Immigrants of Tech - Shabnam Haghzare

Meet Shabnam Haghzare! Shabnam is the National AI Lead at Mitacs - Canada's leading innovation organization. Here we talk about how AI has evolved since she got into the space, her experience with gender equity in AI and what she's excited about when it comes to building her career in Canada.

So, maybe we'll start with a little bit about your background—tell us your story.

Sure, it's a bit of a long story! My CV will give you an idea, but I’ll walk you through some highlights. I originally started studying Electrical Engineering back home, though I had initially switched from Computer Engineering. Looking back, I realize that it was probably a mistake since I now do a lot of work that can be categorized under computer science. But at the time, there was this strong cultural influence—if you scored high on the entrance exams, you went into Electrical Engineering, no questions asked. Another thing that influenced my decision was that a few people told me, “Electrical engineering isn’t really a fit for girls.” That really spurred me on, like, “I’ll show them.”

It turns out, that wasn’t the best decision for me. What I ended up doing later during my Master’s and PhD at the University of Toronto was biomedical engineering in name, but applied AI in practice, which could have been closer to courses in Computer Engineering. So, in a way, things came full circle.

After my PhD, I did a postdoc and some AI consultancy work with Public Health Quebec, where I was part of a major AI project focused on road safety. From there, I transitioned into two startups before moving on to my current role with Mitacs as the National AI Lead and serving on boards of another non-profit, Cybersecurity Global Alliance. But that’s the quick version of my journey!

That’s quite the journey! I’m especially curious to hear about two things: how AI has evolved since you entered the field, and your thoughts on gender equity within the space.

Great questions. Let's start with AI’s evolution. I like to compare the progression of AI development to the stages of the human information processing system. You have perception, processing, decision-making, and finally, task automation. Early AI focused on automating simple tasks—like image recognition, which mimicked the perception stage of human cognition.

As AI advanced, it moved into decision-making processes, like identifying threats in vehicles. But at that point, it wasn’t taking action—just flagging something as a threat. The real progress we’re seeing now, and what I find most exciting, is in the final stage: task automation. We're seeing AI not only recognize and analyze but also execute actions, like in robotics or autonomous vehicles. AI is transitioning from passive to active roles, which is a huge leap.

I also think robotics is going to be the next big frontier for AI because it's less safety-critical than autonomous vehicles, so the adoption rate can be faster. The language models we’re seeing now, like GPT, are also pushing the boundaries by automating more sophisticated, action-oriented tasks.

That’s fascinating. It’s clear AI is evolving rapidly. What are the main challenges in retaining and advancing diverse talent in tech and AI? How can companies better support diverse professionals in reaching leadership roles?

Honestly, I feel incredibly fortunate with the institutions I’ve been part of—University of Toronto, Public Health Quebec, Mitacs. All of them have really committed to equity, diversity, and inclusion. But the challenge I see isn’t recruitment. I think companies have made strides in hiring diverse talent. The issue is retention and advancement—giving people the wings to grow and shine.

In AI and tech specifically, many companies are doing better than more traditional sectors, like finance. But we still lack role models. Yes, companies recruit women, BIPOC individuals, and people from other underrepresented backgrounds, but how many of them make it to decision-making levels? It’s rare. In all my years in AI, I can probably name fewer than 20 women who have reached those higher levels. That’s where I see the gap. It’s not that the talent isn’t there—it’s the support and mentorship needed to help diverse professionals climb the ladder.

That’s something we’ve heard often—there’s a desire to diversify, but the outcomes don’t always follow.

Exactly, there’s a gap between intent and action. I think mentorship could be part of the solution. Programs that help elevate people by sharing experiences and offering guidance could bridge that gap, but it’s still a work in progress.

Agreed. Let’s shift gears. What drew you to build your career in Canada?

Great question. For me, it was a combination of personal and professional reasons. Family was one part, but professionally, the University of Toronto’s reputation for AI was a big draw. I knew it would place me in a network of institutions that work across health, society, and AI, which was really appealing to me.

Toronto itself was another factor. It’s such a diverse city, and having been here before for my Master's, I knew it would be a place where I wouldn’t feel like a stranger. The inclusivity and the opportunity to learn from people all over the world really made it a natural choice for me. I’ve always said the only other place that might compare is New York, but even then, I think Toronto has its own unique inclusivity.

What advice would you give to newcomers looking to break into the tech field?

Put yourself out there! It’s really important to meet people and understand the professional culture. Tech is a fast-paced and dynamic field, and you need to know the ecosystem to find your place. Whether it’s through networking events, meetups, or conferences—just show up and learn. I’m still doing this myself, and it’s always a learning process.

Last question—what’s the most Canadian experience you’ve had?

Oh, I have two stories! One is from a conference I attended in Banff, Alberta. After the conference, I decided to go hiking, and someone told me to bring a bear spray and ringer—because it was prime grizzly bear season. Sure enough, I ran into a mama bear and her cub. My first instinct was very Canadian—I thought, “Oh, how cute!” But a passerby was like, “What are you doing? Get away!” Luckily, nothing happened, but it was definitely a close encounter.

The second one is during my PhD. I was working with older adults in a research study about automated vehicles for people living with dementia. One participant, a gentleman in his 70s, volunteered his time during COVID to come in for our research. Afterward, he sent me the sweetest thank-you card with a bear on it, thanking me for the opportunity when, really, he was doing me the favor. That was a moment that really touched my heart—it felt quintessentially Canadian.