Research @ Carleton
How Canadians feel about AI. May 2024.
Read the full paper here
I conducted a quantitative research study in collaboration with Carleton University examining how Canadians perceive the use of artificial intelligence and autonomous technologies in commercial aviation. As AI becomes increasingly embedded in airport operations, flight planning, maintenance, and future autonomous aircraft, this project addressed a growing gap in Canadian-focused public perception research — especially as previous studies were outdated or limited in scope.
This project strengthened a core part of my engineering philosophy: building systems that earn public trust by being transparent, intuitive, and aligned with human expectations. Whether designing a robotic system, a digital platform, or an AI tool, understanding how people perceive technology is just as important as understanding the mechanics behind it. Studying public sentiment around AI in aviation taught me how technology succeeds only when engineering decisions, safety expectations, and human comfort all move together — a principle that guides my work across robotics, software, and human-centered design.
Objectives
Measure Canadians’ awareness, trust, and concerns regarding AI use in aviation.
Identify conditions under which the public would accept autonomous passenger aircraft.
Understand how demographic factors (age, education, region) shape attitudes toward emerging aviation technologies.
Provide updated insight reflective of post-ChatGPT public literacy around AI.
Contributions & Outcomes
Designed a 42-item survey using Qualtrics, combining original questions with validated items from Pew Research Center and prior aerospace studies.
Conducted a pilot test, optimized question logic, and deployed the survey nationwide via Amazon MTurk.
Processed 233 valid responses, performed data cleaning (bot detection, speed checks, attention checks), and ran statistical analyses (ANOVA, chi-square tests).
Coded qualitative responses, generated word clouds, and synthesized findings across demographics and perception categories.
Produced a full research report discussing patterns, limitations, and implications for policymakers and aviation stakeholders.
Found that 97.9% of Canadians are familiar with AI broadly, but only 65.7% are aware of AI use in aviation.
Identified conditional optimism: strong support for AI improving operational tasks (e.g., route planning, maintenance), but major concerns around safety, reliability, and speed of rollout.
Discovered significant demographic effects: younger and more educated respondents were more supportive of AI in aviation and more willing to fly autonomously.
Highlighted that public involvement is crucial — 95.3% of respondents want a major or minor say in how autonomous aircraft are deployed.
Established a contemporary baseline for Canadian attitudes, filling a national research gap.
Technical Skills
Human-centred research & UX insight — understanding how real stakeholders perceive complex systems.
Data analysis & statistics — ANOVA, chi-square, effect sizes, coding qualitative data.
Survey design & methodology — validation, sampling, bias mitigation, and research ethics.
Technical communication — translating data into actionable insights for policy, industry, and engineering contexts.
