“When systems shape lives, ethics can’t be optional.”

If you look at my résumé, the arc might seem linear — law, finance, global operations, AI. But like most transformations, it was anything but. Every pivot came from a moment of friction: between what was easy and what was right, between comfort and conviction.

I began in law — trained to parse language, respect structure, and understand the contracts that bind individuals and nations alike. That clarity attracted me. But I craved more scale. I transitioned to venture capital, joining a New York investment firm focused on pre-IPO technology companies. There, I saw innovation in its rawest form: fragile, promising, and occasionally, ethically ambiguous.

Later, in the Fortune 500 world, I stepped into operational leadership. I managed profit and loss, led cross-border teams, and optimized complexity into strategy. From the outside, it was a career well-aligned with ambition. But inside, I noticed something else: women, including myself, were being sidelined by legacy systems that weren’t broken — they were working exactly as designed.

That realization burned itself into me.

What Bias Really Looks Like

Bias isn’t always a decision. Sometimes it’s an outcome — engineered by systems that were never meant to include you. I saw brilliant women passed over, diverse voices muted, and data used to justify exclusion. And it wasn’t just personal. It was structural.

So I paused. I left the corporate race and began building platforms — first a nonprofit helping women navigate career transitions, then a learning ecosystem to support global leadership. I thought that was the answer. But again, I hit a wall.

No amount of mentorship and professional development can fix a system architected to exclude.

Enter AI — And a Reckoning

When I first started working on AI projects — with Google, Meta, OpenAI, and Scale AI — it felt like everything I’d done was converging: law, finance, strategy, and systems. But unlike my previous roles, this work didn’t just shape markets. It shaped minds. It shaped justice. It shaped possibility.

That was exhilarating — and terrifying.

AI isn’t neutral. It reflects what we feed it — our data, our decisions, our defaults. Without ethical frameworks, AI doesn’t just replicate bias. It scales it.

And that’s why I stayed.

Ethics Isn’t a Department — It’s a Discipline

It would’ve been easier to stay in finance. Or scale a more commercial product. But for me, the choice was always deeper: to work in alignment with the world I want to help shape.

Ethics in AI isn’t about compliance checklists. It’s about accountability, foresight, and design that centers people — not just performance.

I’ve chosen this path not because it’s easy, but because it’s right. And because the future won’t fix itself.

Choosing Alignment Over Achievement

I didn’t choose AI ethics because it was the fastest path to influence or the most obvious career move. I chose it because it asked something of me — something real. It required not just skill, but principle. Not just knowledge, but vision.

This work demands that we stay uncomfortable, curious, and grounded in values that outlast technology cycles. And that’s why I’m here.

Because I believe we don’t need smarter systems — we need braver ones. And we won’t get there without people willing to stand at the intersection of complexity and conscience, and say: We can build better.