Apple’s focus on data privacy and the end-user experience while balancing A.I. ambitions

December 7, 2022, 10:23 PM UTC
Yael Garten, Director of AI/ML Data Science and Engineering, Apple discussing a topic on stage with her hands up.
Yael Garten, Apple's director of A.I. and M.L. engineering, speaks at Fortune's Brainstorm A.I. summit in San Francisco on Dec. 5, 2022.
Nick Otto for Fortune

Apple is not new to the artificial intelligence hype train that has consumed Silicon Valley.

The multi-trillion dollar company adopted the neural engine chip in its iPhone X in 2017, specifically to enable quick face recognition for the Face ID authentication feature, and launched one of the first A.I.-powered virtual assistants with Siri in 2011.

While Apple has lagged behind its Big Tech counterparts because A.I. can be at odds with the company’s mission for data privacy, it’s pushing forward with these ambitions methodically to ensure the best of both worlds, according to Apple’s director of A.I./M.L. data science & engineering Yael Garten.

“We put a lot of focus and thought and energy into how we can create great machine learning-based products that are also privacy-preserving,” Garten said at Fortune‘s Brainstorm A.I. conference in San Francisco on Monday.

The tech giant has created a number of innovative products using A.I., such as the “Hey Siri” voice recognition feature and Apple Watch’s sleep tracking function. Garten told the audience that products like these come from the company’s obsession with the end-user experience. As The Verge once put it, Apple’s A.I. plan is “a thousand small conveniences.”

“I personally don’t think that A.I. and machine learning is the solution to every problem,” Garten said. “So I do really think it comes back to the core of asking what is the business problem I’m trying to solve.”

Due to the overwhelming amount of fanfare surrounding A.I., technologists have to scrutinize what the best use cases are. A company doesn’t have to power every product they release with A.I., but there’s a lot of ways to be incredibly innovative if it’s used methodically. So it’s really important to focus on what is it that you’re trying to deliver and identify, Garten said.

“Is there a simpler solution? Or it’s actually the right time and space for you to go and invest in a machine learning-based approach or artificial intelligence-based approach?” Garten said. “So really thinking through that construct is something that helps set it up for success.”

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