Rachel Thomas wants you to join the AI workforce, and she has a plan to make that happen.
On Tuesday at MIT Technology Review’s annual EmTech Digital conference in San Francisco, the cofounder of Fast.ai, a company that offers free classes on deep learning, argued that AI is not as inaccessible as it seems.
In an onstage presentation, Thomas discussed what are stereotypically considered prerequisites to working in AI, like a PhD, big data sets, and access to expensive computing power. She then gave examples of AI systems that defy those expectations, like a neural network one of her students created using a training technique that needed only 30 data points to work. She also pointed out the availability of a cloud-based GPU that cost just 45 cents an hour.
“The barriers to using AI are lower than you may think,” she said.
Diverse viewpoints are essential to creating AI that tackles problems outside the purview of Silicon Valley. Thomas recounted the example of a farmer signing up for Fast.ai’s class to develop an algorithm to better monitor the health of his goats’ udders.
“You know about problems no one else knows about,” she says.
Thomas believes that having more diversity within the AI world will also help with the problems of bias and fairness that currently bedevil the industry. She thinks that more diverse teams can prevent problems like the tendency of Google’s Photos app to label black people as “gorillas” and the implied racism uncovered by ProPublica in an algorithm being used for bail decisions in Florida.
“The field has a bit of exclusivity problem,” Thomas said. “The world really needs all of you involved in AI.”
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