems. In this talk, I will therefore discuss some of the mechanisms that we are working on to help develop AI systems that lead to consequences and responsibilities that are valued by the actors who will most probably be impacted by them. Inspired by a pragmatist approach to ethics, these mechanisms are reflexive, collaborative and solutions-oriented, in order to develop new practices and responsibilities that are adapted to the new issues raised by AI.
Allison Marchildon is full professor and Applied Ethics programs lead in the Department of Philosophy and Applied Ethics at Université de Sherbrooke. She is also co-leader of the Ethics, Governance and Democracy theme of the International Observatory on the Societal Impacts of Artificial Intelligence and Digital Technology (OBVIA) and sits on the steering committee of the journal Éthique publique. Her research focuses on ethics, governance, responsibility and power in different fields of activities, including artificial intelligence and new technologies. She is currently advising the Quebec Department of Cybersecurity and Digital Technology in developing an ethical framework for public sector use of AI. Her publications include the books Quels lendemains pour la responsabilité? Perspectives multidisciplinaires (2018), co-edited with André Duhamel; Former à l’éthique en organisation : une approche pragmatiste (2017), co-authored with André Lacroix and Luc Bégin; and Corporate responsibility or corporate power? CSR and the shaping of the definitions and solutions to our public problems (2016), published in the Journal of Political Power.
Natalie Mayerhofer talk
Natalie Mayerhofer is Deputy Chief Learning Officer at the CHUM. During her international career, she has developed expertise in innovation policy, program evaluation, and strategic planning. She thrives on innovative projects, including her greatest challenge, the development of CHUM’s School of Artificial Intelligence in Healthcare.
Nathalie de Marcellis-Warin talk
Deliberative governance and social acceptability are important for promoting responsible innovation in the field of artificial intelligence. Given the rapid advancements and potential impacts of AI, involving citizens and stakeholders in decision-making processes and promoting transparency and accountability in AI development are critical.
Promoting transparency and accountability requires questioning the governmentality of AI systems not only at the technical level but also in their organizational and societal deployment. Moreover, there is an emerging consensus that AI is a global challenge that must be addressed for the public good.
Ensuring that AI technologies are widely accepted by society and addressing concerns related to the ethical and societal implications of AI are also important for promoting responsible innovation and implementing deliberative governance.
This conference aims to address responsible AI innovation from the perspective of deliberative governance in relation to social acceptability in society.
Nathalie de Marcellis-Warin is President and Chief executive officer of CIRANO. She is a full professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal and a Visiting Scientist at the Harvard T. Chan School of Public Health. In addition, she is a member of the Commission de l'éthique en science et en technologie (CEST) du Québec and a research fellow at the International Observatory for Societal Impacts of AI and Digital Transformations (OBVIA). Holder of a PhD in Management Science (in risks and insurance management) from École Normale Supérieure de Cachan (France), her research interests are risk management and decision-making theory in different contexts of risk and uncertainty as well as public policies implementation. She collaborates on major research projects with public and private organizations on the issues of emerging technology adoption and societal impacts.
Samira Abbasgholizadeh-Rahimi talk
Professor Samira A.Rahimi is Assistant Professor in the Department of Family Medicine, Associate Academic Professor of Mila-Quebec AI Institute, Associate member of Faculty of Dentistry, and an Affiliated scientist at Lady Davis Institute for Medical Research of Jewish General Hospital. She is an Associate Member of the College of Family Physicians of Canada, Vice President of the Canadian Operational Research Society (CORS), and Director of Artificial Intelligence in Family Medicine (AIFM). Professor Rahimi is Fonds de Recherche du Québec-Santé (FRQS) Junior 1 Research Scholar in human-centered AI in primary health care, and her work as Principal Investigator has been funded by the Fonds de recherche du Québec – Santé (FRQS), Natural Sciences and Engineering Research Council (NSERC), Roche Canada, Brocher Foundation (Switzerland), and the Strategy for Patient-Oriented Research (SPOR)-Canadian Institutes of Health Research (CIHR). In recognition of her outstanding work, Professor Rahimi has received numerous awards, including the prestigious 2022 New Investigator Primary Care Research Award from the North American Primary Care Research Group (NAPCRG).
Three Minute Thesis Event
Benjamin Fung talk
Dr. Benjamin Fung is a Canada Research Chair in Data Mining for Cybersecurity, a Full Professor of School of Information Studies (SIS) at McGill University, and an Associate Editor of IEEE Transactions on Data and Engineering (TKDE) and Elsevier Sustainable Cities and Society (SCS). He received a Ph.D. degree in computing science from Simon Fraser University in 2007. Collaborating closely with the national defense, law enforcement, transportation, and healthcare sectors, he has published over 140 refereed articles that span across the research forums of data mining, machine learning, privacy protection, and cybersecurity with over 14,000 citations. His data mining works in crime investigation and authorship analysis have been reported by media, including New York Times, BBC, CBC, etc. Dr. Fung is a licensed professional engineer in software engineering. See his research website http://dmas.lab.mcgill.ca/fung for more information.
Jacob Jaremko talk
Jacob Jaremko is a Professor of Radiology and Adjunct Professor of Computing Science at the University of Alberta, a practicing board-certified Pediatric and Musculoskeletal radiologist and partner at Medical Imaging Consultants, and co-founder of 2 startup companies including MEDO.ai. He has a PhD in Biomedical Engineering. He is a Canada CIFAR AI Chair and Fellow of the Alberta Machine Intelligence Institute. His research has focused on developing objective imaging biomarkers of disease in ultrasound and MRI, and on implementing AI-augmented medical imaging diagnostic tools at the clinical point of care &emdash; building the 21st-century stethoscope.
Responsible AI Panel
Panelists: Valentine Goddard, Alexander Scott, Gagan Gill, Sasha Luccioni, Allison Cohen, Richard Khoury
Moderator: Marina Sokolova
Valentine Goddard is a member of the Advisory Council on AI of Canada and a United Nations expert in AI Policy and Governance. Lawyer, certified mediator and curator, Ms. Goddard is the founder and executive director of AI Impact Alliance, an independent non-profit organization whose mission is to facilitate a responsible implementation of AI, and accelerate the achievement of the 17 UN’s Sustainable Development Goals. AI Impact Alliance is a founding organizational member of the International Observatory on the Ethical and Social Impact of AI (OBVIA) and of the Responsible AI Consortium. She is the lead architect of the AI on a Social Mission Conference, a respected international conference on the ethical and social implications of AI, and the Art Impact AI programs which position the arts’ critical role in the future of AI and democracy. Ms. Goddard provides expertise on emerging regulatory frameworks on AI and Data, and on the anticipatory foresight of their socioeconomic implications. She delivers programs that bridge civic engagement and knowledge mobilization with policy innovation. With collaborators from a global network, she delivers thought-provoking programming on the design and the governance of AI Systems (power dynamics, systemic change, political economy, geopolitics, human security, etc). She leads international working groups on critical issues such as gender equality in digital economies and the environment, and supports organizations in their adoption of AI with a focus on the social and regulatory implications.
Alexander Scott is the Director of Group Risk Management at Borealis AI, where he is responsible for the delivery of AI projects across the risk portfolio at RBC. Prior to joining Borealis, Alex led data science teams at TD Bank and a number of management consulting firms. He has supported analytics transformations at banks and public sector institutions across North America. Alex has a Masters in Management Analytics from the Smith School of Business at Queen’s University.
Gagan Gill leads the AI & Society portfolio at CIFAR, a globally renowned research organization dedicated to driving breakthroughs in science and technology. In this role, Gagan oversees programs and initiatives focused on exploring the impact of artificial intelligence on society and responsible AI adoption. Gagan is passionate about ensuring that the development and deployment of AI is done in a responsible, ethical, and equitable way that benefits all members of society. Prior to joining CIFAR, Gagan held a number of positions in program and policy development and knowledge mobilization. Gagan holds an MSc in Neurophysiology, with a secondary field of study in Neuroscience from the University of Guelph.
Dr. Sasha Luccioni is a Research Scientist and Climate Lead at HuggingFace, a Board Member of Women in Machine Learning (WiML), and a founding member of Climate Change AI (CCAI). Over the last decade, her work has paved the way to a better understanding of the societal and environmental impacts of AI technologies.
Allison Cohen is the Senior Applied AI Projects Lead at Mila, the world's largest deep learning research center. In this role, Allison works closely with AI researchers, social science experts and external partners to professionalize and deploy socially beneficial AI projects. Her portfolio of work includes: a misogyny detection and correction tool; an application that can identify online activity that is suspected of containing human trafficking victims; and an agricultural analytics tool to support sustainable practices among smallholder farmers in Rwanda. She was on InspiredMinds! Top 50 Influential Women in AI list and was the Runner Up for the 2022 Women in AI "Leader of the Year" Award in the category of Equity, Diversity and Inclusion. She holds an MA in Global Affairs from the University of Toronto and a BA in International Development from McGill University.
Richard Khoury received his Bachelor’s Degree and his Master’s Degree in Electrical and Computer Engineering from Laval University (Québec City, QC) in 2002 and 2004 respectively, and his Doctorate in Electrical and Computer Engineering from the University of Waterloo (Waterloo, ON) in 2007. From 2008 to 2016, he worked as a faculty member in the Department of Software Engineering at Lakehead University. In 2016, he moved to Université Laval as an associate professor. Since 2021, he’s also serving as president of the Canadian Artificial Intelligence Association. Dr. Khoury’s primary areas of research are data mining and natural language processing, and additional interests include knowledge management, machine learning, and artificial intelligence.
Marina Sokolova works in Text Data Mining and Machine Learning. Her research focuses on Ethical AI: studies of personal health information, fairness in ML applications, privacy protection. Her work on performance evaluation of ML classifiers, done with Guy Lapalme, received an international recognition. Dr. Sokolova is an active CAIAC member and Canadian AI contributor since 2004. In 2020, Marina Sokolova has been bestowed with Distinguished Service Award from CAIAC. Marina Sokolova received M.Sc. in Systems Science and Ph.D. in Computer Science from University of Ottawa. She is a member of Institute for Big Data Analytics at Dalhousie University and Adjunct Professor with Faculty of Medicine and Faculty pf Engineering, University of Ottawa.
Specifically, we will explore an intuitive privacy definition based on hypothesis tests, and see that it helps understand the theoretical guarantees offered by Differential Privacy, as well as the practical attacks it can defend against. We will see how to use this understanding to perform privacy audits of ML models, and if time permits how it can be extended to enforce fairness in ML predictions or defend against adversarial examples.
Mathias Lécuyer is an assistant professor at the University of British Columbia in Vancouver. Prior to this, he was a PhD student at Columbia University with Roxana Geambasu, Augustin Chaintreau, and Daniel Hsu, and a postdoctoral researcher at Microsoft Research in New York. He is broadly interested in machine learning systems, with a specific focus on applications that provide rigorous guarantees of robustness, privacy, and security. His research focuses both on improving practical and theoretical ML tools (differential privacy, causal inference, reinforcement learning) and enabling specific use-cases and applications for them (ML attacks/defenses, privacy preserving data management, system decisions optimization).
Responsible AI Co-chairs
Electrical, Computer, and Biomedical Engineering, Ryerson University
Canada Research Chair in Privacy-preserving and Ethical Analysis of Big Data
Université du Québec à Montréal (UQAM)
Professor, Department of Computing Science
Acting Vice Dean, Faculty of Science
Director, AI4Society Signature Area
University of Alberta