“I’ve seen how easily a system can look ‘ready’ while the people inside it are not. At one point, we had a forecasting capability that was performing extremely well, yet it still wasn’t used as leadership expected it to be.”
Rogayeh Tabrizi finds that people often frame Diversity, Equity, and Inclusion as an abstract statement of values, rather than as a useful way to picture something more operational: equity shows up as the rules of the game. Who gets invited into the room where decisions are made, whose mistakes are tolerated, who is expected to be certain before they speak, and who is allowed to learn in public.
Discussion of DEI often sticks to the abstract, often to avoid naming the many things that organizations silently rely on, but prefer to keep implicit. The reluctance to name those rules out loud—what truly goes into the hiring process, how credibility is granted, how risk is distributed—is exactly what subtly pushes important voices to the margins.
“Success isn’t a title, or even a milestone.” It’s about making decisions that are clearer, more accountable, and less dependent on hidden rules. It’s being able to explain your choices, learn from outcomes, and improve the system for the next person who comes through it.”
Rogayeh’s path into AI started far from business. In particle physics, one learns quickly that complex systems punish simple stories. “You can’t isolate one variable and pretend the rest of the universe is politely waiting,” she quips. “Economics gave me the parallel lesson on the human side: people don’t respond to ‘truth’ in the abstract; they respond to risk, constraints, and uncertainty, with limited information. Put those together, and inclusion stops being abstract. It becomes the deliberate work of changing the environment so that contributing, disagreeing, and learning don’t carry a higher personal cost for some people than for others.”
That kind of change can feel uncomfortable at first, because it challenges familiar habits and informal shortcuts. Many organizations have inherited practices that were never designed for scale, fairness, or clarity; often, they were never designed at all, but simply emerged as patterns of familiarity and ease. Without redesign, the system stays biased even when intentions are good. The environment is a prerequisite for the inclusion of marginalized voices, and it doesn’t appear on its own. It has to be built.
“I’ve seen how easily a system can look ‘ready’ while the people inside it are not. At one point, we had a forecasting capability that was performing extremely well, yet it still wasn’t used as leadership expected it to be. It wasn’t a technical failure. It was a decision failure: different teams were optimizing for different definitions of success, and the perceived cost of being wrong outweighed the benefit of being right. Cases like these are everywhere, and often in these situations, some people are rewarded for being cautious, for doing things the way they’ve always been done. Others are punished for taking risks, even when those risks are reasonable or have been shown to be hardly risks at all. In our case, the model could produce a near-perfect recommendation, but the organization hadn’t created conditions where acting on that recommendation felt safe.”
That’s what Rogayeh means when she says equity shows up in the mechanics. “If the safest option is always to do what’s familiar, then the people who are already established will keep winning—not because they’re better, but because the environment rewards staying inside the lines. This is also why DEI can’t be separated from governance. You can’t ask people to contribute courageously if the cost of being visible is uneven. You can’t claim to value diverse perspectives if the system only rewards a narrow communication style, or if ‘credibility’ is granted through networks rather than evidence. And you can’t build responsible technology if the voices raising concerns are treated as obstacles instead of essential contributors.”
Rogayeh’s perspective on success is shaped by those lessons. “Success isn’t a title, or even a milestone,” she emphasizes. “It’s about making decisions that are clearer, more accountable, and less dependent on hidden rules. It’s being able to explain your choices, learn from outcomes, and improve the system for the next person who comes through it. In practice, that often means building structures that outlast any individual: clear criteria for roles and promotion, consistent evaluation processes, definitions that are openly shared across teams, and feedback loops that treat learning as part of performance rather than a detour from it. Success is not only doing excellent work—it’s helping create an environment where excellent work can be recognized, adopted, and trusted in the long run.”
If Rogayeh could offer advice to younger women, it would be this: “Treat clarity as a form of power. Ask for the criteria. Ask what ‘good’ looks like, who decides it, and how it will be measured. Build depth in something real, but don’t underestimate translation—connecting the details of your work to the people and decisions it’s meant to support. And protect your agency. New systems like AI are powerful, but their value still depends on people using them responsibly. The same is true of inclusion: representation matters, but what changes outcomes is when opportunity stops being allocated by ambiguity and starts being allocated through clear, consistent decisions.”
