The AI ​​leader trying to attract more Latin American women to the technology industry

Belen Sanchez Hidalgoa senior data scientist at data robot, is passionate about getting more women into AI and machine learning roles. That’s why she created DataRobot University WaiCAMPa scholarship-based, seven-week bootcamp-style course for women in Latin America to learn applied data science and AI-related skills.

They have just finished their first cohort, which awarded scholarships to 60 Latin American women who live in 11 different countries and hope to expand globally.

talk to Sanchez Hidalgo about what’s next for the show along with your ideas on how to close out the gender gap in AI.

Amy Shoenthal: Tell me about your career pivot from public policy to technology and how you came to data robot.

Belen Sanchez Hidalgo: I worked for more than a decade in public policy and international development. A big part of my work was innovation and technology, researching how to boost productivity for small and medium-sized businesses. When I was working at the World Bank in 2016, all these reports on “the future of workstarted to go 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 would not be valuable in three years. A few days later, he sent me a photo of one of Amazon’s drones making deliveries in Washington, DC, joking, ‘the robots are coming!’

Jokes aside, that’s when I made the decision to leave the World Bank and learn more about automation. I signed up for a Intensive 12 Week Data Science Immersive Course at General Assemblyand 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 into the tech industry and started working at DataRobot. I started 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. Many companies at the time were willing to invest in this type of training so that people with experience in other industries could make an easy transition to technology.

Shoenthal: What motivated you to create this program and how did DataRobot support it?

Sanchez Hidalgo: One of the great programs that DataRobot has is called Dream Big, a weekend dive where employees are invited to think about their long-term goals. I was a little skeptical at first but I went and it was really amazing. It gave me the opportunity to think about what I wanted to achieve in life, from health to finances and more. One of the areas we explored was legacy, which can be defined in many different ways.

For many, the legacy was about raising their children. I have always been motivated to do things that have a positive impact on the lives of others. That’s why I originally went into public policy. When I transitioned to technology, I realized that piece was missing.

That weekend offered clarity on two things. One of them was about celebrating my two identities: I am Latina, from Ecuador, and I am a woman.

Second, I wanted to do something that would accelerate the adoption of artificial intelligence in Latin America. Having worked in the technology 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 up to speed on new technologies, that can translate into slower economic growth. I wanted to see my region flourish.

Combining my identities with my passion, I realized my legacy could be bringing 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 contact was with the team at Women in Ai, an international organization with a community of 5,000 AI professionals worldwide. They said that my idea aligned perfectly with what they were trying to do. Susan Verdiguel, the ambassador of Mujeres en Ai México, brought an incredible team of volunteers to gather the first cohort. Although the partnership was with Mujeres en AI México, the program reached 60 women in 11 countries in Latin America and the Caribbean.

Then I talked to my colleagues at DataRobot and they jumped on board right away. They realized that it would be a small elevator that would make a big impact. I was able to find amazing ambassadors within the organization. We had a team of people in the marketing, localization, logistics, curriculum development, and many other departments. It was really a team effort.

It took six months of development and we released it in August.

Shoenthal: Much has been written about the AI ​​gender gap and the pitfalls of not having a diverse workforce available to program AI software, hardware, and applications. Can you tell me why it is so important to diversify the industry?

Sanchez Hidalgo: Greater diversity would help avoid biased AI solutions. It has algorithms that define what type of marketing you are going to receive or if you are going to be approved for a mortgage or not.

The World Economic Forum did research that showed only 22% of AI professionals they are women.

How are we perpetuating stereotypes through AI? If you think about the voices of all AI assistants like Alexa, they default to women because women are seen as more submissive. As long as machine learning lacks diverse perspectives, it will 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 ourselves, how is AI affecting the workplace? We are still expected to see more jobs replaced by automation. But Ai will also create more jobs. The part that concerns me is that there have been studies showing that women will be more affected than men in this transition to new jobs.

Administrative roles like secretaries will be easier to automate. So women, who hold the majority of those roles, need to transition into the new jobs that AI will create, and they need the training and tools to do so. Also, once they get into the tech industry in general, they should see better benefits and higher compensation.

Shoenthal: Why do you focus specifically on Latin America for this program? Do you hope to expand it to other regions in the future?

Sanchez 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 is a great desire to go beyond Latin America. I want to expand so we can make it available to women globally. We’re trying to figure out what it takes to make that leap.

Shoenthal: What would you say to young women who are curious about exploring AI as a possible career path?

Sanchez Hidalgo: Don’t be afraid to start learning new skills. You don’t have to go back to college or university. We live in an age where information is accessible. Take advantage of online courses, bootcamps and more. It’s certainly a time commitment, but given the stakes, it’s worth acting on. Take it seriously and take advantage of the different ways you can learn.

The other thing is that to participate in AI machine learning, you don’t necessarily have to become a programmer. If you are afraid of coding, that is not a barrier for this industry. All of my previous work and experience was relevant to what I am doing now. Data scientists need support to fully understand certain business issues. Learning more only gives you more options. Don’t underestimate the value of that.

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