Women & AI: Making the Invisible Visible
Why This Matters
At a recent session with my company’s Women in Technology Employee Resource Group, we heard from Nina Schick, author of DEEPFAKES (2020), the first book to explore generative AI’s broader societal impact. Nina reminded us that women are profoundly underrepresented in AI, and that this gap will have consequences in countless ways.
Her advice stuck with me:
“Whatever your niche, AI is about raising the ceiling on intelligence, creativity, and productivity. Your view and experience are relevant.”
That was a call to action for me. If AI will reshape how we live and work, women must have a hand in shaping it, not just adapting to systems designed without us in mind.
My Framework for Women & AI
As I thought about where to begin, I sketched a framework that I could use both personally and professionally:
Concerns: patriarchal bias, weaponization of facts, exclusion risks
Opportunities: women’s representation, ethical approaches, knowledge-sharing
Safety: risks of biased systems, governance challenges
Inclusion: ensuring women’s voices are heard, tracking legislative shifts
This framework helps me explore not just the risks of AI but also the ways women can lead in shaping its use.
A Personal Lens
My journey started long before I ever worked in technology. I studied philosophy in college, then worked in a nonprofit supporting victims of violent crime. Those experiences sharpened my awareness of how violence against women operates at the edges: ever present, often ignored.
Later, I found myself in tech and now actively working with AI. Philosophy taught me to think deeply as a strategy for life. Nonprofit work taught me how systems often fail women. Both perspectives shape how I see AI today.
I live in Pennsylvania, surrounded by hills and valleys. For years, I didn’t even notice them, they were simply the backdrop. And then it hit me: patriarchy functions the same way. Invisible, yet always surrounding us. It determines healthcare access, erases women’s data, and sidelines our voices.
Those invisible hills are now embedded in AI. And if women’s data is already scant, with governments actively purging more, what happens when AI systems are built on that erasure?
The Risks We Cannot Ignore
When I think about AI through this lens, several urgent risks come into focus:
Representation: If women’s voices aren’t included, we get systems built on male-centric data and assumptions.
Violence: Deepfakes, harassment, and sexualized AI tools disproportionately target women.
Erasure: Governments are stripping gender and reproductive health data from public sources, making women’s realities invisible to future AI training sets.
Environmental Impact: AI’s energy-hungry data centers will reshape economies and environments — but how will the costs fall disproportionately on women?
What We Can Do
So why should women make our voices heard in AI? Because silence means acceptance of the status quo.
AI can lighten our loads:
Automating mundane tasks that drain time and energy.
Helping us research, plan, and advocate for our families.
Allowing us, in professional roles, to focus on strategy rather than drowning in tactical work.
But we can’t simply be consumers of AI. We must be builders, questioners, and advocates.
Here are some ways forward:
Learn and experiment: Don’t let hesitation stop you from using AI. Start small, and share what works.
Amplify women’s voices: Read and promote women researchers, writers, and leaders in AI.
Track legislation: Stay alert to laws that shape AI governance — and speak up when women’s rights are threatened.
Challenge the culture: Push back when colleagues reduce women’s absence in tech to “a boys’ club” or dismiss skills that don’t fit the narrow male mold.
Closing Reflection
If the voices shaping AI remain mostly male, the systems we inherit will reproduce the invisible hills of patriarchy that have always surrounded us.
That’s why women must not only participate in AI but lead in reshaping it. Not from the margins, but from the center.
Written by Alana Moran — exploring the intersections of Women, Data, and AI
