2026 Exploratory IRD Awards
Reducing AI overreliance in mental health care
PI: Vera Békés (Associate Professor, Educational and Counselling Psychology)
AI clinical decision support tools are increasingly deployed in mental health practice, yet overreliance on AI risks compromising decision quality and dehumanization of psychiatric care. Through an experimental study with psychiatric clinicians, we will identify factors that impact overreliance and ways to counteract them. Findings will generate preliminary evidence for a larger research program with direct implications for responsible AI deployment in mental health care.
Leveraging Large Language Models to Detect At-Risk Individuals in Education and Health Sciences
PI: Maria Cutumisu (Associate Professor, Educational and Counselling Psychology)
This project brings together researchers with expertise in education, health, and machine learning to explore how large language models can help identify early warning signs of academic and health challenges. By analyzing patterns in data, the system aims to detect subtle indicators that humans might otherwise miss. The research prioritizes fairness, transparency, and human oversight to ensure responsible use of AI. Ultimately, it aims to enable earlier support and more equitable outcomes for students and patients alike.
Epistemic Dependence, Value Alignment and Freedom of Speech in the Digital Public Sphere
PI: Jocelyn Maclure (Professor, Philosophy)
Freedom of speech requires tolerating the presence of (some) mis- and disinformation, yet the proliferation of false and misleading content threatens our ability to identify reliable information and trustworthy sources, which is essential to allow for healthy democratic institutions. These recent developments are accentuated by new technologies. Dis- and misinformation can now easily be produced through basic prompts fed to freely accessible chatbots built on top of large language models, and recommender systems are known to push misleading or false content on users to keep them engaged. This research project will bring together epistemologists, political philosophers, legal scholars, and computer scientists to identify practical guidelines to regulate new technologies to ensure that they are aligned with democratic goals and respect freedom of speech.
AI-Assisted Quality Assessment in Systematic Reviews
PI: Faleh Tamimi (Professor, Faculty of Dental Medicine and Oral Health Sciences)
Doctors are supposed to make their decisions relying on the available medical literature. However not all medical articles present the same quality of evidence. This project aims to develop an AI that would be able rank medical articles based on their quality . such technology would be able to help doctors make better decisions in their clinical practice
2026 Proof-of-Concept IRD Awards
Improving precision medicine through generative AI: a use case in lung cancer marker identification
PI: Amin Emad (Associate Professor, Electrical and Computer Engineering)
Cancer is the leading cause of death in Canada affecting approximately 1 in 4 Canadians, with lung cancer remaining the most prevalently diagnosed and accounting for the greatest number of cancer mortalities in both males and females. Personalized medicine offers a promising approach by tailoring the treatment strategy to an individual’s characteristics of the disease. However, identifying actionable targets of the disease, specific to an individual, remains a major challenge. Here, we propose a counterfactual-based generative AI model to investigate the molecular mechanisms driving lung cancer at the patient-specific level. Although methodological and preclinical in nature, this project addresses a clinically important challenge: identification of patient-specific markers of the disease to be used as targets of individualized medicine. In the longer term, this approach could support informed, data-driven decision making for therapy recommendation, benefiting the health system and the society.
