The Queer Latina Trying to Build Bias-Free AI

The Queer Latina Trying to Build Bias-Free AI

Laura Montoya, founder and CEO of Accel.AI, a global career development program lowering the barriers to entry in engineering artificial intelligence while fostering inclusion.

SourceSean Culligan/OZY

Why you should care

Because lowering the barriers to entry in AI engineering lifts everyone up.

Imagine this: You’re an awkward, lonely 7-year-old who’s just moved to a new city, and your BFF is your teddy bear. Wouldn’t it be awesome if, rather than imagining Teddy’s personality, he could be a real-life, responsive friend? “I love the idea of being able to connect with something that would otherwise be an inanimate object,” says Laura Montoya, CEO and founder of Oakland-based Accel.AI, an artifical intelligence training accelerator. “Something a child could connect with and have a friendship with … I’m captivated by that idea.”

Montoya moved around a lot as a kid — from Los Angeles to Miami to Michigan — and the idea of being able to create artificial life never went away. AI is a booming industry today, but Montoya, who launched her company in September 2016, is worried that it’s becoming too homogeneous. Her goal with Accel.AI is to counteract that problem by training groups that are underrepresented in AI and make the industry more diverse.

Of course, that’s a huge oversimplification, and Montoya, 30, is frighteningly aware of the challenge she’s taken on. Over 90 percent of startups fail and 20 percent never make it past their first year, but the ginger-haired wild child is ready to go down fighting — after all, she says, if she doesn’t, who will? Deep learning and AI are often referred to as the future of work, but what about all the folks who never had a shot at learning about it?

“AI tech is a direct reflection of the people who are engineering it, so any bias by these individuals will be reflected in the products they create,” Montoya tells OZY — something she’s seen many times with “tech bros” in Silicon Valley. Looking for examples? In 2009 HP’s imaging software couldn’t recognize Asian faces, and Harvard’s Project Implicit discovered that people automatically assign positive or negative behavior to different skin tones. That’s the impetus behind Accel.AI: to make sure that diverse people have a say in tech of the future.

She’s building out a curriculum for an AI boot camp, the concept being to turn noobs into AI whizzes in seven months.

As the daughter of a Colombian immigrant, Montoya’s especially sensitive to how important it is that all voices get heard, citing her father’s struggles to adapt as one reason she wants to use her U.S. privilege to change things for the better. But she’s also found that her status as a queer Latina is an inherent obstacle. There hasn’t been overt discrimination, but she’s received less funding and more questions about her background than her male peers — one potential investor even suggested she get a male co-founder. “I’m not surprised about these responses,” she says, having seen the depressing stats about how few female entrepreneurs there are. “It encourages me to keep going and be successful.”

Montoya’s route into AI, despite her curiosity, was circuitous. As a child she wanted to be a vet and studied biology and physical science at college but found she enjoyed planning and building projects more than dissecting animals. Then, after working in community outreach for a while, she felt herself pulled toward tech and signed up for a six-month developer boot camp, which led to an engineering job at Intuit. Her passion for AI was rekindled, but breaking into the space with zero experience seemed tricky, so she used her hustle, attending every AI-related Meetup.com event she could until she’d amassed a group of experts willing to help fulfill her vision of offering training for a diverse population. She started hosting regular events and, in 2016, took the next step — leaving her job to launch Accel.AI and run it full-time.

It was a crazy, risky idea — precisely what convinced Salesforce software engineer Abhishek Sharma to help out. “She wasn’t doing this for glamour or money,” he tells OZY. “It was for helping people who don’t get opportunities.” Sharma provides Montoya with AI technical know-how but says he gets fewer calls these days because she’s a quick learner.

So far, her goals are on track: 55 percent of the attendees at her February 2017 workshop were women and 29 percent of all attendees identified as Latinx. Globally she’s getting a presence too, traveling to Oslo, Taiwan and Taipei to present on building bias-free AI. To scale, she’s building out a curriculum for an AI boot camp, the concept being to turn noobs into AI whizzes in seven months — ideally with a nonprofit arm to provide scholarships for minorities. She’s beta-testing the curriculum now, with modules on deep learning, coding and big data, and plans to kick it off in 2018.

With so much on her plate, you’d think Montoya would be a workaholic, but she’s emphatic that self-care is essential for being productive. She does yoga most days, runs a tech book club, goes for bike rides, is a novice glassblower — and attends Burning Man every year.

That’s how Carlos Uranga, a Silicon Valley investor and former director of Singularity University’s Innovation Lab, heard of Montoya — and became intrigued with her proposal. “There’s an AI space race taking place right now,” he says, but Montoya’s approach of combining disciplines to get there is something he, a self-professed generalist, found appealing. “AI is the glue between robotics, computer vision [and] bioengineering,” he says.

Montoya’s not just helping make the field more diverse, Uranga believes, but she’s also demonstrating to millennials that multiple proficiencies can be the key to success — which challenges the current “everyone must specialize” model. His concern, however, is that it’s hard to stand out in such a competitive landscape, and her online footprint is dwarfed by companies like Udacity, which launched an AI training program in October 2016.

Realist that she is, Montoya knows she can’t change the world; she’s OK with just a little bit of the future becoming a better, bias-free place as a result of the work she’s putting in today. Can’t argue with that.

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