The AI Leader Bringing More Latin American Women Into Tech
By Amy Shoenthal
Belén Sánchez Hidalgo, a senior data scientist at DataRobot, is passionate about getting more women into Artificial Intelligence and machine learning roles. That’s why she created WaiCAMP by DataRobot University, a scholarship-based seven week bootcamp-style course for women in Latin America to learn applied data science and AI-related skills.
They just wrapped their first cohort, which provided scholarships to 60 Latin American women living across 11 different countries, and are hoping to expand globally.
I spoke to Sánchez Hidalgo about what’s next for the program along with her ideas for how to close the gender gap in AI.
Amy Shoenthal: Tell me about your career pivot from public policy to tech and how you arrived at DataRobot.
Belén Sánchez Hidalgo: I worked for over a decade in public policy and international development. A big part of my work was innovation and tech, looking into how to foster productivity for small and medium sized enterprises. When I was working at the World Bank in 2016, all these reports about “the future of work” started coming out.
I panicked about how the workplace was going to change and how automation was going to take jobs. I told my husband, Zaki, that our skills weren’t going to be valuable in three years. A few days later, he sent me a picture of one of the Amazon drones making deliveries in Washington, DC, joking, ‘the robots are coming!’
Kidding aside, that’s when I made the decision to quit the World Bank and learn more about automation. I signed up for a 12 week intense data science immersive course at General Assembly, and that was the beginning of the transition.
After that, I was able to get my first job as a data scientist and technology advisor for the Inter-American Development Bank, combining the skills I had from my public policy and development days with my new data science education.
In 2019, I officially moved to the tech industry and started working at DataRobot. I began as an applied data science associate through a six month program where the company trained people who had experience in a specific field but were new to data science. A lot of companies at the time were willing to invest in this type of training so people with other industry experience could make an easy transition to tech.
Shoenthal: What motivated you to create this program and how did DataRobot support that?
Sánchez Hidalgo: One of the cool programs DataRobot has is called Dream Big, a weekend immersion where employees are invited to think about their long term goals. I was a bit skeptical at first, but I went and it was actually amazing. It gave me the chance to think about what I wanted to achieve in life, from health to finance and more. One of the areas we explored was legacy, which can be defined in so many different ways.
For many, legacy was all about raising their kids. I’ve always been driven to do things that have a positive impact on the lives of others. That’s why I originally went into public policy. As I had made the transition to tech, I realized I was missing that piece.
That weekend offered clarity on two things. One of them was about celebrating my two identities – I’m Latina, from Ecuador, and I’m a woman.
Second, I wanted to do something that accelerated the adoption of artificial intelligence in Latin America. Having worked in the tech and innovation policy space, I know how much new technologies can accelerate the competitiveness and productivity of nations.
As we have seen throughout history, when regions are not on top of new technologies, that can translate to slower economic growth. I wanted to see my region flourish.
Combining my identities with my passion, I realized my legacy could be to bring more women into this industry. So I put all these pieces together and decided to create a training program for women in Latin America.
I started with a pitch. My first outreach was to the team at Women in Ai, an international organization with a community of 5,000 AI professionals worldwide. They said my idea aligned perfectly with what they were trying to do. Susan Verdiguel, the ambassador from Women in Ai Mexico, brought on an amazing team of volunteers to get the first cohort together. Even though the partnership was with Women in AI Mexico, the program reached 60 women in 11 Latin American and Caribbean countries.
Then I spoke to my colleagues at DataRobot and they were on board immediately. They realized this would be a small lift that would generate a huge impact. I was able to find amazing ambassadors within the organization. We had a team of people across the marketing, localization, logistics, curriculum development, and so many other departments. It was really a team effort.
It took six months of development, and we launched in August.
Shoenthal: There’s been a lot written about the AI gender gap and the pitfalls of not having a diverse staff on hand to program AI software, hardware and applications. Can you talk to me about why it’s so important to diversify the industry?
Sánchez Hidalgo: More diversity would help avoid biased AI solutions. You have algorithms defining what type of marketing you’re going to receive or whether you’re going to be approved for a mortgage or not.
The World Economic Forum did research that showed only 22% of AI professionals are women.
How are we perpetuating stereotypes through AI? If you think about the voices of all the AI assistants like Alexa, their default is women because women are seen as more submissive. As long as machine learning lacks diverse perspectives they’re going to produce biased results. AI tools will reflect the biases of those who are building them. Bringing more diverse women into the design process will help us avoid those pitfalls.
We also have to ask, how AI is impacting the workplace? We are still expected to see more jobs replaced by automation. But Ai is also going to create more jobs. The part worrying me is that there have been studies that show women will be more impacted than men in this transition towards new jobs.
Administrative roles like secretaries will be easier to automate. So women, who hold the majority of those roles, need to make the transition to the new jobs that AI is going to create, and they need the training and tools to do that. Plus, once they enter the tech industry in general, they should see better benefits and higher compensation.
Shoenthal: Why are you focusing specifically on Latin America for this program? Do you hope to expand it to other regions down the line?
Sánchez Hidalgo: We took the last few months to evaluate the results of the first program and receive feedback from the participants and the community. There’s a lot of appetite to go beyond Latin America. I want to expand so we can make it available to women on a global basis. We’re trying to figure out what it will take to make that leap.
Shoenthal: What would you say to young women who are curious about exploring AI as a possible career path?
Sánchez Hidalgo: Don’t be afraid to start learning new skills. You don’t have to go back to college or university. We’re living in a time where information is accessible. Take advantage of online courses, bootcamps and more. It’s certainly a time commitment, but given what’s at stake, it’s worth taking action. Take it seriously and take advantage of all the different ways you can learn.
The other thing is, in order to be involved in AI machine learning, you don’t necessarily have to become a programmer. If you’re afraid of coding, that’s not a barrier to this industry. All my previous work and expertise was relevant to what I’m doing now. Data scientists need support to fully understand certain business problems. Learning more just gives you more choices. Don’t underestimate the value of that.
Photo Source: Diego Pallero