R3Al: Shifting Paradigms for a Robust, Reasoning and Responsible Artificial Intelligence and its Adoption
To advance Canadian priorities, the R3AI program led by IVADO Labs, Université de Montréal’s artificial intelligence (AI) research and transfer institute, will develop and apply much-needed novel AI that is robust, reasoning and responsible.
Why? AI is predicted to have major and increasing impacts on our social systems, environment and economies. However, two major obstacles prevent Canada and other countries from maximizing its positive impacts, calling for a paradigm shift. The first hurdle is that current AI is insufficiently robust when deployed in uncertain “out-of-distribution” settings. The second issue is the misalignment between the deployment and adoption of AI and the ethical, organizational, social, cultural and legal factors that frame the way it should be implemented.
How? With the academic and institutional support of Université de Montréal, HEC Montréal, Polytechnique Montréal, Université Laval and McGill University, R3AI will bring world-leading multidisciplinary researchers and implementation experts to tackle these challenges. The first issue will be addressed by fostering collaboration among AI and cognitive neuroscience experts to better understand and narrow the gap between current AI and human intelligence. The second issue will be overcome by developing the science of AI adoption, with particular attention to ensuring that AI is deployed responsibly, to aligning AI innovations with equity, diversity and inclusion objectives, and to co-building solutions in real-life situations with end users, members of underrepresented groups and Indigenous Peoples.
What? To mobilize R3AI in sectors of strategic importance for Canada, IVADO Labs will implement the new AI design and adoption strategies in three priority sectors in which the partners have major strengths:
- useful new molecules: reduce the time and cost of discovering new drugs, e.g., those needed to fight future pandemics and antimicrobial resistance, as well as help to discover the materials required to achieve carbon neutrality;
- environmental emergencies: decipher and predict biodiversity data to mitigate climate change and improve global health; and
- health systems: develop predictive, explainable and causal health models generalizable across communities and organizations that will have critical outcomes for patients and health systems.
R3AI will provide solutions to logistics and supply-chain challenges cutting across these three priority sectors.