Earlier this year, nonprofit Technovation announced The AI Forward Alliance, a collaboration intended to increase the number of young women in the AI industry. This is one of many initiatives the organization has leveraged to keep its curriculum cutting-edge since its inception in 2006.
We spoke to founder Tara Chklovski, Ph.D., about Technovation’s mission, its AI initiatives, and how businesses can support young women in their careers. Bringing more women and girls into the AI industry brings the courage needed to solve problems like bias, she said.
What is Technovation?
Technovation is an educational nonprofit that operates around the world. Girls and young women ages 8 to 18 can join the program to create a project that benefits their local communities using technology. The project takes about 12 weeks.
Each girl or team of girls is paired with a mentor — for younger girls, a parent — who helps them identify problems and find technological solutions. One group from a rural area in Kenya trained AI to recognize gunshot sounds in order to speed up responses to crime from law enforcement. Other groups created apps to assist women in reporting domestic violence or an app connected to a vibrating bracelet that alerts deaf or hard-of-hearing people to fire, weather, or other alarms.
“We are the only program that is global, fully focused on girls, and has long-term data to show that because of the deep technology experience they go into higher degrees in computer science and into the tech careers at a much higher rate than normal,” said Chklovski.
She said 76% of Technovation graduates go into computer science degrees, and 60% go into tech careers, specifically because of their participation in the program. Chklovski attributes this success in part to putting problem-solving first.
“Instead of walking you through the fundamentals of programming and, at the end, you have a project, we flipped it to say, how do you identify meaningful problems that are going to change the world?” she said.
Participants emerge from their project with a robust business plan and pitch, as well as demo videos for their product.
Encouraging girls to get into forward-looking tech enriches the industry with people confident enough to introduce new ideas, Chklovski said.
“You just want a workforce that’s courageous, that can come up with new ideas,” she said. “The heart of innovation is new ideas, different ideas, different ways of thinking.”
AI is the latest of Technovation’s tools for solving local problems
The AI Forward Alliance is a collaboration between Technovation, UNICEF, Google, and other organizations with the goal of impacting 25 million young women. Specifically, the alliance seeks to foster problem-solving skills, complex systems thinking, data science, and machine learning.
Chklovski pointed out that AI isn’t Technovation’s sole focus, but it has been a part of its efforts for several years.
“We started doing an AI-in-action kind of curriculum eight years ago,” said Chklovski. “We are coming to this AI conversation with … tons of data on what works, what doesn’t work. The whole [generative] AI boom is only accelerating. What we have seen is exciting and interesting to young girls.
“The AI Forward Alliance really is about bringing cutting-edge technology. At the moment, it’s AI, but maybe in five to 10 years, maybe it’s quantum computing. So, we are in some sense tech-agnostic. It’s more about what’s relevant to workforce training, what’s the most powerful tool to tackle the big, complex problems we face.”
Bad data in, bad data out
Chklovski acknowledges that generative AI can cause, as The AI Forward Alliance stated, “contention and concern” — particularly when it comes to AI hallucinations, which occur when an AI model generates inaccurate or misleading information but presents it as if it were true.
“There’s so much room for improvement,” Chklovski said in response to concerns about AI hallucinations. “And I think the way to do that is to improve the data set.”
For example, Technovation projects need to have data on local issues to solve local problems.
“We work with orphanages across Vietnam, and the girls are very concerned that the standard image recognition models that are accessible do not recognize Vietnamese facial expressions,” said Chklovski. “And so they developed their own data set and trained it so that it could work for their population.”
SEE: Stay up-to-date on artificial intelligence with TechRepublic’s cheat sheet.
Women in AI: How businesses can encourage young women in tech
Despite years of progress in various sectors, the tech industry continues to grapple with a longstanding issue: the persistent underrepresentation of women.
Recent research shows that women hold about 26% of tech-related jobs in the U.S., despite women comprising nearly half of the labor force. Women make up 35% of all employees in computer system design and related services in the U.S.
Improving gender equity in the workplace reduces the chance that products, including generative AI, will show bias. A 2018 study from Deloitte found that when organizational leaders foster inclusion, 70% of workers report an increase in “respect, value, and longing,” as well as “psychological safety; and inspiration.”
Conversely, having fewer women in tech limits the pool of people who can help businesses find solutions to real problems. For example, projects worked on in Technovation groups often align with the UN General Assembly’s global goals.
To encourage young women to pursue or continue tech careers, businesses should look outside traditional college pipelines for the skills they want to hire, Chklovski said. Many conversations about AI in education are “myopic,” she suggested, because the technology moves too quickly.
“Prompt engineering is something else. People talk about it, and I think that that’s aiming too low,” she said. “Because by the time you develop the curriculum, you train the teachers, you deploy this at large scale, the technology has already changed. It’s more important to teach young people, especially, to build future-proof skills where lifelong learning is the key.”
Recruiters should search for products young women like the graduates of Technovation have already built and the problems they have solved. For example, Chklovski said, a Technovation team created an Uber-like app in 2010, before the proliferation of rideshare companies. Another group created an app that encouraged digital “focus time,” long before it was a common mantra that people might struggle with attentiveness in a flood of digital information.
She suggested businesses bring a project-first, hands-on approach to workplace training, encouraging people to pick a problem and learn to solve it rather than watching “extremely boring” training courses.
Businesses should also consider internships for young women who hold computer science degrees or have hand-on experience from beyond the top 20 universities, Chklovski noted.
“We have 11,000 alumna who are above the age of 18 — looking for internships, early career opportunities — and have a robust portfolio to show what they have built, what kinds of problems they have solved,” she said. “It takes away some of the uncertainties from hiring.”