AI leader is trying to bring more Latin American women into the tech industry

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Belen Sanchez Hidalgosenior data scientist at data crawler, is passionate about bringing more women into roles in artificial intelligence and machine learning. That’s why she created WaiCAMP by DataRobot Universitya seven-week scholarship-based bootcamp-style course for Latin American women to learn applied data science and AI-related skills.

They have just completed their first cohort, which provided scholarships to 60 Latin American women living in 11 different countries, and hope to expand globally.

I talked to Sanchez Hidalgo on the continuation of the program as well as his ideas on how to close the gender gap in AI.

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

Belen Sanchez Hidalgo: I have worked for over a decade in the field of public policy and international development. Much of my work was innovation and technology, looking at how to foster productivity in small and medium-sized businesses. When I was working at the World Bank in 2016, all these reports on “the future of work“started to come 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 useful in three years. A few days later, he sent me a photo of one of the Amazon drones doing deliveries in Washington, DC, joking, “the robots are coming!”

All kidding aside, that’s when I made the decision to leave the World Bank and learn more about automation. I signed up for a Intense 12-week immersive course in data science 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 science background. Datas.

In 2019, I officially moved into the tech industry and started working at DataRobot. I started as an Associate in Applied Data Science in a six-month program where the company trained people who had experience in a specific area but were new to science. Datas. At the time, many companies 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 DataRobot’s cool programs is called Dream Big, an immersion weekend where employees are encouraged to think about their long-term goals. I was a little skeptical at first, but I went and it was truly amazing. It gave me the chance to reflect on what I wanted to achieve in life, from health to finances and more. One of the areas we explored was inheritance, which can be defined in so many different ways.

For many, 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 first got into public policy. As I had made the transition to technology, I realized I was missing this piece.

This weekend clarified two things. One of them was to celebrate my two identities – I’m Latina, from Ecuador, and I’m female.

Second, I wanted to do something that accelerates the adoption of artificial intelligence in Latin America. Having worked in technology and innovation policy, I know how new technologies can accelerate the competitiveness and productivity of nations.

As we have seen throughout history, when regions do not master new technologies, it can result in slower economic growth. I wanted to see my region flourish.

By combining my identities with my passion, I realized that 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 Latin American women.

I started with a pitch. My first sensitization was with the team of Women in Ai, an international organization with a community of 5,000 AI professionals worldwide. They said my idea fit perfectly with what they were trying to do. Susan Verdiguel, the ambassador of Women in Ai Mexico, enlisted an incredible team of volunteers to bring together the first cohort. Although the partnership was with Women in AI Mexico, the program reached 60 women in 11 countries in Latin America and the Caribbean.

Then I spoke to my colleagues at DataRobot and they immediately joined me. They realized it would be a small lift that would generate a huge impact. I was able to find incredible ambassadors within the organization. We had a team of people in marketing, localization, logistics, program development, and so many other departments. It was really teamwork.

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

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

Sanchez Hidalgo: More diversity would help avoid biased AI solutions. You have algorithms defining what type of marketing you are going to receive or whether or not you are going to be approved for a mortgage.

The World Economic Forum has done research that has only shown 22% of AI professionals are women.

How do we perpetuate stereotypes with AI? If you think about the voices of all AI assistants like Alexa, their default voice is female because females are considered more submissive. As long as machine learning lacks diverse perspectives, it will produce biased results. AI tools will reflect the biases of those who build them. Bringing more diverse women into the design process will help us avoid these pitfalls.

We also need to ask ourselves what is the impact of AI in the workplace? It is still expected that more jobs will be replaced by automation. But Ai will also create more jobs. What worries me is that there have been studies that show 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 fill the majority of these roles, need to transition into the new jobs that AI will create, and they need the training and tools to do so. Additionally, once they enter the general tech industry, they should see better benefits and higher compensation.

Shoenthal: Why are you focusing specifically on Latin America for this program? Do you hope to extend it to other regions later?

Sanchez Hidalgo: We have taken the last few months to evaluate the results of the first program and receive feedback from participants and the community. There is a lot of 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 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?

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 is certainly a time commitment, but given what is at stake, it is worth taking action. Take it seriously and enjoy all the different ways you can learn.

The other thing is that to be involved in AI machine learning, you don’t necessarily have to become a programmer. If you are afraid of coding, it is not a hindrance to this industry. All of my previous work and expertise was relevant to what I do now. Data scientists need support to fully understand certain business issues. Knowing more just gives you more choices. Don’t underestimate the value of this.

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