A data scientist at AT&T is continuing the artificial intelligence research legacy of her father, a pioneer at the company's famed Bell Labs division. Natalie Gilbert, 30, works in the Chief Data Office, developing AI agents that streamline complex HR processes for the telecom giant's vast workforce.
Her work is directly built upon the foundations laid by her father, Mazin Gilbert, who worked on early speech recognition and synthesis systems in the 1990s alongside AI luminaries like Yann LeCun. "Everything I've built here has the same foundation he was working on: convolutional neural networks," Natalie Gilbert stated.
From Childhood Inspiration to Corporate Innovation
Growing up, Natalie spent after-school hours in her father's office, observing intense technical discussions and complex diagrams on whiteboards. This early exposure inspired her to create her own "super nonsensical" decision trees, fostering a blend of creativity and analytical thinking she uses today.
One formative project was "Dr Bot," an early large language model prototype she worked on with her father that assessed symptoms to recommend care. "What I do with AI agents really boils down to a bunch of decision trees that reason through how to get from point A to point B," she explained, noting it was a skill learned from him.
Transforming HR with Autonomous AI Agents
In her current role, Gilbert is applying these principles to a significant internal project. Her team is developing an AI agent designed to eliminate confusion in navigating HR policies and procedures for AT&T's employees. "We're basically eliminating the question of where to go to solve an HR problem by having an AI agent identify the relevant policy," she said.
This shift towards more autonomous, reasoning agents marks an evolution from the foundational work on convolutional neural networks—which enable computers to process images and sound—conducted by her father's generation. "Their early discoveries have enabled us to work with AI agents and make them more autonomous," Gilbert noted.
The Changing Skillset of an AI Developer
The field's rapid evolution demands constant learning. "It feels like people need to learn something new every two months," Gilbert observed. A key change is the move towards natural language interfaces. "I actually spend most of my time doing prompt engineering, which isn't coding at all; it's using natural language to get machines to understand us."
She cautioned that while tools like coding copilots increase speed, developers must still understand the underlying technology. "If you don't know how the code is actually handling an edge-case scenario, then your AI tools aren't going to be any good."
A Surreal Legacy
Reflecting on the journey from her father's speech recognition research to her work on generative AI and autonomous agents, Gilbert finds the continuity profound. "It's sort of ironic, because this is another form of what my dad did 30 years ago," she said.
For Natalie Gilbert, her career represents more than personal achievement. "AI has changed so drastically in my lifetime, and now I feel like I'm representing him and representing his legacy. Continuing the work that he did feels surreal."