Artificial intelligence is reshaping engineering in profound ways, influencing how problems are analyzed, decisions are made, and systems are designed. From academic research to professional practice, Black engineers and students across Canada are engaging with AI thoughtfully and critically, ensuring that innovation is paired with responsibility. During Black History Month, Engineers Canada is highlighting a Black engineer and a PhD student who are not only engaging with AI, but also helping shape how it is used responsibly, ethically, and effectively within and outside the profession.
For Stephen Obadinma, a fourth-year PhD student at Queen’s University, the path into AI was driven by both imagination and opportunity. “I was interested in AI from a young age,” Obadinma says, recalling how films such as Blade Runner and Ghost in the Shell sparked questions about machine intelligence and sentience. That early curiosity became action during his undergraduate studies in computer engineering, when he discovered the Natural Sciences and Engineering Research Council of Canada (NSERC) Undergraduate Student Research Awards. “It was a rare opportunity as an undergrad,” he explains. “After my summer doing research, I had a lot of fun and was able to help contribute to a new dataset and paper, so I decided to continue doing research in AI and stay on for a master’s and PhD with the same supervisor.”
Since then, the field has changed dramatically. “The models and methods we are using now are totally different,” Obadinma notes, describing how quickly AI has evolved during his academic journey. His current research focuses on AI safety, particularly adversarial attacks against large language models. Rather than assuming these systems behave as intended, Obadinma tests how they respond under pressure. “Much of my work now is on attacking large language models to see how they deal with pressure and whether they can be made to behave in ways they are not supposed to.”
He emphasizes that the stakes are high. “Now that AI is being adopted en masse and is being incorporated into practically everything, its capability for harm has skyrocketed,” Obadinma says. He points to real-world consequences, such as biased resume screening tools that can unfairly impact thousands of people. Compounding this risk is the lack of transparency surrounding many popular models. “We have no idea on which specific data they were trained on, or how they were trained, or which specific process they underwent to mitigate bias,” he explains. For Obadinma, academia plays a vital role in addressing these challenges by rigorously testing systems and publicly sharing findings to influence both developers and regulators.
Obadinma’s perspective is also shaped by lived experience. “As a Black student, I am acutely aware of how people’s implicit bias can lead to uncomfortable interactions and feeling marginalized,” he says. Recognizing that AI can replicate and amplify these same biases motivates his focus on safety. “It gives me motivation with my research to really stress-test these models.”
In professional practice, Regina Inaya, a civil engineer and project management professional, brings a complementary perspective from the field. Drawn to engineering through a love of problem-solving, Inaya says, “Math quickly became my favorite subject because I liked finding answers and saw each problem as a puzzle to figure out.” That curiosity led her to civil engineering, where she saw an opportunity to create solutions that have lasting impact. “Small, thoughtful changes can lead to big results,” she says, “and civil engineering lets me create solutions that last for years.”
Inaya’s interest in AI grew naturally alongside her engineering career. “I’ve always liked learning for its own sake,” she explains, noting that her curiosity evolved into a sense of responsibility as AI began reshaping industries. “I believe in preparing for the future before it arrives. I want to be equipped not just to adapt, but to contribute in a responsible and meaningful way.”
In her current role as a Quality Manager, Inaya uses AI as a practical support tool rather than a replacement for engineering judgment. “I primarily use AI as a brainstorming and productivity tool,” she explains. “It supports me with drafting reports, developing standard operating procedures and checklists, creating meeting summaries and templates, and performing data analysis.” While her role has shifted away from core design and construction activities, she consistently uses AI to improve “efficiency, clarity, and quality of deliverables.” She also participated in a project where AI-enabled tools helped a client make informed decisions about which products were most viable.
Inaya has also seen AI’s impact at a systems level, citing Ontario Power Generation as an example. “AI-driven tools optimize streamflow forecasting and process extensive sensor data in real time,” she says. “This capability enables engineers to intervene proactively, minimize downtime, and prolong the operational lifespan of essential infrastructure.” For her, these advancements represent a new era where creativity, precision, and sustainability can coexist.
Both Obadinma and Inaya stress the importance of representation in engineering and AI. “The systems we design influence real lives, communities, and futures,” Inaya says. “When those responsible for building these systems represent only a narrow segment of society, significant perspectives are unintentionally excluded.” She emphasizes that inclusive representation strengthens innovation and creates a ripple effect for future generations.
They also challenge common misconceptions about AI and its role in engineering. Inaya addresses the fear that AI will replace engineers, explaining that “AI excels at processing data and running simulations, but it cannot replace human judgment, ethical reasoning, or contextual understanding.” Obadinma adds that another widespread misconception is viewing AI as a tool that can be used naively, without training or critical awareness. “AI is often treated like a magic box,” he says, noting that this mindset leads some people to reject it entirely while others rely on it without considering its limitations. “AI is a tool that requires actual skill to operate properly,” Obadinma emphasizes, arguing that education and thoughtful use are essential to avoid harm and ensure AI is applied where it can genuinely help.
Together, their experiences highlight how Black engineers and students are shaping the future of AI in engineering with intention, critical thinking, and accountability. As AI continues to evolve, their voices underscore the importance of building systems that are not only innovative, but also ethical, inclusive, and grounded in human expertise.
