Leah davis

About

Leah Davis is a PhD student and Vadasz Scholar and Doctoral Fellow in the RAISE Lab in the Artificial Intelligence (AI) ethics stream in the Faculty of Electrical and Computer Engineering at McGill University. She recently graduated from the University of Oxford with a Master of Science in Social Data Science at the Oxford Internet Institute. Her thesis, supervised by Dr. AJung Moon, Dr. Brent Mittelstadt, and Dr. Daria Onitiu, “In Good Measure: Designing A Systematic Fairness Metric Selection Framework for Machine Learning Practitioners” created a dynamic working software prototype for tracing fairness metric selection decision-making processes.

Before graduate school, Leah earned her Bachelor of Engineering from the Biomedical Engineering Co-op Program at the University of Guelph, where she completed over two years of industry experience as an Engineer-in-Training in requirements engineering positions within software quality assurance and medical device regulation. Alongside, she worked in AI course and program development at the Center for Advancing Responsible and Ethical AI (CARE-AI) at the University of Guelph and as a Researcher in sociotechnical harms and evaluation procedures at the Montreal Institute for Learning Algorithms (MILA) - The Quebec AI Institute. Her leadership experience centralizes two core themes: female empowerment and peer mentorship within engineering and STEM subjects, parallel to engineering education and engagement work. She’s held various leadership roles within the Open Roboethics Institute, the Engineering Student Societies’ Council of Ontario (ESSCO), the Ontario Network of Women in Engineering, Women in Science and Engineering chapters, and the Oxford Women in Computer Science chapter. She also led the development of the Linacre Boat Club mentorship program during her time on the rowing team in her Masters.

For more information, please visit her website at https://leahdavis.boxmode.io/ or LinkedIn profile at bit.ly/3JnD1uj.

Projects

General All-Purpose AI Auditing Project (Co-Lead), August 2024 - Present

Collaboration with Dr. AJung Moon (McGill University), Dr. Dominic Martin (Université du Québec à Montréal), and Dr. Sébastien Gambs (Université du Québec à Montréal)

Adapting Traditional Measurement Models for Sociotechnical Evaluation (Lead), August 2024 - Present

Collaboration with Dr. AJung Moon (McGill University)

Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Contributor), July 2023 - Present

Collaboration with Shalaleh Rismani (McGill University), Dr. Renee Shelby (Google Research, JusTech Lab), Dr. Negar Rostamzadeh (Google Research), Bonam Mingole (Penn State), and Dr. AJung Moon (McGill)

In Good Measure: Designing a Fairness Metric Selection Framework for Machine Learning Practitioners (Lead), January 2024 - August 2024

MSc Thesis supervised by Dr. AJung Moon (McGill University), Dr. Brent Mittelstadt (University of Oxford), and Dr. Daria Onitiu (University of Oxford)