CARE-AI awards four research projects across campus to further U of G’s expertise in ethical Artificial Intelligence
Researchers from across campus supported with $40k in seed funding.
U of G’s Centre for Advancing Responsible and Ethical Artificial Intelligence (CARE-AI) seeks to advance multidisciplinary AI training and research alongside responsible application to improve life. By supporting research projects CARE-AI fosters a network of researchers and scholars from across campus to push AI forward.
Kevin Matsui, Director or CARE-AI shared, “I’m really excited to see the work this funding is supporting. Each year we get more and more applications, with interesting collaborations that demonstrate the capacities we have at U of G.” The world of AI is evolving quickly, integrating across many sectors and disciplines. “It’s important that we explore the benefits of AI with integrity and showcase how it can improve society when researched well and with the right intentions,” says Matsui. Representatives from all seven colleges helped select the following projects for funding:
Public Health
Dr. Jennifer McWhirter, from OVC and Dr. Fattane Zarrinkalam from the School of Engineering, along with Postdoctoral scholar Melissa MacKay and PhD candidate Sydney Gosselin will explore promising applications for AI in public health, specifically health communications.
The research team will apply text- and graphics-based generative AI models to develop social media campaigns for a current public health issue and measure its effectiveness in terms of health communication evidence, accuracy, and ethical issues such as stigma and bias. It is hoped that the research can support future use of AI in the health sector to promote health effectively and equitably.
Sustainable Agriculture
Drs. Ashutosh Singh, Abdallah Elsayed, Guneet Kaur, from the School of Engineering are collaborating with Dr. Jayasankar Subramanian, from Plant Agriculture and external partner Dr. Gopu Raveendran Nair from the University of Illinois Urbana-Champaign to apply machine learning tools for development and characterization of nanoparticles to improve agricultural sustainability.
The study intends to develop nanoparticles (NPs) with specific and unique characteristics for application as nutrient carriers, for plant disease suppression or for pest management (nanopesticides/nanoinsecticides) to improve agricultural sustainability.
Combating Disease
Dr. Eranga Ukwatta, School of Engineering and Dr. Yan Yan from the School of Computer Science are using AI to improve the efficacy in medical imaging applications.
Their research will work to create a fully automated cancer diagnostics tool based on medical images to detect abnormalities and characterize them. This will help to reduce subjectivity and variability amongst radiologists, improving diagnosis and treatment outcomes.
Exploring Social Fandom
Dr. Ritu Chaturvedi and Dr. Stacey Scott from the School of Computer Science, Dr. Benjamin Giguère from Psychology, and Computer Science Postdoctoral scholar Leila Homaeian are using machine learning to identify social support among global fandom members on social media.
This research can help to understand how AI may be used to automatically detect social support behaviours in online communities and potentially be applied to automatically connect support seekers with support providers.