Canada-UK Artificial Intelligence Initiative: Projects Funded


News release: Canada and the United Kingdom collaborate on responsible artificial intelligence

Read more details about the 10 international research projects funded  through the Canada-UK Artificial Intelligence Initiative.

BIAS – Responsible AI for Labour Market Equality

(Linglong Kong, University of Alberta and Monideepa Tarafdar, Lancaster University)

This project will look at how AI can both lead to and lessen unintentional bias in job advertising, hiring and professional networking processes, which are increasingly digitalized. The researchers will work with industrial partners to understand and mitigate gender and ethnic biases within HR processes, such as hiring and professional networking.

Responsible AI for Inclusive, Democratic Societies: A Cross-Disciplinary Approach to Detecting and Countering Abusive Language Online

(Wendy Hui Kyong Chun, Simon Fraser University and Kalina Bontcheva, University of Sheffield)

Recently the UK government has started considering regulatory measures requiring social media platforms to address abusive language and hate speech through content moderation. This project aims to develop shared knowledge on responsible AI methods to automatically detect and counter abuse and hate speech online.

Responsible Automation for Inclusive Mobility (RAIM)

(Babak Mehran, University of Manitoba and Ed Manley, University of Leeds)

The RAIM project will develop new models of autonomous transport for enhancing mobility in ageing populations. The research will build a better understanding of the opportunities and challenges facing autonomous transport, and build these into AI methods for estimating future demand and optimizing new services.

Self-guided Microrobotics for Automated Brain Dissection

(Aaron Wheeler, University of Toronto and Danail Stoyanov, University College London)

This project will develop a powerful new tool for microsurgery using AI-driven microrobotic systems to identify and collect targets from within complex biological tissues. The system will be used to harvest rare neural stem cells, which hold great promise in treating neurodegenerative diseases and traumatic brain injuries.

EPI–AI: Automated Understanding and Alerting of Disease Outbreaks from Global News Media

(David Buckeridge, McGill University and Nigel Collier, University of Cambridge)

The EPI–AI project aims to achieve a step change in automated global epidemic alerting using news media monitoring. Teams at McGill and Cambridge universities, in collaboration with national and international public health agencies, will adopt an interdisciplinary approach that combines natural language processing, epidemiology, biomedical informatics and bioethics to address this complex task.

Using AI-Enhanced Social Robots to Improve Children's Healthcare Experiences

(Samina Ali, University of Alberta and Mary Ellen Foster, University of Glasgow)

Children experience pain and distress in clinical settings daily, with negative short-term and long-term consequences. Working with stakeholders, we will develop a robust, adaptive, socially intelligent robot designed to distract children during painful clinical procedures, thereby reducing pain and distress. The robot's effectiveness will be evaluated through a clinical trial.

AI-driven Biomaterial Screening to Accelerate Medical Device Development

(Nicole Li-Jessen, McGill University and Adam Celiz, Imperial College London)

Conventional research and development for biomaterials in healthcare is expensive and laborious and heavily relies on in vitro and in vivo models. The overarching goal of this project is to integrate AI into the development pipeline to reduce cost and accelerate the discovery of new biomaterials for medicine.

AI to Create Equitable Multi-Ethnic Polygenic Risk Scores that Improve Clinical Care

(Brent Richards, Jewish General Hospital and Michael Inouye, University of Cambridge)

Recent breakthroughs in genomics and machine learning have generated genetic risk scores with the potential to improve patient care and health maintenance; however, these tools work better for individuals of European ancestries than other ancestries. We will develop state-of-the-art AI to address these inequities and improve health for all.

Leveraging the Impact of Diversity in Neurodevelopmental Disability (NDD) by Integrating Machine Learning in Personalized Interventions

(Francois Bolduc, University of Alberta and Ian Dunham of the European Bioinformatics Institute)

NDD includes disorders of cognitive, emotional and social development, affecting 13% of the population. While our understanding of genes involved in NDD has exploded, interventions are still relatively generic. We will use machine learning to better understand how diversity between individuals with NDD could guide more personalized interventions.

The Self as Agent-Environment Nexus: Crossing Disciplinary Boundaries to Help Human Selves and Anticipate Artificial Selves

(Georg Northoff, University of Ottawa and Karl Friston, University College London)

This project aims to help people suffering from abnormal changes in their perception and self, as in psychiatric conditions like schizophrenia. This not only carries major ethical implications for the understanding of ourselves, but will also inform the second aim of this project, paving the way for an understanding and mathematical theory of artificial selves.

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