Last fall, Le Wagon Montreal hosted a dynamic panel discussion on Women in AI, featuring Stefania Pecore – AI R&D Director and Ambassador for Women Techmakers, Women in AI, and Women in Games, and Gabrielle Hurtubise-Radet – Principal Manager of Startup Programs at Mila.
The discussion explored breaking barriers, navigating biases in AI, and empowering women to build careers in technology. The panelists shared personal experiences, insights, and practical advice for overcoming imposter syndrome and making an impact in AI.
👉 Click here to see the whole discussion
Stefania’s Journey: From Linguistics to AI
“I started in Italy with a bachelor’s in foreign languages. I was able to discuss cultures, different languages, and literature. But I started wondering: Is learning multiple languages the only way to communicate?”
Stefania’s curiosity led her to machine translation and AI, transitioning from linguistics to computer science. However, she noticed a clear divide between her linguistics peers (mostly women) and the technical students (mostly men).
“I expected easy collaboration, but there was a blockage—maybe from different skills, maybe something else. It felt like two separate groups.”
Now, she encourages others to embrace curiosity and take strategic steps toward tech careers:
“Whoever AI is everywhere. There are many points of entry right now. So you don’t need to be a researcher or a statistician to enter AI.”
Gabrielle’s Path: From law to AI
Gabrielle also entered AI from a non-technical background:
“I studied law and worked in politics. I thought about becoming a lawyer, but I realized that if I wanted to have an impact at scale, technology was the best way.”
Her transition led her to Microsoft, then a startup, and eventually Mila, where she helps AI researchers launch startups. But imposter syndrome was a real challenge:
“When I started at Mila, I couldn’t even think of myself as a woman in AI. I remember an award competition for women in AI, and a colleague said, ‘You should apply.’ And I thought, ‘I’m not a woman in AI.’ But then I realized—I work with AI scientists every day, I help build AI startups—I AM a woman in AI. I applied and became a finalist.”
Her advice to others is:
“Rethink how you position yourself in a male-dominated environment. Flip the perspective—what would your male colleagues do in your position?”
Overcoming imposter syndrome and self-doubt
Both panelists emphasized self-advocacy and community support in overcoming imposter syndrome.
Gabrielle’s word is: recognizing your unique value
“I once received feedback on my work: ‘Please hire someone who actually understands AI.’ And it stung. But then I thought—what are my unique differentiators? I’m an excellent communicator. I build programs and bring people together. And that’s something that even technical people in AI don’t always have.”
Her key takeaway:
“Think about your unique differentiators. What makes you valuable in this field? AI is not just coding—it’s also about communication, ethics, design, and strategy.”
As for Stefania’s, she advises us to bring our own chair
“If the room is closed, or you don’t have a seat at the table, bring your own chair and make sure you can be yourself.”
She encourages people transitioning into AI to be strategic about finding opportunities:
“If it’s your first month in AI, don’t look for a role in a giant company right away. Find a startup or a small company where you can use your existing skills AND your new AI knowledge. Build your journey step by step.”
Addressing bias in AI: why representation matters
The real-world impact of AI bias
The panelists discussed the systemic biases embedded in AI systems, referencing research from UNESCO, the World Economic Forum, and the Alan Turing Institute.
“A study analyzing 133 AI software tools found that 44% showed bias against women, and 25% showed racial bias.”
She outlined several examples:
- Hiring software showed biases against female applicants.
- Chatbots and translation models reinforce gender stereotypes (e.g., female names associated with “family” and “home,” male names with “business” and “leadership”).
- Voice assistants recognize American male voices better than female or accented voices.
- Facial recognition struggles with diverse skin tones, affecting security and healthcare access.
AI bias and body image: in between reflection and reinforcement
The panelists warned us about AI’s impact on body image. Many AI-driven image enhancement tools reinforce unrealistic beauty standards. These distortions are not just technical glitches—they reflect and perpetuate deep-seated societal biases embedded in the data that AI systems are trained on.
“A recent test showed that AI automatically enhanced women’s photos—adding cleavage and altering facial features. This is dangerous, especially for young users who see AI-generated images and believe they must fit an unrealistic standard.”
Gabrielle and Stefania call to action:
“We must actively test AI tools, report biases, and hold developers accountable. AI is shaped by society’s biases, but we have a chance to change that.”
How to take action and build inclusive AI
The panelists advised us to use our time, money, and brain wisely:
“It’s easy to feel powerless about AI bias, but we have three powerful tools:
- Time – Spend it wisely. Engage with ethical tech communities.
- Money – Support AI companies that prioritize fairness.
- Brain – Educate yourself, recognize biases, and speak up when you see them.”
The future of women in AI: representation and networks
The need for more women in AI startups
Gabrielle shared how the intersection of AI and entrepreneurship is still heavily male-dominated:
“When I first started in AI startups, I was often the only woman in a room of 27 men. That’s changing, but we still need more female founders, investors, and leaders.”
The panelists also emphasized the need to build and belong to strong women-led communities to support one another and challenge bias.
They highlighted several initiatives supporting women in AI:
“I once had a colleague who deserved a leadership role but was struggling to get promoted. So we formed a group and actively advocated for her to become a team lead—and she got the job. We need to lift each other up!” – Stefania
Their final advice
As said, Gabrielle and Stefania highlight the importance of building and belonging to strong women-led communities—spaces where women uplift each other and grow despite male dominance and bias.
Taking the leap requires courage, even in the face of fear. Meanwhile, Gabrielle reminds us of the power of resilience:
“It won’t be easy, but success comes from those who keep going. Stay patient, stay true to yourself, and don’t give up.”
Together, their words reinforce a shared truth: stepping forward—scared or not—is the key to empowerment.
Conclusion
The panel offered a powerful discussion on breaking barriers, addressing bias, and empowering women in AI. The key takeaway? Women belong in AI—and we all have a role in shaping its future.
Feeling inspired by the panel’s insights and stories? Ready to challenge biases in AI and help build a more inclusive tech landscape ? Start your journey today! Sign up for one of our upcoming free workshops or book a meeting with our advisors to explore training opportunities that align with your goals! 🚀
