GoKawiilFully responsible, trustworthy technology is an almost impossible mandate in a tech landscape that prioritizes speed — but that doesn't mean some companies aren't trying.
On the heels of the Trump administration's national AI legislative framework on March 20, in which "winning the AI race" remains paramount, tech developers face tension between the common ethos of moving fast and breaking things versus strategically implementing responsible tech frameworks from the start.
Getting ahead has, in many instances, taken the driver's seat, the cost of which has become clear. Microsoft's self-admitted realization that AI-generated code often forgoes accessibility makes human oversight and iteration a must.
For Jenny Lay-Flurrie, who became head of Microsoft's Trusted Technology Group in February and has worked in accessibility for much of her 21 years with the company, the responsible development and deployment of tech is two-fold: "How do we make sure that we build it right? And how can we make sure that it stays right?"
Microsoft launched its Trusted Technology Group in early 2025 and has since consolidated all responsible tech initiatives under its umbrella, including Lay-Flurrie's former directive of accessibility.
While Microsoft has centralized its responsible tech under a top-down model, competitors like Google maintain a more engineering-led architecture guided by its core AI principles and specialized safety councils. Techniques vary across big tech, but Microsoft's approach is one that's been reshaped since 2002, when Bill Gates released the Trustworthy Computing memo that prioritized things like reliability over new feature development.
AI's woes (and the people who fix them)
Lay-Flurrie's foray into the broader responsible tech space may be recent, but she says that it follows the same general principles she's used to, including fairness, transparency, inclusiveness and accountability. Microsoft operates on the principle that "people should be accountable for AI" regardless of its outcomes.
That's why, when Microsoft realized its AI wasn't accurately representing blind people, her team moved to fix the problem.
"Some of the generated imagery of blind people came back with people wearing these horrible full-on blindfolds," she said. "These models were being trained on a lot of the material that exists in society. Unfortunately, society is not always the most inclusive place, so there are instances where we have to insert data to train it."
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