The Centre for Advancing Responsible and Ethical Artificial Intelligence (CARE-AI) is located in the heart of the Toronto-Waterloo corridor, at the University of Guelph (U of G). CARE-AI is unique, as it integrates ethics, governance and social responsibility with technical leadership. Our researchers span from faculty across all Colleges on UofG’s campus – working in one or more of the three core pillars: AI methodologies; AI applications; and AI responsibility.
CARE-AI expands our research community’s expertise and fosters a network of over 90 researchers and scholars from across campus, as well as includes an advisory panel of academic and industry leaders. It will focus on applying machine learning and AI to U of G strengths, including human and animal health, environmental sciences, agriculture, agri-food, business, insurance and the bio-economy. CARE-AI researchers will investigate methodologies, including learning algorithms, human-computer interfaces, data analytics, sensors and robots. Researchers at CARE-AI work collaboratively with inter-disciplinary departments, industry partners as well as other institutions to support CARE-AI’s ecosystem.
It is our mission to advance multidisciplinary AI training and research, and its responsible application to improve life.
At CARE-AI we aim to:
1. Study the ethical implications that arise from the growing influence of AI in our lives.
2. Build responsible, innovative AI systems that serve human values and society.
3. Apply AI research advancements to problems that are central to the human condition and society.
4. Train the next generation of AI professionals in core technical AI, and the societal and ethical implications of these emerging technologies.
CARE-AI’s leadership and researchers are comprised of innovative thinkers and research experts paving the way towards an interdisciplinary approach to AI.
CARE-AI expands our research community’s expertise, fostering a network of researchers and scholars from across campus and formed committees with academic and industry partners. Our CARE-AI researchers investigate methodologies, including learning algorithms, human-computer interfaces, data analytics, sensors and robots. The research on machine learning and AI, includes human and animal health, environmental sciences, agriculture, agri-food, business, insurance and the bio-economy. CARE-AI focuses on collaborative research with interdisciplinary departments, industry partners as well as other institutions to support our CARE-AI ecosystem.
Managing Director
Administrative Assistant
Academic Co-Director
Academic Co-Director
School of Engineering
Department of Mathematics and Statistics
School of Engineering
School of Computer Science
Plant Agriculture
School of Engineering
School of Computer Science
School of Engineering
Department of Mathematics and Statistics
School of Engineering
Department of Psychology
School of Hospitality, Food and Tourism Management
School of Engineering
School of Computer Science
Department of Philosophy
School of Computer Science
School of Computer Science
Department of Integrative Biology
School of Computer Science
School of Engineering
School of Computer Science
School of Engineering
Department of Mathematics and Statistics
Department of Engineering
School of Engineering
School of Languages and Literature
School of Environmental Sciences
Department of Management
School of Environmental Sciences
School of Environmental Design and Rural Studies
School of Engineering
School of Engineering
Department of Economics and Finance
School of Computer Science
Department of Mathematics & Statistics
School of Engineering
Department of Mathematics and Statistics
School of Computer Science
Department of Psychology
School of Engineering
Supply Chain Manager, CDL Rapid Screening Consortium
Executive Director, Weston Family Foundation
Partner and Head of Technology and Innovation - Canada, Norton Rose Fulbright
Principal Software Engineer, Untether AI
CEO, Founder, TechGirls
CTO and Partner, Inovia Capital
Interested in becoming a partner, contact:
care-ai@uoguelph.ca
“I think the CSAI program has encouraged me to consider broader ethical implications of applying AI solutions within the medical imaging field. This focus will be invaluable going forward as issues related to respecting patient data privacy and ensuring the fairness of any AI solution are highly relevant to solving healthcare problems.”